RMCP Vol. 11, Num. 1 (2020): January-March [english version] by Revista Mexicana de Ciencias Pecuarias

Edición Bilingüe Bilingual Edition

Revista Mexicana de Ciencias Pecuarias Rev. Mex. Cienc. Pecu. Vol. 11 Núm. 1, pp. 1-310, ENERO-MARZO-2020

ISSN: 2448-6698

Rev. Mex. Cienc. Pecu. Vol. 11 Núm. 1, pp. 1-310, ENERO-MARZO-2020

REVISTA MEXICANA DE CIENCIAS PECUARIAS Volumen 11 Número 1, EneroMarzo, 2020. Es una publicación trimestral de acceso abierto, revisada por pares y arbitrada, editada por el Instituto Nacional de Investigaciones Forestales, Agrícolas y Pecuarias (INIFAP). Avenida Progreso No. 5, Barrio de Santa Catarina, Delegación Coyoacán, C.P. 04010, Cuidad de México, www.inifap.gob.mx Distribuida por el Centro Nacional de Investigación Disciplinaria en Salud Animal e Inocuidad, Km 15.5 Carretera México-Toluca, Colonia Palo Alto, Cuidad de México, C.P. 05110. Editor responsable: Arturo García Fraustro. Reservas de Derechos al Uso Exclusivo número 04-2016-060913393200-203. ISSN: 2448-6698, otorgados por el Instituto Nacional del Derecho de Autor (INDAUTOR). Responsable de la última actualización de este número: Arturo García Fraustro, Centro Nacional de Investigación Disciplinaria en Salud Animal e Inocuidad, Km. 15.5 Carretera México-Toluca, Colonia Palo Alto, Ciudad de México, C.P. 015110. http://cienciaspecuarias. inifap.gob.mx, la presente publicación tuvo su última actualización en marzo de 2020. Alimentaciòn con follaje de Erythrina americana Miller en ovejas Blackbelly x Pelibuey en Tabasco. Fotografía tomada por: Jorge Oliva Hernández

DIRECTORIO FUNDADOR John A. Pino EDITORES ADJUNTOS Oscar L. Rodríguez Rivera Alfonso Arias Medina

EDITOR EN JEFE Arturo García Fraustro

EDITORES POR DISCIPLINA Dra. Yolanda Beatriz Moguel Ordóñez, INIFAP, México Dr. Ramón Molina Barrios, Instituto Tecnológico de Sonora, México Dra. Maria Cristina Schneider, PAHO, Estados Unidos Dra. Elisa Margarita Rubí Chávez, UNAM, México Dr. Feliciano Milian Suazo, Universidad Autónoma de Querétaro, México Dr. Javier F. Enríquez Quiroz, INIFAP, México Dra. Martha Hortencia Martín Rivera, Universidad de Sonora URN, México Dr. Fernando Arturo Ibarra Flores, Universidad de Sonora URN, México Dr. James A. Pfister, USDA, Estados Unidos Dr. Eduardo Daniel Bolaños Aguilar, INIFAP, México Dr. Sergio Iván Román-Ponce, INIFAP, México Dr. Jesús Fernández Martín, INIA, España Dr. Sergio D. Rodríguez Camarillo, INIFAP, México Dr. Martin Talavera Rojas, Universidad Autónoma del Estado de México, México Dra. Maria Salud Rubio Lozano, Facultad de Medicina Veterinaria y Zootecnia, UNAM, México Dra. Elizabeth Loza-Rubio, INIFAP, México Dr. Juan Carlos Saiz Calahorra, Instituto Nacional de Investigaciones Agrícolas, España Dra. Silvia Elena Buntinx Dios, Facultad de Medicina Veterinaria y Zootecnia, UNAM, México Dr. José Armando Partida de la Peña, INIFAP, México Dr. José Luis Romano Muñoz, INIFAP, México. Dr. Alejandro Plascencia Jorquera, Universidad Autónoma de Baja California, México Dr. Juan Ku Vera, Universidad Autónoma de Yucatán, México Dr. Ricardo Basurto Gutiérrez, INIFAP, México. Dr. Luis Corona Gochi, Facultad de Medicina Veterinaria y Zootecnia, UNAM, México Dr. Juan Manuel Pinos Rodríguez, Facultad de Medicina Veterinaria y Zootecnia, Universidad Veracruzana, México Dr. Carlos López Coello, Facultad de Medicina Veterinaria y Zootecnia, UNAM, México Dr. Arturo Francisco Castellanos Ruelas, Facultad de Química. UADY Dra. Guillermina Ávila Ramírez, UNAM, México. Dr. Emmanuel Camuus, CIRAD, Francia. Dr. Héctor Jiménez Severiano, INIFAP., México Dr. Juan Hebert Hernández Medrano, UNAM, México. Dr. Adrian Guzmán Sánchez, Universidad Autónoma Metropolitana-Xochimilco, México Dr. Eugenio Villagómez Amezcua Manjarrez, INIFAP, CENID Salud Animal e Inocuidad, México Dr. Fernando Cervantes Escoto, Universidad Autónoma Chapingo, México Dr. Adolfo Guadalupe Álvarez Macías, Universidad Autónoma Metropolitana Xochimilco, México Dr. Alfredo Cesín Vargas, UNAM, México.

TIPOGRAFÍA Y FORMATO Nora del Rocío Alfaro Gómez Indizada en el “Journal Citation Report” Science Edition del ISI . Inscrita en el Sistema de Clasificación de Revistas Científicas y Tecnológicas de CONACyT; en EBSCO Host y la Red de Revistas Científicas de América Latina y el Caribe, España y Portugal (RedALyC) (www.redalyc.org); en la Red Iberoamericana de Revistas Científicas de Veterinaria de Libre Acceso (www.veterinaria.org/revistas/ revivec); en los Índices SCOPUS y EMBASE de Elsevier (www.elsevier. com).

REVISTA MEXICANA DE CIENCIAS PECUARIAS La Revista Mexicana de Ciencias Pecuarias es un órgano de difusión científica y técnica de acceso abierto, revisada por pares y arbitrada. Su objetivo es dar a conocer los resultados de las investigaciones realizadas por cualquier institución científica, relacionadas particularmente con las distintas disciplinas de la Medicina Veterinaria y la Zootecnia. Además de trabajos de las disciplinas indicadas en su Comité Editorial, se aceptan también para su evaluación y posible publicación, trabajos de otras disciplinas, siempre y cuando estén relacionados con la investigación pecuaria.

total por publicar es de $ 5,600.00 más IVA por manuscrito ya editado. Se publica en formato digital en acceso abierto, por lo que se autoriza la reproducción total o parcial del contenido de los artículos si se cita la fuente. El envío de los trabajos de debe realizar directamente en el sitio oficial de la revista. Correspondencia adicional deberá dirigirse al Editor Adjunto a la siguiente dirección: Calle 36 No. 215 x 67 y 69 Colonia Montes de Amé, C.P. 97115 Mérida, Yucatán, México. Tel/Fax +52 (999) 941-5030. Correo electrónico (C-ele): rodriguez_oscar@prodigy.net.mx.

Se publican en la revista tres categorías de trabajos: Artículos Científicos, Notas de Investigación y Revisiones Bibliográficas (consultar las Notas al autor); la responsabilidad de cada trabajo recae exclusivamente en los autores, los cuales, por la naturaleza misma de los experimentos pueden verse obligados a referirse en algunos casos a los nombres comerciales de ciertos productos, ello sin embargo, no implica preferencia por los productos citados o ignorancia respecto a los omitidos, ni tampoco significa en modo alguno respaldo publicitario hacia los productos mencionados.

La correspondencia relativa a suscripciones, asuntos de intercambio o distribución de números impresos anteriores, deberá dirigirse al Editor en Jefe de la Revista Mexicana de Ciencias Pecuarias, CENID Salud Animal e Inocuidad, Km 15.5 Carretera México-Toluca, Col. Palo Alto, D.F. C.P. 05110, México; Tel: +52(55) 3871-8700 ext. 80316; garcia.arturo@inifap.gob.mx o arias.alfonso@inifap.gob.mx. Inscrita en la base de datos de EBSCO Host y la Red de Revistas Científicas de América Latina y el Caribe, España y Portugal (RedALyC) (www.redalyc.org), en la Red Iberoamericana de Revistas Científicas de Veterinaria de Libre Acceso (www.veterinaria.org/revistas/ revivec), indizada en el “Journal Citation Report” Science Edition del ISI (http://thomsonreuters. com/) y en los Índices SCOPUS y EMBASE de Elsevier (www.elsevier.com)

Todas las contribuciones serán cuidadosamente evaluadas por árbitros, considerando su calidad y relevancia académica. Queda entendido que el someter un manuscrito implica que la investigación descrita es única e inédita. La publicación de Rev. Mex. Cienc. Pecu. es trimestral en formato bilingüe Español e Inglés. El costo

VISITE NUESTRA PÁGINA EN INTERNET Artículos completos desde 1963 a la fecha y Notas al autor en: http://cienciaspecuarias.inifap.gob.mx Revista Mexicana de Ciencias Pecuarias is an open access peer-reviewed and refereed scientific and technical journal, which publishes results of research carried out in any scientific or academic institution, especially related to different areas of veterinary medicine and animal production. Papers on disciplines different from those shown in Editorial Committee can be accepted, if related to livestock research.

Part of, or whole articles published in this Journal may be reproduced, stored in a retrieval system or transmitted in any form or by any means, electronic, mechanical, photocopying or otherwise, provided the source is properly acknowledged. Manuscripts should be submitted directly in the official web site. Additional information may be mailed to Associate Editor, Revista Mexicana de Ciencias Pecuarias, Calle 36 No. 215 x 67 y 69 Colonia Montes de Amé, C.P. 97115 Mérida, Yucatán, México. Tel/Fax +52 (999) 941-5030. E-mail: rodriguez_oscar@prodigy.net.mx.

The journal publishes three types of papers: Research Articles, Technical Notes and Review Articles (please consult Instructions for authors). Authors are responsible for the content of each manuscript, which, owing to the nature of the experiments described, may contain references, in some cases, to commercial names of certain products, which however, does not denote preference for those products in particular or of a lack of knowledge of any other which are not mentioned, nor does it signify in any way an advertisement or an endorsement of the referred products.

For subscriptions, exchange or distribution of previous printed issues, please contact: Editor-in-Chief of Revista Mexicana de Ciencias Pecuarias, CENID Salud Animal e Inocuidad, Km 15.5 Carretera México-Toluca, Col. Palo Alto, D.F. C.P. 05110, México; Tel: +52(55) 3871-8700 ext. 80316; garcia.arturo@inifap.gob.mx or arias.alfonso@inifap.gob.mx. Registered in the EBSCO Host database. The Latin American and the Caribbean Spain and Portugal Scientific Journals Network (RedALyC) (www.redalyc.org). The Iberoamerican Network of free access Veterinary Scientific Journals (www.veterinaria.org/ revistas/ revivec). Thomson Reuter´s “Journal Citation Report” Science Edition (http://thomsonreuters.com/). Elsevier´s SCOPUS and EMBASE (www.elsevier.com) and the Essential Electronic Agricultural Library (www.teeal.org).

All contributions will be carefully refereed for academic relevance and quality. Submission of an article is understood to imply that the research described is unique and unpublished. Rev. Mex. Cien. Pecu. is published quarterly in original lenguage Spanish or English. Total fee charges are US $ 325.00 per article in both printed languages.

VISIT OUR SITE IN THE INTERNET Full articles from year 1963 to date and Instructions for authors can be accessed via the site http://cienciaspecuarias.inifap.gob.mx

REVISTA MEXICANA DE CIENCIAS PECUARIAS REV. MEX. CIENC. PECU.

VOL. 11 No. 1

ENERO-MARZO-2020

CONTENIDO ARTÍCULOS

Pág. Producción de leche de vacas en pastoreo de alfalfa (Medicago sativa) en el altiplano mexicano Milk production in dairy cows grazing alfalfa (Medicago sativa) in the central Mexican highlands Vicente Lemus Ramírez, Aurelio Guevara Escobar, Juan Antonio García Rodríguez, Delia Gaspar Sánchez, José Guadalupe García Muñiz, David Pacheco Ríos…………………………………………............1

Efecto de la mezcla ensilada de Pennisetum purpureum y Tithonia diversifolia sobre la fermentación ruminal in vitro y su emisión de metano en el sistema RUSITEC Effect of a Pennisetum purpureum and Tithonia diversifolia silage mixture on in vitro ruminal fermentation and methane emission in a RUSITEC system

Vilma A. Holguín, Mario Cuchillo-Hilario, Johanna Mazabel, Steven Quintero, Jairo Mora-Delgado .…19

Growth dynamics and senescence of digit grass as a response to several canopy heights Dinámica de crecimiento y senescencia del pasto pangola como respuesta a diversas alturas de corte José Dantas Gusmão Filho,Daniela Deitos Fries, Braulio Maia de Lana Sousa, Jailson Lara Fagundes, Alfredo Acosta Backes, Daniel Lucas Santos Dias, Sarita Socorro Campos Pinheiro, Fábio Andrade Teixeira ..................................................................................................................................................38

Rendimiento y calidad nutritiva del forraje en un sistema silvopastoril intensivo con Leucaena leucocephala y Megathyrsus maximus cv. Tanzania Forage yield and nutritional quality in Leucaena leucocephala and Megathyrsus maximus cv. Tanzania in an intensive silvopastoral system Manuel Hernández Hernández, Silvia López Ortiz, Jesús Jarillo Rodríguez, Eusebio Ortega Jiménez, Sergio Pérez Elizalde, Pablo Díaz Rivera, María Magdalena Crosby Galván .........................................53

Consumo de follaje de Erythrina americana Miller en ovejas Blackbelly x Pelibuey Erythrina americana Miller foliage intake in Blackbelly x Pelibuey ewes Diana Fabiola Hernández-Espinoza, Jesús Alberto Ramos-Juárez, Roberto González-Garduño, Luz del Carmen Lagunes-Espinoza, María Aurelia López-Herrera, Jorge Oliva-Hernández ..............................70

III

Pasture structure and sheep performance supplemented on different tropical grasses in the dry season Estructura del pasto, y rendimiento de ovejas suplementadas con diferentes pastos tropicales en la estación seca Leonardo Santana Fernandes, Gelson dos Santos Difante, Marcone Geraldo Costa, João Virgínio Emerenciano Neto, Itânia Maria Medeiros de Araújo, Joederson Luiz Santos Dantas, Antonio Leandro Chaves Gurgel ........................................................................................................................................89

In vitro production of porcine embryos with use of chemically semi-defined culture media system Producción in vitro de embriones porcinos con el uso de un sistema de medios de cultivo químicamente semi-definidos

David Urbán Duarte, Horacio Álvarez Gallardo, Sandra Pérez Reynozo, José Fernando De la Torre Sánchez ............................................................................................................................................... 102

Transmission of Anaplasma marginale by unfed Rhipicephalus microplus tick larvae under experimental conditions Transmisión de Anaplasma marginale por larvas no alimentadas de garrapata Rhipicephalus microplus bajo condiciones experimentales Itzel Amaro Estrada, Miguel A. García-Ortiz, Jesús F. Preciado de la Torre, Edmundo E. Rojas-Ramírez, Rubén Hernández-Ortiz, Francisco Alpírez-Mendoza, Sergio D. Rodríguez Camarillo ...................... 116

Inclusion of concentrate and growth promoters’ additives in sheep diets on intake, digestibility, degradability, ruminal variables and nitrogen balance Inclusión de concentrado y de aditivos promotores de crecimiento en las dietas de ovinos sobre el consumo, digestibilidad, degradabilidad, variables ruminales y balance de nitrógeno Marcelo Vedovatto, Camila da Silva Pereira, João Artêmio Marin Beltrame, Ibrahin Miranda Cortada Neto, Anderson Luiz de Lucca Bento, Gabriella de Oliveira Dalla Martha, Maria da Graça Morais, Gumercindo Loriano Franco................................................................................................................ 132

Efecto del propóleo y aceite de orégano sobre parámetros productivos, leucocitos, metabolitos y estabilidad oxidativa de la pechuga de pollo Supplementation of broiler diets with propolis and oregano oil and its effect on production parameters, leukocytes, metabolites and breast meat antioxidant stability José Inés Ibarra-Espain, Carlos Alfredo Carmona-Gasca, Francisco Escalera-Valente, Fidel AvilaRamos ................................................................................................................................................. 153

Relación genética, formación de biopelículas, movilidad y virulencia de Escherichia coli aislada de mastitis bovina Genetic relationships, biofilm formation, motility and virulence of Escherichia coli isolated from bovine mastitis Alejandro Sergio Cruz-Soto, Valentín Toro-Castillo, Cristián Omar Munguía-Magdaleno, José Emmanuel Torres-Flores, Luis Enrique Flores-Pantoja, Pedro Damián Loeza-Lara, Rafael JiménezMejía ................................................................................................................................................... 167

Caracterización técnica y ambiental de fincas de cría pertenecientes a muy pequeños, pequeños, medianos y grandes productores Technical and environmental characterization of very small, small, medium and large cowcalf operations in Colombia Ricardo González–Quintero, María Solange Sánchez–Pinzón, Diana María Bolívar–Vergara, Ngonidzashe Chirinda, Jacobo Arango, Heiber Alexander Pantévez, Guillermo Correa–Londoño, Rolando Barahona–Rosales ................................................................................................................ 183

REVISIONES DE LITERATURA

Impacto del estrés por calor en la producción de ovinos de pelo. Revisión Heat stress impacts in hair sheep production. Review Ricardo Vicente Pérez, Ulises Macías Cruz, Leonel Avendaño Reyes, Abelardo Correa-Calderón, María de los Ángeles López Baca, Ana L. Lara Rivera .................................................................................. 205

Azospirillum spp. en gramíneas y forrajeras. Revisión Azospirillum spp. in grasses and forages. Review Camila Fernandes Domingues Duarte, Ulysses Cecato, Thiago Trento Biserra, Divaney Mamédio, Sandra Galbeiro .................................................................................................................................. 223

NOTAS DE INVESTIGACIÓN

Soil management and planting spacing effects on establishment of mixed swards of purple stargrass (Cynodon nlemfuensis cv. BRS Lua) and forage peanut (Arachis pintoi cv. Belmonte) in an area of degraded Brachiaria brizantha Efecto del manejo del suelo y espaciamiento de siembra en el establecimiento de la mezcla de pasto-estrella-púrpura (Cynodon nlemfuensis cv. BRS Lua) y maní forrajero (Arachis pintoi cv. Belmonte) en área degradada de Brachiaria brizantha Divaney Mamédio, Carlos Maurício Soares de Andrade, Aliedson Ferreira Sampaio, Daniele Rebouças Santana Loures ................................................................................................................................... 241

Dinámica de crecimiento y curvas de extracción de nutrientes de Pennisetum sp. (Maralfalfa) Growth dynamics and nutrient extraction curves of Pennisetum sp. (Maralfalfa) Oscar López-Astilleros, Julio Cesar Vinay Vadillo, Yuri Villegas-Aparicio, Isaías López Guerrero, Salvador Lozano-Trejo ........................................................................................................................ 255

In vitro ruminal degradation of carbohydrate fractions in tropical grasses fertilized with nitrogen Degradación ruminal in vitro de las fracciones de carbohidratos contenidas en pastos tropicales fertilizados con nitrógeno

Erika Andrea Hernández, Francisco Indalecio Juárez Lagunes, Alice N. Pell, Maribel Montero Lagunes, Juan Manuel Pinos Rodríguez, Robert W. Blake ................................................................................ 266

Frecuencia de SNP en genes candidatos para crecimiento y su efecto en caracteres de peso vivo en ganado para carne de Tamaulipas Frequency of SNP located in candidate genes for growth and their effect on live weight variables in beef cattle from Tamaulipas Ana María Sifuentes Rincón, Gaspar Manuel Parra Bracamonte, Williams Arellano Vera, Pascuala Ambriz Morales, Antonio Cantú Covarrubias, Víctor Ricardo Moreno Medina ................................... 283

Comportamiento productivo y valor nutricional de veza común (Vicia sativa l.) durante otoño-invierno en Zacatecas, México Yield and nutritional value of common vetch (Vicia sativa l.) during fall-winter in Zacatecas, Mexico Ricardo A. Sánchez-Gutiérrez, Juan José Figueroa-Gonzáles, José Saúl Rivera Vázquez, Manuel Reveles-Hernández, Héctor Gutiérrez-Bañuelos, Alejandro Espinoza-Canales ................................. 294

“Garrapata Hércules” Eragrostis superba (Peyr), variedad de pasto para zonas áridas y semiáridas “Wilman lovegrass Hercules”, Eragrostis superba (Peyr) a grass variety for arid and semiarid regions Sergio Beltrán López, Carlos Alberto García Díaz, Catarina Loredo Osti, Jorge Urrutia Morales, José Antonio Hernández Alatorre, Héctor Guillermo Gámez Vázquez ....................................................... 304

Actualización: marzo, 2020 NOTAS AL AUTOR La Revista Mexicana de Ciencias Pecuarias se edita completa en dos idiomas (español e inglés) y publica tres categorías de trabajos: Artículos científicos, Notas de investigación y Revisiones bibliográficas.

bibliográficas una extensión máxima de 30 cuartillas y 5 cuadros. 6.

Los autores interesados en publicar en esta revista deberán ajustarse a los lineamientos que más adelante se indican, los cuales en términos generales, están de acuerdo con los elaborados por el Comité Internacional de Editores de Revistas Médicas (CIERM) Bol Oficina Sanit Panam 1989;107:422-437. 1.

Sólo se aceptarán trabajos inéditos. No se admitirán si están basados en pruebas de rutina, ni datos experimentales sin estudio estadístico cuando éste sea indispensable. Tampoco se aceptarán trabajos que previamente hayan sido publicados condensados o in extenso en Memorias o Simposio de Reuniones o Congresos (a excepción de Resúmenes).

Todos los trabajos estarán sujetos a revisión de un Comité Científico Editorial, conformado por Pares de la Disciplina en cuestión, quienes desconocerán el nombre e Institución de los autores proponentes. El Editor notificará al autor la fecha de recepción de su trabajo.

El manuscrito deberá someterse a través del portal de la Revista en la dirección electrónica: http://cienciaspecuarias.inifap.gob.mx, consultando el “Instructivo para envío de artículos en la página de la Revista Mexicana de Ciencias Pecuarias”. Para su elaboración se utilizará el procesador de Microsoft Word, con letra Times New Roman a 12 puntos, a doble espacio. Asimismo se deberán llenar los formatos de postulación, carta de originalidad y no duplicidad y disponibles en el propio sitio oficial de la revista.

Por ser una revista con arbitraje, y para facilitar el trabajo de los revisores, todos los renglones de cada página deben estar numerados; asimismo cada página debe estar numerada, inclusive cuadros, ilustraciones y gráficas.

Los artículos tendrán una extensión máxima de 20 cuartillas a doble espacio, sin incluir páginas de Título, y cuadros o figuras (los cuales no deberán exceder de ocho y ser incluidos en el texto). Las Notas de investigación tendrán una extensión máxima de 15 cuartillas y 6 cuadros o figuras. Las Revisiones

Los manuscritos de las tres categorías de trabajos que se publican en la Rev. Mex. Cienc. Pecu. deberán contener los componentes que a continuación se indican, empezando cada uno de ellos en página aparte. Página del título Resumen en español Resumen en inglés Texto Agradecimientos y conflicto de interés Literatura citada

Página del Título. Solamente debe contener el título del trabajo, que debe ser conciso pero informativo; así como el título traducido al idioma inglés. En el manuscrito no es necesaria información como nombres de autores, departamentos, instituciones, direcciones de correspondencia, etc., ya que estos datos tendrán que ser registrados durante el proceso de captura de la solicitud en la plataforma del OJS (http://ciencias pecuarias.inifap.gob.mx).

Resumen en español. En la segunda página se debe incluir un resumen que no pase de 250 palabras. En él se indicarán los propósitos del estudio o investigación; los procedimientos básicos y la metodología empleada; los resultados más importantes encontrados, y de ser posible, su significación estadística y las conclusiones principales. A continuación del resumen, en punto y aparte, agregue debidamente rotuladas, de 3 a 8 palabras o frases cortas clave que ayuden a los indizadores a clasificar el trabajo, las cuales se publicarán junto con el resumen.

Resumen en inglés. Anotar el título del trabajo en inglés y a continuación redactar el “abstract” con las mismas instrucciones que se señalaron para el resumen en español. Al final en punto y aparte, se deberán escribir las correspondientes palabras clave (“key words”).

10. Texto. Las tres categorías de trabajos que se publican en la Rev. Mex. Cienc. Pecu. consisten en lo siguiente: a) Artículos científicos. Deben ser informes de trabajos originales derivados de resultados parciales o finales

VII

de investigaciones. El texto del Artículo científico se divide en secciones que llevan estos encabezamientos:

Procure abstenerse de utilizar los resúmenes como referencias; las “observaciones inéditas” y las “comunicaciones personales” no deben usarse como referencias, aunque pueden insertarse en el texto (entre paréntesis).

Introducción Materiales y Métodos Resultados Discusión Conclusiones e implicaciones Literatura citada

Reglas básicas para la Literatura citada Nombre de los autores, con mayúsculas sólo las iniciales, empezando por el apellido paterno, luego iniciales del materno y nombre(s). En caso de apellidos compuestos se debe poner un guión entre ambos, ejemplo: Elías-Calles E. Entre las iniciales de un autor no se debe poner ningún signo de puntuación, ni separación; después de cada autor sólo se debe poner una coma, incluso después del penúltimo; después del último autor se debe poner un punto.

En los artículos largos puede ser necesario agregar subtítulos dentro de estas divisiones a fin de hacer más claro el contenido, sobre todo en las secciones de Resultados y de Discusión, las cuales también pueden presentarse como una sola sección. b) Notas de investigación. Consisten en modificaciones a técnicas, informes de casos clínicos de interés especial, preliminares de trabajos o investigaciones limitadas, descripción de nuevas variedades de pastos; así como resultados de investigación que a juicio de los editores deban así ser publicados. El texto contendrá la misma información del método experimental señalado en el inciso a), pero su redacción será corrida del principio al final del trabajo; esto no quiere decir que sólo se supriman los subtítulos, sino que se redacte en forma continua y coherente.

El título del trabajo se debe escribir completo (en su idioma original) luego el título abreviado de la revista donde se publicó, sin ningún signo de puntuación; inmediatamente después el año de la publicación, luego el número del volumen, seguido del número (entre paréntesis) de la revista y finalmente el número de páginas (esto en caso de artículo ordinario de revista). Puede incluir en la lista de referencias, los artículos aceptados aunque todavía no se publiquen; indique la revista y agregue “en prensa” (entre corchetes).

c) Revisiones bibliográficas. Consisten en el tratamiento y exposición de un tema o tópico de relevante actualidad e importancia; su finalidad es la de resumir, analizar y discutir, así como poner a disposición del lector información ya publicada sobre un tema específico. El texto se divide en: Introducción, y las secciones que correspondan al desarrollo del tema en cuestión.

En el caso de libros de un solo autor (o más de uno, pero todos responsables del contenido total del libro), después del o los nombres, se debe indicar el título del libro, el número de la edición, el país, la casa editorial y el año. Cuando se trate del capítulo de un libro de varios autores, se debe poner el nombre del autor del capítulo, luego el título del capítulo, después el nombre de los editores y el título del libro, seguido del país, la casa editorial, año y las páginas que abarca el capítulo.

11. Agradecimientos y conflicto de interés. Siempre que corresponda, se deben especificar las colaboraciones que necesitan ser reconocidas, tales como a) la ayuda técnica recibida; b) el agradecimiento por el apoyo financiero y material, especificando la índole del mismo; c) las relaciones financieras que pudieran suscitar un conflicto de intereses. Las personas que colaboraron pueden ser citadas por su nombre, añadiendo su función o tipo de colaboración; por ejemplo: “asesor científico”, “revisión crítica de la propuesta para el estudio”, “recolección de datos”, etc. Siempre que corresponda, los autores deberán mencionar si existe algún conflicto de interés. 12. Literatura citada. Numere las referencias consecutivamente en el orden en que se mencionan por primera vez en el texto. Las referencias en el texto, en los cuadros y en las ilustraciones se deben identificar mediante números arábigos entre paréntesis, sin señalar el año de la referencia. Evite hasta donde sea posible, el tener que mencionar en el texto el nombre de los autores de las referencias.

En el caso de tesis, se debe indicar el nombre del autor, el título del trabajo, luego entre corchetes el grado (licenciatura, maestría, doctorado), luego el nombre de la ciudad, estado y en su caso país, seguidamente el nombre de la Universidad (no el de la escuela), y finalmente el año. Emplee el estilo de los ejemplos que aparecen a continuación, los cuales están parcialmente basados en el formato que la Biblioteca Nacional de Medicina de los Estados Unidos usa en el Index Medicus. Revistas

Artículo ordinario, con volumen y número. (Incluya el nombre de todos los autores cuando sean seis o

VIII

menos; si son siete o más, anote sólo el nombre de los seis primeros y agregue “et al.”). I)

Basurto GR, Garza FJD. Efecto de la inclusión de grasa o proteína de escape ruminal en el comportamiento de toretes Brahman en engorda. Téc Pecu Méx 1998;36(1):35-48.

forestales y agropecuarias del estado de Veracruz. Veracruz. 1990:51-56. XI)

Sólo número sin indicar volumen. II) Stephano HA, Gay GM, Ramírez TC. Encephalomielitis, reproductive failure and corneal opacity (blue eye) in pigs associated with a paramyxovirus infection. Vet Rec 1988;(122):6-10. III) Chupin D, Schuh H. Survey of present status ofthe use of artificial insemination in developing countries. World Anim Rev 1993;(74-75):26-35.

No se indica el autor. IV) Cancer in South Africa [editorial]. S Afr Med J 1994;84:15.

Suplemento de revista. V) Hall JB, Staigmiller RB, Short RE, Bellows RA, Bartlett SE. Body composition at puberty in beef heifers as influenced by nutrition and breed [abstract]. J Anim Sci 1998;71(Suppl 1):205.

Organización, como autor. VI) The Cardiac Society of Australia and New Zealand. Clinical exercise stress testing. Safety and performance guidelines. Med J Aust 1996;(164):282-284.

En proceso de publicación. VII) Scifres CJ, Kothmann MM. Differential grazing use of herbicide treated area by cattle. J Range Manage [in press] 2000.

Libros y otras monografías

Autor total. VIII) Steel RGD, Torrie JH. Principles and procedures of statistics: A biometrical approach. 2nd ed. New York, USA: McGraw-Hill Book Co.; 1980.

Autor de capítulo. IX)

Roberts SJ. Equine abortion. In: Faulkner LLC editor. Abortion diseases of cattle. 1rst ed. Springfield, Illinois, USA: Thomas Books; 1968:158-179.

Memorias de reuniones. X)

Loeza LR, Angeles MAA, Cisneros GF. Alimentación de cerdos. En: Zúñiga GJL, Cruz BJA editores. Tercera reunión anual del centro de investigaciones

Olea PR, Cuarón IJA, Ruiz LFJ, Villagómez AE. Concentración de insulina plasmática en cerdas alimentadas con melaza en la dieta durante la inducción de estro lactacional [resumen]. Reunión nacional de investigación pecuaria. Querétaro, Qro. 1998:13.

XII) Cunningham EP. Genetic diversity in domestic animals: strategies for conservation and development. In: Miller RH et al. editors. Proc XX Beltsville Symposium: Biotechnology’s role in genetic improvement of farm animals. USDA. 1996:13.

Tesis. XIII) Alvarez MJA. Inmunidad humoral en la anaplasmosis y babesiosis bovinas en becerros mantenidos en una zona endémica [tesis maestría]. México, DF: Universidad Nacional Autónoma de México; 1989. XIV) Cairns RB. Infrared spectroscopic studies of solid oxigen [doctoral thesis]. Berkeley, California, USA: University of California; 1965.

Organización como autor. XV) NRC. National Research Council. The nutrient requirements of beef cattle. 6th ed. Washington, DC, USA: National Academy Press; 1984. XVI) SAGAR. Secretaría de Agricultura, Ganadería y Desarrollo Rural. Curso de actualización técnica para la aprobación de médicos veterinarios zootecnistas responsables de establecimientos destinados al sacrificio de animales. México. 1996. XVII) AOAC. Oficial methods of analysis. 15th ed. Arlington, VA, USA: Association of Official Analytical Chemists. 1990. XVIII) SAS. SAS/STAT User’s Guide (Release 6.03). Cary NC, USA: SAS Inst. Inc. 1988. XIX) SAS. SAS User´s Guide: Statistics (version 5 ed.). Cary NC, USA: SAS Inst. Inc. 1985.

Publicaciones electrónicas XX) Jun Y, Ellis M. Effect of group size and feeder type on growth performance and feeding patterns in growing pigs. J Anim Sci 2001;79:803-813. http://jas.fass.org/cgi/reprint/79/4/803.pdf. Accessed Jul 30, 2003. XXI) Villalobos GC, González VE, Ortega SJA. Técnicas para estimar la degradación de proteína y materia orgánica en el rumen y su importancia en rumiantes en pastoreo. Téc Pecu Méx 2000;38(2): 119-134.

http://www.tecnicapecuaria.org/trabajos/20021217 5725.pdf. Consultado 30 Ago, 2003.

g gramo (s) ha hectárea (s) h hora (s) i.m. intramuscular (mente) i.v. intravenosa (mente) J joule (s) kg kilogramo (s) km kilómetro (s) L litro (s) log logaritmo decimal Mcal megacaloría (s) MJ megajoule (s) m metro (s) msnm metros sobre el nivel del mar µg microgramo (s) µl microlitro (s) µm micrómetro (s)(micra(s)) mg miligramo (s) ml mililitro (s) mm milímetro (s) min minuto (s) ng nanogramo (s)Pprobabilidad (estadística) p página PC proteína cruda PCR reacción en cadena de la polimerasa pp páginas ppm partes por millón % por ciento (con número) rpm revoluciones por minuto seg segundo (s) t tonelada (s) TND total de nutrientes digestibles UA unidad animal UI unidades internacionales

XXII) Sanh MV, Wiktorsson H, Ly LV. Effect of feeding level on milk production, body weight change, feed conversion and postpartum oestrus of crossbred lactating cows in tropical conditions. Livest Prod Sci 2002;27(2-3):331-338. http://www.sciencedirect. com/science/journal/03016226. Accessed Sep 12, 2003. 13. Cuadros, Gráficas e Ilustraciones. Es preferible que sean pocos, concisos, contando con los datos necesarios para que sean autosuficientes, que se entiendan por sí mismos sin necesidad de leer el texto. Para las notas al pie se deberán utilizar los símbolos convencionales. 14 Versión final. Es el documento en el cual los autores ya integraron las correcciones y modificaciones indicadas por el Comité Revisor. Los trabajos deberán ser elaborados con Microsoft Word. Las fotografías e imágenes deberán estar en formato jpg (o compatible) con al menos 300 dpi de resolución. Tanto las fotografías, imágenes, gráficas, cuadros o tablas deberán incluirse en el mismo archivo del texto. Los cuadros no deberán contener ninguna línea vertical, y las horizontales solamente las que delimitan los encabezados de columna, y la línea al final del cuadro. 15. Una vez recibida la versión final, ésta se mandará para su traducción al idioma inglés o español, según corresponda. Si los autores lo consideran conveniente podrán enviar su manuscrito final en ambos idiomas. 16. Tesis. Se publicarán como Artículo o Nota de Investigación, siempre y cuando se ajusten a las normas de esta revista. 17. Los trabajos no aceptados para su publicación se regresarán al autor, con un anexo en el que se explicarán los motivos por los que se rechaza o las modificaciones que deberán hacerse para ser reevaluados. caloría (s) centímetro (s) grado centígrado (s) dosis letal 50%

versus

gravedades

Cualquier otra abreviatura se pondrá entre paréntesis inmediatamente después de la(s) palabra(s) completa(s).

18. Abreviaturas de uso frecuente: cal cm °C DL50

19. Los nombres científicos y otras locuciones latinas se deben escribir en cursivas.

Updated: March, 2020 INSTRUCTIONS FOR AUTHORS Revista Mexicana de Ciencias Pecuarias is a scientific journal published in a bilingual format (Spanish and English) which carries three types of papers: Research Articles, Technical Notes, and Reviews. Authors interested in publishing in this journal, should follow the belowmentioned directives which are based on those set down by the International Committee of Medical Journal Editors (ICMJE) Bol Oficina Sanit Panam 1989;107:422-437. 7.

All contributions will be peer reviewed by a scientific editorial committee, composed of experts who ignore the name of the authors. The Editor will notify the author the date of manuscript receipt.

Title page. It should only contain the title of the work, which should be concise but informative; as well as the title translated into English language. In the manuscript is not necessary information as names of authors, departments, institutions and correspondence addresses, etc.; as these data will have to be registered during the capture of the application process on the OJS platform (http://cienciaspecuarias.inifap.gob.mx).

Papers will be submitted in the Web site http://cienciaspecuarias.inifap.gob.mx, according the â&#x20AC;&#x153;Guide for submit articles in the Web site of the Revista Mexicana de Ciencias Pecuariasâ&#x20AC;?. Manuscripts should be prepared, typed in a 12 points font at double space (including the abstract and tables), At the time of submission a signed agreement co-author letter should enclosed as complementary file; coauthors at different institutions can mail this form independently. The corresponding author should be indicated together with his address (a post office box will not be accepted), telephone and Email.

Abstract. On the second page a summary of no more than 250 words should be included. This abstract should start with a clear statement of the objectives and must include basic procedures and methodology. The more significant results and their statistical value and the main conclusions should be elaborated briefly. At the end of the abstract, and on a separate line, a list of up to 10 key words or short phrases that best describe the nature of the research should be stated.

Text. The three categories of articles which are published in Revista Mexicana de Ciencias Pecuarias are the following:

Only original unpublished works will be accepted. Manuscripts based on routine tests, will not be accepted. All experimental data must be subjected to statistical analysis. Papers previously published condensed or in extenso in a Congress or any other type of Meeting will not be accepted (except for Abstracts).

To facilitate peer review all pages should be numbered consecutively, including tables, illustrations and graphics, and the lines of each page should be numbered as well.

Research articles will not exceed 20 double spaced pages, without including Title page and Tables and Figures (8 maximum and be included in the text). Technical notes will have a maximum extension of 15 pages and 6 Tables and Figures. Reviews should not exceed 30 pages and 5 Tables and Figures.

Title page Abstract Text Acknowledgments and conflict of interest Literature cited

a) Research Articles. They should originate in primary works and may show partial or final results of research. The text of the article must include the following parts: Introduction Materials and Methods Results Discussion Conclusions and implications Literature cited In lengthy articles, it may be necessary to add other sections to make the content clearer. Results and Discussion can be shown as a single section if considered appropriate.

Manuscripts of all three type of articles published in Revista Mexicana de Ciencias Pecuarias should contain the following sections, and each one should begin on a separate page.

b) Technical Notes. They should be brief and be

evidence for technical changes, reports of clinical cases of special interest, complete description of a

limited investigation, or research results which should be published as a note in the opinion of the editors. The text wi ll contain the same information presented in the sections of the research article but without section titles.

names(s), the number of the edition, the country, the printing house and the year. e. When a reference is made of a chapter of book written by several authors; the name of the author(s) of the chapter should be quoted, followed by the title of the chapter, the editors and the title of the book, the country, the printing house, the year, and the initial and final pages.

c) Reviews. The purpose of these papers is to

summarize, analyze and discuss an outstanding topic. The text of these articles should include the following sections: Introduction, and as many sections as needed that relate to the description of the topic in question.

f. In the case of a thesis, references should be made of the author’s name, the title of the research, the degree obtained, followed by the name of the City, State, and Country, the University (not the school), and finally the year.

10. Acknowledgements. Whenever appropriate, collaborations that need recognition should be specified: a) Acknowledgement of technical support; b) Financial and material support, specifying its nature; and c) Financial relationships that could be the source of a conflict of interest.

Examples The style of the following examples, which are partly based on the format the National Library of Medicine of the United States employs in its Index Medicus, should be taken as a model.

People which collaborated in the article may be named, adding their function or contribution; for example: “scientific advisor”, “critical review”, “data collection”, etc. 11. Literature cited. All references should be quoted in their original language. They should be numbered consecutively in the order in which they are first mentioned in the text. Text, tables and figure references should be identified by means of Arabic numbers. Avoid, whenever possible, mentioning in the text the name of the authors. Abstain from using abstracts as references. Also, “unpublished observations” and “personal communications” should not be used as references, although they can be inserted in the text (inside brackets).

Journals

Standard journal article (List the first six authors followed by et al.) I)

Basurto GR, Garza FJD. Efecto de la inclusión de grasa o proteína de escape ruminal en el comportamiento de toretes Brahman en engorda. Téc Pecu Méx 1998;36(1):35-48.

Issue with no volume II) Stephano HA, Gay GM, Ramírez TC. Encephalomielitis, reproductive failure and corneal opacity (blue eye) in pigs associated with a paramyxovirus infection. Vet Rec 1988;(122):6-10.

Key rules for references a. The names of the authors should be quoted beginning with the last name spelt with initial capitals, followed by the initials of the first and middle name(s). In the presence of compound last names, add a dash between both, i.e. Elias-Calles E. Do not use any punctuation sign, nor separation between the initials of an author; separate each author with a comma, even after the last but one.

III) Chupin D, Schuh H. Survey of present status of the use of artificial insemination in developing countries. World Anim Rev 1993;(74-75):26-35.

No author given IV) Cancer in South Africa [editorial]. S Afr Med J 1994;84:15.

b. The title of the paper should be written in full, followed by the abbreviated title of the journal without any punctuation sign; then the year of the publication, after that the number of the volume, followed by the number (in brackets) of the journal and finally the number of pages (this in the event of ordinary article).

Journal supplement V) Hall JB, Staigmiller RB, Short RE, Bellows RA, Bartlett SE. Body composition at puberty in beef heifers as influenced by nutrition and breed [abstract]. J Anim Sci 1998;71(Suppl 1):205.

c. Accepted articles, even if still not published, can be included in the list of references, as long as the journal is specified and followed by “in press” (in brackets).

Organization, as author

d. In the case of a single author’s book (or more than one, but all responsible for the book’s contents), the title of the book should be indicated after the

VI) The Cardiac Society of Australia and New Zealand. Clinical exercise stress testing. Safety and

XII

performance guidelines. Med J Aust 1996;(164):282284.

In press VII) Scifres CJ, Kothmann MM. Differential grazing use of herbicide-treated area by cattle. J Range Manage [in press] 2000.

Books and other monographs

Author(s) VIII) Steel RGD, Torrie JH. Principles and procedures of statistics: A biometrical approach. 2nd ed. New York, USA: McGraw-Hill Book Co.; 1980.

Chapter in a book IX)

Roberts SJ. Equine abortion. In: Faulkner LLC editor. Abortion diseases of cattle. 1rst ed. Springfield, Illinois, USA: Thomas Books; 1968:158-179.

Conference paper

XVI) SAGAR. Secretaría de Agricultura, Ganadería y Desarrollo Rural. Curso de actualización técnica para la aprobación de médicos veterinarios zootecnistas responsables de establecimientos destinados al sacrificio de animales. México. 1996. XVII) AOAC. Official methods of analysis. 15th ed. Arlington, VA, USA: Association of Official Analytical Chemists. 1990. XVIII) SAS. SAS/STAT User’s Guide (Release 6.03). Cary NC, USA: SAS Inst. Inc. 1988. XIX) SAS. SAS User´s Guide: Statistics (version 5 ed.). Cary NC, USA: SAS Inst. Inc. 1985.

Electronic publications XX) Jun Y, Ellis M. Effect of group size and feeder type on growth performance and feeding patterns in growing pigs. J Anim Sci 2001;79:803-813. http://jas.fass.org/cgi/reprint/79/4/803.pdf. Accesed Jul 30, 2003. XXI) Villalobos GC, González VE, Ortega SJA. Técnicas para estimar la degradación de proteína y materia orgánica en el rumen y su importancia en rumiantes en pastoreo. Téc Pecu Méx 2000;38(2): 119-134. http://www.tecnicapecuaria.org/trabajos/20021217 5725.pdf. Consultado 30 Jul, 2003.

Loeza LR, Angeles MAA, Cisneros GF. Alimentación de cerdos. En: Zúñiga GJL, Cruz BJA editores. Tercera reunión anual del centro de investigaciones forestales y agropecuarias del estado de Veracruz. Veracruz. 1990:51-56.

XI)

12. Tables, Graphics and Illustrations. It is preferable that they should be few, brief and having the necessary data so they could be understood without reading the text. Explanatory material should be placed in footnotes, using conventional symbols.

Thesis

13. Final version. This is the document in which the authors have already integrated the corrections and modifications indicated by the Review Committee. The works will have to be elaborated with Microsoft Word. Photographs and images must be in jpg (or compatible) format with at least 300 dpi resolution. Photographs, images, graphs, charts or tables must be included in the same text file. The boxes should not contain any vertical lines, and the horizontal ones only those that delimit the column headings, and the line at the end of the box.

XIII) Alvarez MJA. Inmunidad humoral en la anaplasmosis y babesiosis bovinas en becerros mantenidos en una zona endémica [tesis maestría]. México, DF: Universidad Nacional Autónoma de México; 1989. XIV) Cairns RB. Infrared spectroscopic studies of solid oxigen [doctoral thesis]. Berkeley, California, USA: University of California; 1965.

Organization as author XV) NRC. National Research Council. The nutrient requirements of beef cattle. 6th ed. Washington, DC, USA: National Academy Press; 1984.

14. Once accepted, the final version will be translated into Spanish or English, although authors should feel free to send the final version in both languages. No charges will be made for style or translation services.

XIII

15. Thesis will be published as a Research Article or as a Technical Note, according to these guidelines.

Âľm mg ml mm min ng

micro meter (s) milligram (s) milliliter (s) millimeter (s) minute (s) nanogram (s) P probability (statistic) p page CP crude protein PCR polymerase chain reaction pp pages ppm parts per million % percent (with number) rpm revolutions per minute sec second (s) t metric ton (s) TDN total digestible nutrients AU animal unit IU international units

16. Manuscripts not accepted for publication will be returned to the author together with a note explaining the cause for rejection, or suggesting changes which should be made for re-assessment. 17. List of abbreviations: cal cm Â°C DL50 g ha h i.m. i.v. J kg km L log Mcal MJ m Âľl

calorie (s) centimeter (s) degree Celsius lethal dose 50% gram (s) hectare (s) hour (s) intramuscular (..ly) intravenous (..ly) joule (s) kilogram (s) kilometer (s) liter (s) decimal logarithm mega calorie (s) mega joule (s) meter (s) micro liter (s)

versus

gravidity

The full term for which an abbreviation stands should precede its first use in the text. 18. Scientific names and other Latin terms should be written in italics.

XIV

https://doi.org/10.22319/rmcp.v11i1.4814 Article

Milk production in dairy cows grazing alfalfa (Medicago sativa) in the central Mexican highlands

Vicente Lemus Ramírez a Aurelio Guevara Escobar b* Juan Antonio García Rodríguez a Delia Gaspar Sánchez a José Guadalupe García Muñiz c David Pacheco Ríos d

Universidad Nacional Autónoma de México, Facultad de Medicina Veterinaria y Zootecnia, Centro de Enseñanza, Investigación y Extensión en Producción Animal del Altiplano, Tequisquiapan Qro. México. b

Universidad Autónoma de Querétaro, Facultad de Ciencias Naturales. Qro. México.

Universidad Autónoma Chapingo. Departamento de Zootecnia, 56230. Chapingo, Estado de México. México. d

Grasslands Research Centre. Animal Science Group, Palmerston North 4442, New Zealand.

* Corresponding author: guevara@uaq.mx

Abstract: Pasture grazing and feed supplementation strategies can seriously affect milk production in dairy cows. An evaluation was done of the effects of environmental and grazing management factors on pasture productivity variables, and milk and milk solids (fat+protein+lactose) production in an alfalfa grazing system in central Mexico from 2009 to 2011. Data were collected on milk yield and composition, pre-grazing herbage mass (PHM), residual herbage

Rev Mex Cienc Pecu 2020;11(1):1-18

mass (RHM), herbage disappearance rate (HDR), pasture growth rate (PGR), and stocking rate (SR), among other variables. Data on rainfall, temperature, and evapotranspiration at the experimental site was obtained from remote sensing databases. Grazing area increased and supplementation decreased from 2009 to 2011. Annual pasture dry matter production (t DM ha-1) was 17,343 in 2009, 14,649 in 2010, and 13,497 in 2011. Annual pasture utilization rate was 75 % in 2009, 71 % in 2010 and 73 % in 2011, while SR (cows ha-1) was 3.7 in 2009, 3.1 in 2010 and 2.7 in 2011. Milk production (19,290 in 2009, 13,419 in 2010, and 12,563 kg ha-1 in 2011) and milk solids (2,409 in 2009, 1,638 in 2010 and 1,554 kg ha-1 yr-1 in 2011) decreased over time. Based on a multiple regression, grazing interval and nighttime temperature explained PGR; daytime temperature and SR explained PHM; PGR, daytime temperature and feed energy explained milk yield; and HDR and feed energy explained milk solids yield. Feed supplement use is most needed during the 192-d window (October to April) when PGR is below average, and RHM needs to be between 400 and 500 kg DM ha-1 to maximize PGR in the following grazing cycle. Key words: Milk solids production, Grazing management, Alfalfa pastures.

Received 16/03/2018 Accepted 22/11/2018

Introduction

Compared to confinement systems, livestock grazing systems have economic, health and animal welfare advantages(1,2). Mixed temperate grasslands have been proposed for pasture production in the Mexican Highlands(3,4), in such pastures, clover and alfalfa and other legumes have important contributions to grasslands ecophysiology(5,6). Alfalfa is grazed in many countries under irrigated or rainfed conditions since its relatively deep roots provide an advantage over many other forage crops(7,8). In temperate climates, alfalfa is a preferred forage due to its high nutritional quality and flexible harvest for hay or silage, among other aspects. However, alfalfa cultivation has drawbacks, including occurrence of bloat when consumed fresh or grazed by livestock(9), high crude protein content, which increases the energy cost for urinary N excretion(10), the high cost of crop establishment and its need for extensive irrigation(11). Managing alfalfa to promote its persistence in pastures requires rotational grazing to control feed selection by livestock, match the animal production system to forage availability, and balance competition between pasture plant species(9,12). Determined by ambient temperature 2

Rev Mex Cienc Pecu 2020;11(1):1-18

and soil moisture, alfalfa biomass accumulation rate is seasonal(9,13). Obtaining a biomass adequate for grazing requires adjustment of intercrop periods to ensure sufficient stem and leaf recruitment(14). Grazing alfalfa in combination with grass fodder and concentrated feed supplementation positively affects production, offers some protection against tympanism, provides an improved nutrient balance and facilitates adjustments in grazing pressure(8). Although supplementation offers advantages for grazing management, it also increases dependence on resources external to the grazing unit. Moreover, supplementation can lead to substitution effects, reducing forage intake in the pasture(10). Grazing efficiency is reflected in the ability of individual cows to produce dairy solids (fat, protein and lactose) during a season or lactation; it is best expressed as yield per unit area (kg milk solids ha-1). In contrast, continual housing dairy production models quantify performance based on production per herd and individual (L cow-1 per day or lactation), while in industrialized systems milk solids concentration is emphasized. The combination of forage quality and quantity determines animal product quality, but in grazing systems environmental fluctuations also cause changes in production(15). The present study objective was to evaluate what factors influence production of alfalfa for grazing and milk production by studying the relationships between the environment, pasture and animal production in a case study of dairy cows grazing pastures dominated by alfalfa but under different management regimes over a three-year period.

Material and methods Study site The study was carried out at the Center for Teaching, Research and Extension in Animal Production in the Highlands (Centro de Enseñanza, Investigación y Extensión en Producción Animal en el Altiplano - CEIEPAA), of the Faculty of Veterinary Medicine and Zootechny of the National Autonomous University of Mexico (UNAM), in Tequisquiapan municipality, in the state of Querétaro, Mexico. Located in the central highlands of Mexico (20°36’13.88” N; 99°55’02.91” W), the site is 1913 m asl. Local climate is temperate, with average annual rainfall of 512 mm, mostly during the rainy season (average season length = 78 days), and an average daytime temperature of 17.5 °C. Winters are relatively mild with eighteen days of frost from October to February, and warm summer(16). Prevailing winds are northeastsouthwest.

Rev Mex Cienc Pecu 2020;11(1):1-18

General pasture conditions The pasture was established in 2005 with the grasses Dactylis glomerata (orchard grass), Lolium multiflorum (Italian ryegrass), Festuca arudinacea (tall fescue) and Bromus inermis (brome grass), and the legume Medicago sativa (alfalfa). By 2009 alfalfa dominated the pasture. Management consisted of side roll sprinkler irrigation and grazing by dairy cows using the strip method. On average, 1.5 irrigations were applied per grazing cycle, but irrigation depth was not recorded. Cattle were controlled with a mobile electric fence. The pasture was fertilized with Ca(H2PO4)2 at a rate of 50 kg P2O5 ha-1, applied twice annually during spring (May-June) and early autumn (September-October). Data were collected over a three-years period from 2009 to 2011. Grazing area was 21 ha in 2009, 22 ha in 2010 and 27 ha in 2011. Only the studied dairy herd grazed the pasture during this period.

Herbage mass Estimation of pasture herbage mass (HM) (kg DM ha-1) was done with the metal frame technique(17), modified to quantify alfalfa production. All vegetation (HM) inside a 0.25 m2 metal frame was cut at a height of 10 cm to protect the alfalfa tillering. Pre-grazing HM (PHM) was estimated as pre-grazing pasture HM, and residual HM (RHM) as post-grazing HM; both were expressed in kg DM ha-1. Both PHM and RHM were estimated by randomly placing the frame eight times, harvesting the HM each time and averaging the HM quantities to produce a single measurement. The herbage samples were dehydrated in a forced air oven at 95 Â°C for 48 h to determine dry matter (DM) content. Herbage disappearance rate (HDR) was calculated as the difference between PHM and RHM (kg DM ha-1), and considered an estimate of animal consumption on the day of measurement. Grazing interval (GI) between defoliations was recorded in days (d) for each grazing period. Pasture growth rate (PGR) was calculated as PHM divided by GI. In some pastures the PHM biomass was harvested as hay, and in these cases herbage production was also quantified in terms of bales and average bale weight; this fodder was used as a supplement. Vegetation activity phenology was modeled for PGR using the TIMESAT model(18).

Chemical analyses Herbage samples (200 g DM) were taken monthly and sent to the Biochemistry and Animal Nutrition Department of the FMVZ-UNAM for analyses. In vitro DM digestibility was quantified following the method of Tilley and Terry(19). Herbage metabolizable energy (ME) content (MJ kg-1 DM) was estimated from in vitro DM digestibility values using the equations proposed by Geenty and Rattray(20). Total milk solids, fat and protein contents were measured with a Milkoscan 133 (Foss Electric, Denmark). 4

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Livestock and pasture management The milk production model was all year-round calving and milking. The studied pastures were grazed by groups of 45 cows in 2009, 54 cows in 2010 and 61 cows in 2011; these groups included lactating and dry cows. Breeds included Holstein Friesian, Jersey and Holstein x Jersey crosses. Holstein was the predominant breed in all three years: 58 % in 2009, 54 % in 2010 and 51 % in 2011. Average cow body weight during the study period was 510 Âą 66 kg. The cows were in the grazing paddocks always and supplements offered in feed bunks before milking. The supplement was commercial balanced feed and/or rolled corn grain at a rate of 1.8 kg supplement plus 1.6 kg pasture hay (dry basis) per cow per day. Average effective area devoted to grazing was 12.4 ha in 2009, 17.8 ha in 2010 and 22.2 ha in 2011. Hay was harvested during the period of highest annual DM abundance, and the area harvested annually as hay averaged 8.5 ha in 2009, 3.9 ha in 2010 and 4.5 ha in 2011. Stocking rate (SR) was 3.63 cows ha-1 yr-1 in 2009, 3.03 cows ha-1 yr-1 in 2010 and 2.75 cows ha-1 yr-1 in 2011. The animals had free access to water and mineral salts. Cows were drenched with 1 g polysiloxane cow-1 d-1 before entering the pasture during bloating season. As an additional measure, Bloat Tenz (Ecolab, Ltd., New Zealand), a mixture of ethoxylated and propoxylated alcohols used as non-ionic surfactants, was added to the drinking water at a 1:1000 ratio. The grazing control measures and application of anti-bloat medications effectively prevented mortality or clinical cases due to alfalfa-based feeding under the studied intensive grazing conditions.

Environmental data The National Meteorological Service database does not contain data from weather stations near the study site, therefore environmental characterization was done using remote sensing data. Precipitation data were from the Tropical Rainfall Measurement Mission (TRMM) 3B43 v.7, linked to the Global Precipitation Measurement (GPM) mission. Spanning from 1998 to the present, the TRMM is provided on a monthly basis and is derived from measurements taken at 3-h intervals with a 0.25 Â° spatial resolution. Daytime and nighttime temperatures were obtained from the MOD11A2 v.5 surface temperature and emissivity product of the Medium Resolution Imaging Spectroradiometer (MODIS) on board the Terra and Aqua satellites. The MOD11A2 product provides temporary eight-day scales and a 250 m spatial scale. Estimated evapotranspiration data was obtained from the MOD16A2 product at scales of eight days and 1000 m. Both products are cloud free because they are a mosaic of daily measurements averaged only when they have the necessary quality.

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Statistical analyses A factor analysis with repeated observations was used for the present case study, the factors being year (three levels) and month (twelve levels); this was considered a study with pseudoreplication due to the lack of randomization in the factor levels. The relationship between environmental variables and the production system was evaluated by multiple linear regression. Model variable selection was done using the variance inflation factor (VIF) with a value near 10 and elimination of reverse terms (stepwise), without considering interactions between variables. In the models, compliance was confirmed with the assumptions of normality, homogeneous variance and independence. A 5% significance level was used in the Bonferroni correction or the regression models. Analyses were run with the programs SAS University Edition (SAS Institute Inc., Cary, NC, USA) and Minitab v. 17 (Minitab Inc., State College, PA, USA).

Results and discussion Environmental conditions Weather during the study period coincided with the climatic description of the site, with July being the rainiest month and May the hottest (Figure 1). Daytime temperatures rose from February to June and remained stable from July to January (Figure 1A), a trend caused by cloud cover during the rainy season and the influence of polar air masses. The environment was characterized as extreme because it had a difference greater than 15 °C between the warmest (42.7 °C) and coldest (6.1 °C) months, and a broad difference between average daily daytime and nighttime temperatures in each month (Figure 1A). Average annual rainfall was 489 mm and actual evapotranspiration was 454 mm. However, these two variables’ seasonal patterns were not similar due to soil moisture content and agricultural irrigation (not measured) at the study site. The large spatial measurement scale meant these variables provided only the general environmental condition in the study region and not those of the studied alfalfa paddocks.

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Figure 1. Environmental conditions at study site in Tequisquiapan, Querétaro, based on remote sensing data. A) Daytime (⚫) and nighttime temperatures (⚪) according to MOD11A2 product from MODIS; B) Rainfall based on TRMM (⚫) and evapotranspiration (⚪) based on MOD16A2 product from MODIS.

Forage production Average PGR, PHM and HDR values differed between 2009 and the following years, but were similar between 2010 and 2011 (Table 1). From year to year RHM was only similar between 2009 and 2010. Forage production was generally significantly lower in 2011, although the tendency to decrease was first observed in 2010. Values for PGR exhibited seasonal variation with greater accumulation in the summer. Dry matter (DM) accumulation during the study period was 17,343 kg ha-1 yr-1 in 2009, 14,649 kg ha-1 yr-1 in 2010, and 13,497 kg ha-1 yr-1 in 2011. Based on PGR phenology parameters the growing season was 173 d long, beginning near day 115 (April 25) and ending near day 288 (October 15) of the year. The beginning and end of growing seasons were defined based on the threshold of 50 % PGR; in other words, PGR was lower than average for 192 d which were consequently outside the growing season. It is during this period that efforts are needed to improve PGR and livestock supplementation policy and thus reduce the feed deficit. The phenology model estimated maximum PGR to be 82.7 kg DM ha-1 d-1 on day 200 of the year. Pasture utilization rate was 75 % in 2009, 71 % in 2010 and 73 % in 2011.

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Table 1: Least means squares for production and management variables of a grazed alfalfa pasture Herbage mass

Rest

Rate (kg ha-1 d-1)

Period (d)

Pre-grazing

Residual (kg ha-1)

Year 2009 2010 2011 se

1947 1717 1543 39

a b b

502 496 419 12

a a b

1445 1221 1125 28

a b b

58 50 49 1.3

a b b

36 37 35 0.4

ab a b

Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec se

1146 1148 1631 1638 1861 2429 2237 2376 1819 1734 1491 1324 77

a a bc bc cd e de e c c abc ab

266 267 412 458 527 686 630 688 506 472 401 357 25

a a bc bc cd e de e cd bc bc ab

880 882 1219 1180 1334 1743 1607 1689 1313 1262 1089 967 57

a a bc abc cd e de e cd c abc ab

23 24 40 46 60 84 78 86 62 59 37 30 2.5

a a bc c d e e e d d bc ab

51 48 41 36 31 29 29 28 29 29 40 44 0.8

e d c b a a a a a a c d

abcde

Disappearance Rate

Accumulation

Different letter suffixes in the same column and time category (year or month) indicate significant difference (P<0.05, Bonferroni correction).

Both PGR and PHM were highest from June to August. However, PHM values changed gradually through the months, except from August to September and from February to March (Table 1). Grazing management affected PHM behavior since it was focused on matching animal and forage production levels. Values for RHM were notably low from December to February and much higher from June to August. In response to lower PGR, which threatened winter forage production, 29-d rotations were applied in September and October. A large proportion (46%) of PHM was explained by the previous month’s RHM and current month’s PGR (45 %). Other sources of variation included daytime temperature, the current month’s SR and GI in previous month (0.97; P<0.05). Previous month’s RHM explained most (54%) of the variation in PGR, with GI explaining 30 % and nighttime temperature 2.5 % (P<0.05). The low PGR values from November to February had a proportional relationship to previous month’s monthly nighttime temperature as an explanatory variable (y= 9.70 + 2.36x, r2= 0.86, F1,10= 27.4). A deficit in soil moisture can be ruled out as having had an effect in this period since evapotranspiration was similar from December to May (Figure 1B).

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The relationship between previous monthâ&#x20AC;&#x2122;s RHM (y) and PHM (x) was directly proportional (Figure 2), although in different ways depending on the period within the year: NovemberFebruary (y= 1059.22 + 0.00007 x2.5, F1,10= 11.23, r2 = 0.52), March to June (y = 1386.50 + 0.0000059 x3, F1,10= 24.14, r2 = 0.71) and July to October (y= 2711.01 -228300000 / x2, F1,10 = 4.05, r2 = 0.31). This grouping by months was according to similarity in PGR values (Table 1). Average PHM neared 2500 kg ha-1 only in July. From July to October PHM was not this high despite RHM values being comparatively higher than in other months. This herbage production pattern from November to February suggests the potential to obtain higher PHM (Figure 2) if RHM were between 400-600 kg ha-1 (RHM averaged <400 kg ha-1) (Table 1). Stocking rate (SR) decreased from 3.7 cows ha-1 in 2009 to 3.1 cows ha-1 in 2010 and 2.7 cows ha-1 in 2011; only 2009 differed from 2011 (P<0.05).

Figure 2: Relationship between previous monthâ&#x20AC;&#x2122;s RHM and current PHM during three periods within the year in a grazed alfalfa pasture.

Pasture chemical composition was consistent with the availability of younger forage in the autumn and winter (Table 2). Energy concentrations were particularly high in the fall. Crude protein (CP) levels were high from the fall into the winter, with higher concentrations from November to February (22.4 %) than the rest of the year (21.9 %, P<0.05). In vitro DM digestibility changed only gradually but tended to increase in the fall, while forage DM content was higher in spring than in autumn. The only significant correlation was between PHM and CP (-0.36, P<0.05).

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Table 2: Alfalfa pasture chemical composition

Month

Metabolizable energy Mcal kg-1 DM

Crude protein %

In vitro digestibility %

Dry matter %

Neutral detergent fiber %

Ash %

J 11.0 ab* 22.3 ab 66.7 ab 23.3 bc 47.0 a 3.1 b F 11.0 ab 22.3 ab 66.7 ab 23.3 bc 47.0 a 3.1 b M 10.8 b 21.5 b 65.7 b 25.3 ba 47.7 a 3.6 a A 11.0 b 21.8 b 66.3 ab 26.3 a 46.0 a 3.6 a M 11.0 b 21.8 b 66.3 ab 26.3 a 46.0 a 3.6 a J 10.8 b 21.7 b 67.0 ab 22.7 bc 45.7 a 3.1 b J 10.8 b 21.7 b 67.0 ab 22.7 bc 45.7 a 3.1 b A 10.8 b 21.7 b 67.0 ab 22.7 bc 45.7 a 3.1 b S 11.3 a 22.6 a 68.0 a 22.0 c 44.3 a 3.1 b O 11.3 a 22.6 a 68.0 a 22.0 c 44.3 a 3.1 b N 11.3 a 22.6 a 68.0 a 22.0 c 44.3 a 3.1 b D 11.0 ab 22.3 ab 66.7 ab 23.3 bc 47.0 a 3.1 b se 0.1 0.16 0.46 1.0 0.9 abc Different letter suffixes in the same column indicate significant difference (p<0.05, Bonferroni correction).

Pasture energy contribution differed from 60 % in 2009 to 95 % in 2010 to 84 % in 2011(P<0.05) as supplementation progressively decreased. The lower SR can be attributed to the lower pasture production and lower supplementation level. Greater supplementation in 2009 allowed for higher SR. Higher supplementation levels also led to lower RHM (Figure 3), even though effective grazing area increased over time (12.4 ha in 2009, 17.8 ha in 2010 and 22.2 ha in 2011). The supplementation strategy and pasture management were apparently not clearly linked.

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Figure 3: The relationship between metabolizable energy (ME, %) from the alfalfa pasture and RHM in months with more than 10% energy supplementation.

Milk production The potential profitability of grazing systems depends on multiple factors. Prominent among these are high forage production per hectare per year, high forage use levels by the grazing dairy herd, and the cowsâ&#x20AC;&#x2122; genetic potential for milk production exclusively from grazed pasture. Milk production can be modified by adding concentrated feed, hay or silage in the diet to supplement (or complement) nutrient supply. In the present case study, different nutritional regimes were established in the form of supplementation supporting animal productivity in 2009, and the almost total absence of supplements in 2010 and 2011. Moreover, the supplementation strategy was not focused on compensating for the seasonal nutrient deficit, and the productive modelâ&#x20AC;&#x2122;s seasonal pattern consequently exhibited a mismatch between peak pasture forage production from June to August (Table 1) and peak milk production from March to May, especially in 2009 (Figure 4). Monthly milk production (kg milk ha-1 mo-1) was explained linearly by SR in the range of 2.0 to 5.5 cows ha-1 (y= 2.0 + 392.7 x, corrected r2= 0.74, P<0.0001). Changes in SR and increasing the grazing area were the main strategy used to compensate for the feed deficit. Average milk production was higher in 2009 than the other two years (which did not differ), be it by animal unit (17.4 kg cow-1 d-1 in 2009, 14.6 kg in 2010 and 14.9 kg in 2011; P<0.05) or unit area (1,607.5 kg ha1 mo-1 in 2009, 1,118.3 kg in 2010 and 1,047.0 kg in 2011; P<0.05).

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Figure 4: Stocking rate (A): lactating (⚫) and dry (⚪) cows, and milk yield (B): per cow (⚫) and area unit (⚪) for Holstein and Jersey dairy herd grazing an alfalfa pasture.

Lactating cows were incorporated seasonally, using more in June to August and fewer from December to January (Figure 4A). Milk yield per hectare was linked to the number of lactating cows. In all three years of the study period milk yield per cow was lower in the three months of September to November (13.1 kg cow-1 d-1) than during the rest of the year (16.5 kg cow-1 d-1) (P<0.05). One strategy tested was to increase the number of cows in an effort to match forage availability to nutrient demand. However, it was not very effective at resolving the feed deficit of the autumn and winter months and led to a drop in milk production most evident in individual productivity (kg cow milk-1 d-1, Figure 4B). There was a strong correlation between different yields (milk, solids or fat) and the variables of CP concentration (-0.41 in 2009, -0.39 in 2010 and -0.37 in 2011), NDF (0.48 in 2009, 0.49 in 2010 and 0.41 in 2011) and monthly energy intake from pasture (-0.41 in 2009, -0.45 in 2010 and -0.39 in 2011). Analysis of milk yield with progressive elimination multiple regression models and candidate explanatory variables related to the environment, the pasture and feed intake showed daytime temperature, monthly energy intake from the pasture and monthly energy intake from concentrate to be the common explanatory variables in the models for milk, total solids and fat yields; these models’ corrected r2 was greater than 0.9 (P<0.05). When feed composition was the only candidate variable the yields (milk, total solids or fat) were explained mainly by monthly energy intake from the pasture or concentrate, although CP and NDF concentration also had some effect; these models’ corrected r2 was less than 0.84 (P<0.05). In the presence of environmental variables, pasture CP and NDF concentrations had no significant effect.

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Pasture use level and total milk solids production were closely related (Figure 5). In 2009 pasture use level had no effect on solids production due to the good availability of concentrated feed. A lack of concentrates in 2010 and 2011 resulted in heavier pasture use, with a consequently negative effect on milk solids production. Increasing PHM to levels above 2000 kg ha-1 and RHM to at least 600 kg ha-1 kg would result in a use level (70%) approximating a balance between animal and pasture production.

Figure 5: Relationship between pasture utilization rate and milk solids per hectare in 2009 (â&#x161;Ť), 2010 (â&#x161;Ş) and 2011 (â&#x2013; ). During 2010 and 2011 supplementation was low.

In 2010 and 2011 total milk solids increased in response to milk fat, but in 2009 milk fat did not exceed 43 g kg-1 regardless of the higher total solids levels in this year (Figure 6A). The highest total solids and fat values were in the months of November and December 2011, when milk yield was the lowest at any point during the study period (Figure 4B). Milk fat generally decreased as milk production increased (Figure 6B), but without clear differences between years, possibly due to the seasonal effects of other variables. However, total milk solids produced per hectare was proportional to the number of cows per hectare and the highest yield levels were in 2009, mainly due to higher supplementation levels (Figure 6B). This higher supplementation also resulted in higher milk solids yield per hectare although with a lower fat proportion. In 2010 and 2011 total milk solids yield did not exceed 200 kg ha-1 month-1 in most months. These discrepancies in milk solids yield highlight the need to assess the economic costs of supplementation (Figure 5).

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Figure 6: Relationship between milk characteristics in 2009 (â&#x161;Ť), 2010 (â&#x161;Ş) and 2011 (â&#x2013; ). (A) Milk fat and total solids; (B) milk fat and milk yield; and (C) monthly milk solids yield and lactating cows per hectare.

During the study period total milk solids (fat, protein and lactose) yield (2,409 kg ha-1 yr-1 in 2009, 1,638 kg in 2010 and 1,554 kg in 2011) was near the 1,580 kg ha-1 reported for the highly productive grasslands of the Waikato area of New Zealand(21), although the current definition of total solids in New Zealand does not include lactose(22). Milk fat yields (727 kg ha-1 yr-1 in 2009, 523 kg in 2010 and 496 kg in 2011) were also near the 600 kg ha-1 reported in the same study. Annual milk yield (19,290 kg ha-1 in 2009, 13,419 kg ha-1 in 2010 and 12,563 kg ha-1 in 2011) was within levels reported for alfalfa-based grazing production with strategic supplementation (10,000 L ha-1 year-1), lactations ranging from 7,000 at 7,500 L, and a two-cow ha-1 stocking rate(23). Improving the production system used in the present study would depend on matching forage production and feed demand, and strategic use of feed supplements to compensate for pasture PHM deficit. Alfalfa growth in the present case was seasonal whereas milk production was constant year-round, lacking a planned period without production during which all cows were simultaneously dry, as is commonly done in seasonal grazing systems(24). According to the phenology model, PGR was higher than average for 173 d, meaning there were 192 d during which forage production could be improved by addressing the limiting factors of temperature, water and nutrients. Climate change is predicted to bring milder winters and warmer nights to the study region(25,26), suggesting that alfalfa may perform better based on the temperature results of the regression model. Levels for PGR were lowest from November to February, meaning strategic application of nitrogen fertilizer(27) and adequate irrigation management to compensate for evaporation could improve yield during this season. Additional soil moisture and mineralizable nitrogen data are needed to better support these decisions. However, during 14

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this period alfalfa CP concentration was high compared to nutrient requirements, highlighting the need to balance the diet through supplements or promote grass growth in the pasture. Fluctuations in milk yield suggest there is an opportunity for improvement since yield per hectare did not precisely follow individual yield, particularly in the November to February period. One strategy would be to focus on supplementation and better pasture management during this period.

Conclusions and implications The present work showed the importance of representing the performance of pasture production in terms of harvested area per unit of time. Minimum cut height to assess grazing management was 10 cm in order to maintain a safety margin against overgrazing and decrease defoliation of alfalfa regrowth. When pasture residual herbage mass was lower so were the herbage mass available for grazing and accumulation rate in the following month. Pasture metabolizable energy also decreased when post-grazing residual mass was lower, which required feed supplements. Based on the present results a minimum threshold for management of residual mass would be from 400 to 500 kg DM ha-1 depending on the period of the year, but especially from November to February. Total milk solids production per hectare declined at higher pasture utilization rate and lower feed supplementation levels; clearly, supplementation had a compensatory effect. Nighttime temperature had a positive effect on herbage accumulation rate, while daytime temperature had a positive effect on milk or total solids yield. Mismatches in pasture production and milk yield peaks were notable, indicating a need to better synchronize the annual phases in this grazing system. The mismatch between the year-round milk production model, the seasonal yield of alfalfa pasture and the inefficiencies of grazing management could be addressed particularly during the 192-d period of phenology when pasture accumulation rate was 50 % below maximum. Feed supplementation is clearly needed in cattle grazing alfalfa and must be applied strategically during certain periods of the year and considering the targeted total milk solids yield. Finally, deeper study is needed of microclimate interactions in a grazing milk production model based on alfalfa, especially given rainfall deficits during drought and the alternative use of irrigation in other production options.

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https://doi.org/10.22319/rmcp.v11i1.4740 Article

Effect of a Pennisetum purpureum and Tithonia diversifolia silage mixture on in vitro ruminal fermentation and methane emission in a RUSITEC system

Vilma A. Holguín a,b* Mario Cuchillo-Hilario c,d Johanna Mazabel c Stiven Quintero c Jairo Mora-Delgado b

Universidad Nacional de Colombia - Palmira. A.A 237, Palmira, Colombia.

Grupo de Investigación Sistemas Agroforestales Pecuarios, Universidad del Tolima, A.A. 546, Ibagué, Colombia. c

International Center for Tropical Agriculture (CIAT), A.A. 6713, Cali, Colombia.

Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán (INCMNSZ), Departamento de Nutrición Animal, Ciudad de México, México.

*Corresponding author: vholguin@ut.edu.co

Abstract: Livestock diets in the tropics are traditionally based on grass species, with significant consequent nutritional limitations. Balancing the diet requires supplementation with forage species offering high quality protein. An artificial rumen simulation technique system (RUSITEC) was used to digest a mixture of the grass Pennisetum purpureum (PP) and the sunflower Tithonia diversifolia (TD). Evaluations were done of the effects of added lactic acid bacteria on rumen kinetics and methane (CH4) release. Four treatments were analyzed: T1) a control with 100% PP silage with no

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inoculum; T2) a PP/TD (67:33%) mixture with no inoculum; T3) a PP/TD (67:33%) mixture inoculated with the lactic acid bacteria (LAB) Lactobacillus paracasei T735; and T4) a PP/TD (67:33%) mixture inoculated with the commercial Sil-AllÂŽ4x4 LAB. Data were analyzed with a completely random design. Ammonium concentration did not differ (P>0.05) between the treatments (T2, T3 and T4) and the control (T1). The T4 treatment lowered volatile fat acids by 57 % compared to the control (P<0.001). Methane release was also lower (P<0.05) in T4 (1.36 mmol/g) than in the control (2.43 mmol/g), although levels were also relatively low in T3. The ciliate protozoa population did not differ among the treatments or with the control (P>0.05). The decrease in methane emission per gram dry matter in the PP/TD silages was probably due to lower fiber degradation levels. This suggests that methane emissions were lower per unit of edible animal protein produced even though the total amount of methane released did not differ. Key words: Defaunation, Fiber, Protozoa, Digestion, Silage.

Received: 05/01/2018 Accepted: 23/11/2018

Introduction Vascular plant genetic biodiversity per unit of area is highest in the worldâ&#x20AC;&#x2122;s tropics. Despite this wealth, animal feeding systems in tropical regions are mainly based on a very few plant species, with a limited range of forage trees and bushes(1). Worldwide demand for meat and dairy products is projected to greatly increase as human populations continue to grow. Raw materials for animal feed are a primary drive behind higher livestock production costs, highlighting the need to exploit regional biodiversity in the search for alternative feed sources and rationally employ natural local resources(2). Livestock producers in the tropics have traditionally used diets based on associations of native and/or introduced grasses. The high cell wall content of grasses creates significant nutritional limitations that translate into low intake rates and consequent shortages in digestible nutrients intake. Both phenomena are generally due to poor microbial fermentation of grasses which results in nutrient flow and absorption lower than that required by ruminants(3). Nutritional deficiencies require the use of supplementary feeds, introduction of forage legumes in pastures, or

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supplementation with shrub legume forage or other non-legume high protein quality woody species(4). Mixing a selection of forage species into the ruminant diet has been proposed as an efficient alternative for improving protein and energy supply in livestock production in the tropics(5). This can be accomplished by supplying fodder mixtures through browsing, cutting and hauling or forage conservation by silage processes(6). An appropriate energy:protein mixture for livestock is 70:30, and forage mixtures commonly include grasses and legumes in this proportion(7). Protein sources can be non-legumes from among the immense diversity of forage trees in the tropics(8). Wild sunflower Tithonia diversifolia (TD) is widely used in animal feed due to its high protein content, high digestibility and ease of management. In one study DM content in TD ranged from 13.5 to 25.0 %, depending on age and cut frequency, and crude protein values varied from 11.0 to 29.8 %, with significant differences in leaves at 30 and 60 d(9). The leaves of TD are reported to have high crude protein content (20.6 %)(10). Silage is a nutrient conservation strategy based on anaerobic fermentation by Lactobacillus genus bacteria(11). Limited data is available on TDâ&#x20AC;&#x2122;s medium acidification process and ease of silage. Research is needed on the acidifying potential of native Lactobacillus strains(6), and silage stability and nutrient loss reduction once silage is exposed to aerobic conditions(12). There are reports indicating that optimization of the anaerobic fermentation process can be induced by mixtures (especially those including TD) that improve feed characteristics(6,10). Ruminal fermentation gas production simulation techniques (e.g. continuous cultures such as the RUSITEC artificial rumen simulation system) are commonly used in in vitro experimental procedures for studying ruminal fermentation processes. They allow control of the conditions under which fermentation occurs and of the factors affecting it(13). Simulation methods are based on maintaining small quantities of ruminal fluid under controlled environmental conditions (anaerobic, temperature and kinetic) so the microbiota can act at discretion on the raw material being tested(14,15). A properly prepared simulation system can maintain a normal bacterial population in ruminal fluid under strictly controlled conditions for long time periods(16). Developed by Czerkawsky and Breckeridge(17) and modified by Machmuller et al(18), this system is specifically for quantifying fermentation by simulating the physiological activities of ruminal digestion for relatively long time periods. The RUSITEC system allows analysis of fermentation in vitro for periods sufficiently long to provide evidence of possible microbe adaptation within the rumen. The present study objective was to evaluate the association of Pennisetum purpureum (PP) and Tithonia diversifolia (TD) as a forage mixture, as well as the effect of addition of lactic acid bacteria (LAB) on ruminal kinetics and methane production variables in the RUSITEC rumen simulation system.

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Material and methods The analyses were done at the Forage Quality Laboratory of the International Center for Tropical Agriculture (Centro Internacional de Agricultura Tropical - CIAT) in the Municipality of Palmira, Columbia (3°30’09” N; 76°21’18” W).

Forages

Biomass of TD was quantified in the pre-flowering stage (60 d) for a cut made 40 cm above ground level, including leaves and stems, in February 2013. The TD was grown at the experimental farm of the National University of Colombia (Universidad Nacional de Colombia), Palmira (1,000 m asl, 24 °C average annual temperature, 1,020 mm average annual rainfall precipitation and 72 % average annual relative humidity). Collection of PP was done at 75 d of age (10 cm above ground level). Both forages were reduced to a 2-3 cm particle size with a three-blade mill (7.5 hp, 1400 rpm, and 4.5 amps; Gaitan).

Silage preparation

When ensiled, humidity in the TD was 30 % of DM and that in the PP forages was 35 % of DM. Four treatments were used: T1) Control, 100% PP silage no inoculum; T2) mixture of PP (67%) and TD (33%) silage no inoculum; T3) mixture of PP (67%) and TD (33%) silage, LAB inoculum (Lactobacillus paracasei - T735 previously isolated from TD); and T4) mixture of PP (67%) and TD (33%) silage, commercial Sil-All®4x4 inoculum [LAB mixture: Streptococcus faecium (National Collection of Microorganism Cultures – CNCM; I-3236), L. plantarum (CNCM I-3235), Pediococcus acidilactici (CNCM I-3237) and L. salivarius (CNCM I-3238)] (Table 1). The mini silos were done in triplicate. Both inocula were applied at a 104 CFU/g concentration. The forage mixtures (1,000 g each) were vacuum-packed following the Rostock model for silages(19), and stored for ninety days in darkness at room temperature (25 °C). On d 90, the min silos were opened, and the silages lyophilized and ground (Thomas Wiley Mill 4, with a 1.0 mm sieve).

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Table 1: Treatments analyzed in mini silo digestion process based on mixtures of Pennisetum purpureum (PP) and Tithonia diversifolia (TD) Mixture (%) Inoculum T1 PP (100) No inoculum T2 TD /PP (33/67) No inoculum T3 TD /PP (33/67) T735 T4 TD /PP (33/67) Sill-All®4x4 T1= Control, 100% PP silage no inoculum; T2= mixture of PP (67%) and TD (33%) silage no inoculum; T3= TD/PP (33/67%) mixture silage, LAB (Lactobacillus paracasei - T735); and T4= TD/PP (33/67%) silage, commercial Sil-All®4x4.

In vitro ruminal fermentation in RUSITEC system

The RUSITEC system consists of eight fermenter tubes that allow simultaneous evaluation of a maximum of eight treatments. In the present study four treatments, two repetitions per treatment, were analyzed; the run effect was used as a repetition. Experimental period was ten days, of which the first four days corresponded to the adaptation period of the microorganisms to the experimental diets and the following six days were for data collection and sampling. Ruminal fluid (890 ml) and buffer solution or artificial saliva (110 ml) were added to each of the eight fermenter tubes(20). Before being added, the ruminal liquid was filtered through four layers of gauze. Artificial saliva flow was controlled with a pump to ensure a continuous supply of 500 ml per day per fermenter, equivalent to a 0.5 per day dilution rate. At the beginning of each experimental period, 60 g ruminal content and 16 g DM separately packed experimental silage were added to each fermentation tube for incubation. The diets were packed in nylon bags measuring 13.5 x 6.5 cm with 100 µm pores (NItex 03-100 / 32, SEFAR, Heiden, Switzerland). Subsequently, every 24 h one of the bags was replaced by a new one, starting with the ruminal content bag. In this way each bag was incubated for 48 h. After a bag change, air in the fermenter was displaced with N2 to restore anaerobic conditions. The removed bags were washed with cold water until the wastewater ran clear, and stored at -20 °C until analysis. The fermenters were fed daily. Four hours before feeding, ruminal fluid samples were taken to quantify redox potential, pH, ammonium concentration and microorganism count. Gas collected from the fermenters was stored in 10 l bags (Supel™ Inert Foil Gas Sampling Bags, Screw Cap Valve) and quantified by water displacement.

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Chemical analysis

Chemical composition analyses were run on the samples before digestion in the RUSITEC and on the incubation residues after digestion. Bromatological analyses were done following established methods: nutritional quality, NFTA Method 2.1.4 in oven at 105 °C (930.15)(21); acid detergent fiber (ADF), NFTA Method 4.1 (973.18)(22); neutral detergent fiber (NDF)(23,24,25); and crude protein (CP), Kjeldahl (984.13)(22). Estimated dry matter digestibility (EDMD) was calculated with the equation: EDMD = 88.9 - (0.779 x ADF). Ammonium concentrations were measured following the Ammonia (NH3) Electrode Instruction Manual. Three points (1, 10 and 100 mmolar) were calibrated. For each calibration 20 ml molar solution was stirred and 1 ml sodium hydroxide added, and this repeated for the other two points (10 and 100 mmolar). Once calibrated, a 1 ml inoculum sample was taken, 18 ml distilled water and 1 ml sodium hydroxide added, and the reading taken.

pH and redox potential

Redox potential and pH were measured with a pH/ion meter (SG8, Mettler-Toledo series: B 337764747). After device calibration, a 6 ml sample was taken from each fermenter and the measurement taken with the indicated electrode.

Protozoan count

Protozoa counts were done using 2,000 µL Hayem solution (2.5 g/L HgCl2; 25 g/L Na2SO4; 5.0 g/L NaCl) and 500 µl ruminal fluid (days 0 and 1), or 100 µl Hayem solution and 1,000 µl ruminal fluid (d 2 to 8). The mixtures were placed in plastic tubes, these placed in a 0.1 mm deep Neubauer chamber (Hausser Scientific), and the protozoans present in the entire chamber area counted(26).

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Methane

Methane (CH4) was measured with a chromatographer (Shimadzu GC-2014). The column (Shimadzu) had a series of columns packed for methane: 4m H-D 80/100, 0.7m S-Q and 1.5 P-N. Column temperature was 80 Â°C and detector temperature was FID 25 Â°C. This device does not employ a traditional injection port and injection is directly connected to a cable, which is at room temperature. The carrier gas was nitrogen at a column flow rate of 30.83 ml/min.

Statistical analysis

Data were analyzed using a completely randomized design (P<0.05). The variables were evaluated with general and mixed linear models for repeated measurements (Infostat, ver. 2010 software). The model included the fixed effects of treatment, measurement time and their interaction. Incubation time was considered a random effect. Different covariance structures were analyzed for each variable and the best model estimated based on Akaike (AIC) and Bayesian (BIC) information criteria.

Results and discussion Analysis of silage chemical composition after the RUSITEC digestion process found no differences (P= 0.5182) in CP levels between silages (Table 2). Addition of TD may not have been sufficient to modify this parameter, and higher proportions of TD in the silages could have generated a significant difference between treatments. The highest CP content (7.8 %) was in T3 (PP/TD; T735), which is similar to the 6 % (30 d) and 8 % (90 d) CP reported for silage(27).

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Table 2: Analysis of silage chemical composition after the RUSITEC digestion (values expressed as a percentage of dry matter) T1 Variable DM CP NDF ADF Ashes OM DMD

% % % % % % %

Mean 92.46 5.55 74.05 51.02 12.51 87.49 49.15

T2 SD 0.01b 0.64a 0.11a 0.00a 0.01b 0.01a 0.00 a

Mean 92.52 7.20 69.1 52.15 11.96 88.04 48.28

T3 SD 0.04bc 1.70a 0.63b 1.31a 0.29b 0.29a 1.02 a

Mean 91.77 7.80 65.09 49.92 10.91 89.09 50,01

T4 SD 0.08a 1.13a 0.07c 0.18a 0.07a 0.07ab 0.14 a

Mean 92.74 7.50 68.56 51.21 11.71 88.29 49.01

SD 0.1c 2.12a 0.3b 0.4a 0.4ab 0.4b 0.34 a

DM= dry matter; CP= crude protein; NDF= neutral detergent fiber; ADF= acid detergent fiber; OM= organic matter; DMD=dry matter digestibility. ab Values with different superscript are different (P<0.05).

Neutral detergent fiber (NDF) levels were highest in the control (T1; P<0.0001) and lowest in T3. Unlike CP, the fiber content in PP versus TD in the mixture significantly modified NDF, substantially lowering its levels. In the mini silo systems NDF responded inversely to TD inclusion, decreasing as TD inclusion increased. Content of NDF in forages generally ranges from 30 to 80% and the higher the fiber proportion the lower the productivity of animals that consume it(28). This dynamic is associated with DM intake since the higher the fiber content the longer the rumen retention time and the lower the voluntary fodder intake. The NDF content in treatments T2, T3 and T4 was between 15 and 19 points higher than the 54.5% reported for silages containing TD, and their ADF content was notably higher than the 32% at 90 days reported elsewhere(27). Treatment had no apparent effect on ADF, although it tended to decrease in T3. This lack of a difference in ADF may be due to the maturity of the PP, which was older (75 days) than the TD forage used in a previous report(27). Ash content was lower in T3 than in T1 and T2 (P<0.0141), and organic matter content was higher in T3 than in T1 and T2. Silage digestibility did not differ between treatments (P= 0.1311). This is noteworthy since higher NDF content normally results in lower DM digestibility, especially when diets include woody species like TD (e.g. T2, T3 and T4, included TD leaves and stems). In addition, high cell wall content in fodder is reported to cause low digestibility and can restrict use of a fodder as animal feed(8,16, 28).

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Ruminal liquid

After 8 d fermentation in the RUSITEC, pH was slightly higher than normal rumen acidity range (7.3 to 7.4), but without differences (P>0.05) between treatments (Figure 1). High pH levels are likely a response to a highly fibrous diet since long fibers stimulate rumination and secretion can increase saliva production(29). Saliva functions as a lubricant for the consumed feed, and can raise pH to an average of 8.2, as well as increase sodium, potassium, bicarbonate and phosphate levels(29,30). These characteristics are simulated in the artificial saliva used in the RUSITEC, which may initially raise ruminal liquid pH, but its buffer capacity later stabilizes it. In addition to this effect of the artificial saliva, the trend from acidic towards basic pH in the present results may have resulted from a downward trend in organic acids production over time.

Figure 1. Rumen acidity in silages made from a mixture of Pennisetum purpureum (PP) and Tithonia diversifolia (TD) in a RUSITEC system

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Balance in the natural rumen environment is maintained thanks to a buffer solution derived from the alkaline salivary secretion. This modulates the acidity of carbohydrate fermentation in the rumen, within a range of 5.8 to 7, generally near neutral(29). Of all the factors of the rumen medium, pH is the most susceptible to variation, and ration is the factor that can most affect it. Maintaining ruminal pH within an adequate range is the result of production and neutralization or elimination of protons in the rumen medium. Fermentation of non-structural carbohydrates (NSC) is more energy efficient but it is highly acidic; therefore the proportion of NSC in a diet needs to be limited or counteracted with structural carbohydrates (SC) which provide a buffering capacity to the rumen environment(31). Redox potential did not differ (P>0.05) between treatments (Figure 2), which suggests that simulation in the RUSITEC closely approximated a rumenâ&#x20AC;&#x2122;s anaerobic environment. At times oxygen can be present in the rumen, possibly because it has entered with feed or water(3,15). Low oxygen concentrations, as indicated by negative oxidation potential (Eh) values between -250 and -450 millivolts (mV), stimulate the growth of anaerobic microorganisms(32). Figure 2. Redox potential of silages containing Pennisetum purpureum (PP) and Tithonia diversifolia (TD) and digested in a RUSITEC

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Dry matter degradation

Mean DM degradation over eight days of digestion in the RUSITEC was significantly higher (P<0.0001) in T3 (41.33 ± 5.63) than in T1 (37.88 ± 5.76) and T2 (34.61 ± 4.79) (Figure 3), but did not differ significantly from T4 (39.71 ± 5.90). Longitudinal analysis also identified differences (P<0.0001) between degradation at 8 days and at the beginning of the period. The diets containing TD exhibited higher DM degradation, which can be explained by their lower non-legume protein dicotyledonous fiber content and higher forage digestibility and degradability, both inversely related to NDF content(28).

Figure 3. Dry matter degradation in silages containing a mixture of Pennisetum purpureum (PP) and Tithonia diversifolia (TD) and digested with a RUSITEC

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Volatile fatty acids (VFA)

Volatile fatty acids (VFA) levels were not affected by treatment in that no differences were present, although VFA levels were slightly lower in T3 (Table 3). In forage-based diets VFA can provide between 50 and 85 % of energy requirements. Moreover, the proportions, relative to total rumen gasses, between VFA and greenhouse gases (GHG) is 65 % for CO2, 27 % for CH4 and 0.2 % for free H2(33). Table 3: Response variables for in vitro rumen fermentation of a Pennisetum purpureum (PP) and Tithonia diversifolia (TD) mixture Control (100% PP)

Mixture (33% TD + 67% PP) No Inoculum

T-735 LAB

Sill-All LAB

VFA, mmol/l

50.10±14.2a

40.5A±8.57a

39.87±10.2a

41.18±11.2a

0.3247

Acetate, mmol/l

27.86±8.5a

23.45±5.1a

24.34±6.2a

25.14±6.5a

0.4875

Propionate, mmol/l

13.34±2.9a

10.83±2.2a

10.86±2.5a

10.99±2.6a

0.3525

Butyrate, mmol/l

8.35±2.6a

5.87±1.2b

4.22±1.1c

4.26±1.7c

<0.0001

Acetate/Propionate

2.06±0.2c

2.16±0.1bc

2.23±01ab

2.29±0.1a

0.0009

Methane, mmol/g

2.43±1.1a

1.53±0.9ab

1.42±1.6ab

1.36±1.4b

<0.0001

Ammonium, mmol/l

0.13±0.07a

0.06±0.00bc

0.05±0.00bc

0.06±0.01bc

<0.0001

Protozoa (1*105)

0.05±0.00a

0.1±0.00a

0.05±0.00a

0.15±0.00a

0.7681

P value Variables

T1= Control, 100% PP silage no inoculum; T2= mixture of PP (67%) and TD (33%) silage no inoculum; T3= TD/PP (33/67%) silage, LAB (Lactobacillus paracasei - T735); and T4= TD/PP (33/67%) silage, commercial SilAll®4x4. VFA = volatile fatty acids. abc Different letter superscripts in the same row indicate significant difference (P< 0.05).

Fermentation product composition differed between treatments. Though not significant (P= 0.4875), acetate drainage was higher in T1 compared to the treatments containing TD. A similar trend was observed for propionate drainage, although again with no differences (P= 0.3525). Butyrate production did differ between treatments (P<0.0001), with the highest production in the control (T1), and progressively lower levels with addition of TD (T2) and the LAB inocula (T3 and T4).

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In ruminants, formation of propionate is more energy efficient than that of butyrate and acetate because production of the latter two leads to release of carbon atoms that cannot be burned in the form of CH4 (or H atoms that do not convert to VFA)(34). This means that grass-only diets lead to high segregation of butyrate as C atoms are released as CH4. Total VFA was not affected by the treatments in the present study but the VFA profile was notably modified, which coincides with a previous report on diet additives in a RUSITEC(35). This is confirmed by the significant differences in the acetate/propionate ratio, which was higher in T4 and T3 (P=0.0009) than in T1. Normal VFA molar proportions in the rumen are acetic acid (65 %); propionic acid (20 %); butyric acid (13%) and others (2 %)(36). Though slightly altered, these general proportions were observed in the present results with T4 having the proportions nearest these estimates: 60.7 % (acetate); 26.7 % (propionate); 9.7 % (butyrate) and 2.9 % (others). In diets based entirely on forages the acetate:propionate ratio approaches 3:1, while as diet concentrate percentage increases the ratio narrows to 2:1 or less(16).

Ammoniacal nitrogen (NH3-N)

Production of NH3-N (as a measure of dietary N metabolism) was lower in the treatments including TD, suggesting lower dietary protein degradation in these treatments. The higher ammonium level in T1 was probably related to increased proteolysis. Daily NH3-N production changed over time in all treatments (P<0.0001); generally, values increased on the first day and then gradually decreased, which agrees with previous reports(16). On day 8, NH3-N was highest in T1 compared to the treatments containing TD. Ammonium content did not differ among these treatments although it was slightly higher in T3, even though DM digestibility did not differ between them. This occurred despite the greater N input in T3. Previous studies have shown that in high protein forages incorporation of dietary N in microbial N increases as NH3-N decreases(37,38). This discrepancy indicates that protein degradation may occur at a slower rate in diets containing TD. Ruminal ammonia concentration in the different treatments was much lower than the 3.26 mmol/l reported elsewhere(39), but near the 1.76 mmol/l observed in an evaluation of a mixed substrate (1/3 Cratylia argentea, 2/3 Brachiaria dictyoneura) in a RUSITEC system(3). However, these levels are still lower than the 3.6 mmol/l suggested for maximum microbial protein synthesis in the rumen(40).

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Methane emission

At 8-days incubation, net CH4 production per g DM was higher in T1 than in T4, which had the lowest production (Table 3). The present CH4 production was similar to the 1.47 and 1.61 mmol/g DM reported for a mixture of B. dictyoneura hay and additives(39). This also generally agrees with a study using the gas production methodology in which grass-only silages emitted high levels of CH4 which decreased as TD inclusion levels increased, and where 80 to 88 % of the total gas produced at 60 h incubation was detected at the inflection point(41). In another study of PP/TD forage mixtures CH4 production decreased as TD inclusion increased from 15 % (33.3 ml) to 30 % (30.1 ml) and 100 % (28.06 ml)(42). Decreases in CH4 emission per gram degraded MS are probably due to lower fiber degradation, suggesting that less CH4 would be emitted per unit of edible animal protein with the TD treatments, even though total CH4 emission may not decline(39). The lower CH4 production in the PP/TD silage in the present results may be due in part to the action of condensed tannins (CT), which are known to reduce CH4 emissions in woody forage species(43). Tithonia diversifolia (TD) forage has relatively moderate CT levels(9), which can vary from 1.0 % in the dry season to 1.4 % in the rainy season(44); these are not negligible levels. The higher CH4 production in T1 was probably due to the greater proportion of cell wall in this allgrass forage. Cell walls contain more NDF, which has low ruminal digestibility, meaning more NDF passes through the rumen into the large intestine where it can be fermented and thus produce CH4 through the action of methanogenic microbes(35,43). Protozoa population is a good measure of rumen microbial biomass since they have relatively high weight among the microbiota. Though their net count may be smaller than the bacteria, the protozoa have a greater individual volume, resulting in a protozoan cell mass similar to the bacterial mass(16). The protozoa also colonize and degrade plant tissues in the rumen and produce enzymes capable of degrading plant and hemicellulose polysaccharides(29). In the present results the protozoa population changed over time in all treatments with values gradually decreasing during the first three days and then stabilizing during the last four days at average values that did not differ between treatments (P>0.05). Among the TD treatments (T2, T3 and T4), the protozoa count was relatively lowest in T3, which also had the highest CP proportion. This coincides with a study in which degradation was highest in substrates supplemented with a high-quality legume forage(39). However, these same forages can have high secondary metabolite (e.g. tannins and saponins) contents which can negatively affect ciliate (protozoa) populations; this would definitely improve nitrogen use but not necessarily reduce methanogenesis.

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Conclusions and implications The isolated ruminal fluid in the RUSITEC maintained variable levels comparable to the rumen in vivo. Neither the hydrogenation nor the redox potentials exhibited differences between the Control (100% Pennisetum purpureum - PP) treatment and the forage mixtures (PP/Tithonia diversifolia TD), with and without inoculum in the silage. Values for pH were slightly higher than normal rumen acidity (7.3 and 7.4), but without variation between treatments. Redox potential did not differ between treatments. Ammoniacal nitrogen was lower in the TD treatments, which could have practical applications: reductions in the CH4 emitted per unit of animal protein produced could provide benefits even if total CH4 emissions did not decrease.

Acknowledgements Thanks are due the Centro Internacional de Agricultura Tropical (CIAT) and the Universidad del Tolima for financial and technical support, and Patricia Ávila and Orlando Trujillo (Laboratorio de Calidad de Forraje del CIAT) for technical support.

Literature cited: 1. Rosales M. Mezclas de forrajes: uso de la diversidad forrajera tropical en sistemas agroforestales. En: Rosales M, Murgueitio E, Osorio H. Agroforestería para la producción animal en Latinoamérica. Roma, FAO. 1999:201-231. 2. Holguín VA, Ortiz.Grisalez S, Velasco Navia A, Mora.Delgado J. Multi-criteria evaluation of 44 introductions of Tithonia diversifolia (Hemsl.) A. Gray in Candelaria, Valle del Cauca. Rev Med Vet Zoot 2015; 62:57-72. 3. Hess HD, Monsalve LM, Lascano CE, Carulla JE, Díaz TE, Kreuzer M. Supplementation of a tropical grass diet with forage legumes and Sapindus saponaria fruits: effects on in vitro ruminal nitrogen turnover and methanogenesis. Aust J Agric Res 2003;547:703-713. 4. Rao I, Peters M, Castro A, Schultze-Kraft R, White D, Fisher M. et al. Livestock Plus: sustainable intensification of tropical forage.based systems for improving livelihood and environmental benefits. Trop Grassl . Forr Trop 2015;3(2):59-82.

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5. Ribeiro RS, Terry SA, Sacramento JP, Silveira SRE, Bento CBP, da Silva EF, et al. Tithonia diversifolia as a supplementary feed for dairy cows. PLoS One 2016;11:e0165751. 6. Holguín VA, Cuchillo HM, Mazabel J, Martens SD. In-vitro assessment for ensilabillity of Tithonia diversifolia alone or with Pennisetum purpureum using epiphytic lactic acid bacteria strains as inocula. Acta Sci Anim Sci 2018;40:e37940. 7. Ojeda F. Técnicas de cosecha y ensilaje. En: Mannetje L´t. editor. Uso del ensilaje en el trópico privilegiando opciones para pequeños campesinos. Roma: FAO. 2001:137-146 8. Pinto-Ruiz R, Hernández D, Guevara F, Gómez H, Medina F, Hernández A, et al. Preferencia de ovinos por el ensilaje de Pennisetum purpureum mezclado con arbóreas forrajeras tropicales. Livest Res Rural Dev 2010;22:106. 9. Lezcano Y, Soca M, Sánchez LM, Ojeda FF, Olivera Y, Fontes D, Santana HH. Caracterización cualitativa del contenido de metabolitos secundarios en la fracción comestible de Tithonia diversifolia Hemsl. A. Gray. Spanish. Past Forr 2012;353:283-292. 10. Fasuyi AO, Ibitayo FJ. Nitrogen balance and morphometric traits of weanling pigs fed graded levels of wild sunflower Tithonia diversifolia leaf meal. Afr J Food Agric Nutr Dev 2011;113:1-17. 11. Heinritz SN, Martens SD, Avila P, Hoedtke S. The effect of inoculant and sucrose addition on the silage quality of tropical forage legumes with varying ensilability. Anim Feed Sci Technol 2012;174(3.4):201-210. 12. Kleinschmit DH, Kung Jr L. A meta-analysis of the effects of Lactobacillus buchneri on the fermentation and aerobic stability of corn and grass and small-grain silages. J Dairy Sci 2006;89(10):4005-4013. 13. Rymer C, Huntington JA, Wlliams BA, Givens Dl. In vitro accumulative gas production techniques: History, methodological considerations and challenges. Anim Feed Sci Technol 2005;123.124:9-30. 14. Menke KH, Steingass H. Estimation of the energetic feed value obtained from chemical analysis and in vitro gas production using rumen fluid. Anim Res Dev 1988;28:7-55. 15. Abel HJ, Irmgard I, da Costa Gómez C, Steinberg W. Effect of increasing dietary concentrate levels on microbial biotin metabolism in the artificial rumen simulation system RUSITEC. Arch Tierernahr 2001;554:371-376.

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16. Martínez ME, Ranilla MJ, Tejido ML, Ramos SS, Carro MD. Comparison of fermentation of diets of variable composition and microbial populations in the rumen of sheep and Rusitec fermenters. I. Digestibility, fermentation parameters, and microbial growth. J Dairy Sci 2010; 938:3684-3698. 17. Czerkawski JW, Breckenridge G. Design and development of a long-term rumen simulation technique Rusitec. Br J Nutr 1977;38:371.384. 18. Machmuller A, Soliva CR, Kreuzer M. In vitro ruminal methane suppression by lauric acid as influenced by dietary calcium. Can J Anim Sci 2002;82:233-239. 19. Hoedtke S, Zeyner A. Comparative evaluation of laboratory-scale silages using standard glass jar silages or vacuum-packed model silages. J Sci Food Agric 2011;91(5):841-849. 20. McDougall EI. Studies on ruminant saliva l. The composition and output of sheep´s saliva. Biochem J 1948;43:99-109. 21. Association of Official Analytical Chemists. AOAC 973.18. Fiber acid detergent and lignin H2SO4 in animal feed. Gaithersburg, MD, USA. 2010. 22. Association of Official Analytical Chemists. AOAC 930.15. Moisture in animal, loss on drying at 135 C for 2 hours. Gaithersburg, MD, USA: AOAC International. 2000. 23. Van Soest PJ, Robertson JB, Lewis BA. Methods for dietary fiber neutral detergent fiber and nonstarch polysaccharides in relation to animal nutrition. J Dairy Sci 1991;(7410):3583-3597. 24. Tilley JMA, Terry RA. A two stage technique for in vitro digestion of forage crops. Grass Forage Sci 1963;182:104-111. 25. Moore JE. Procedures for the two-stage in vitro digestion of for ages. In Harris, L.E. Nutrition research techniques for domestic and wild animals, Vol. 1. Logan: Utah State University. 1970. 26. Rojas A. Conceptos y práctica de microbiología general. Universidad Nacional de Colombia. Palmira. 2011. 27. Roa ML, Castillo CA, Tellez E. Influencia del tiempo de maduración en la calidad nutricional de ensilajes con forrajes arbóreos. Rev Sist Prod Agroecol 2010;11:63-73. 28. Barahona R, Sánchez S. Limitaciones físicas y químicas de la digestibilidad de pastos tropicales y estrategias para aumentarla. Rev Corpoica Ciencia y Tecnol Agropecuaria 2005;6:69-82. 29. Krause KM, Oetzel GR. Understanding and preventing subacute ruminal acidosis in dairy herds: A review. Anim Feed Sci Technol 2006;126:215-236. 35

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30. Emery RS, Smith CK, Grimes RM, Huffman CF, Duncan CW. Physical and chemical changes in bovine saliva and rumen liquid with different hay-grain rations. J Dairy Sci 1960;431:76– 80. 31. Calsamiglia S, Ferret A. Fisiología ruminal relacionada con la patología digestiva: acidosis y meteorismo. Curso de Especializacion FEDNA. Barcelona, España. 2002. www.produccion.animal.com.ar. 32. Araujo O, Vergara-López J. Propiedades físicas y químicas del rumen. Arch Latinoam Prod Anim 2007;15:133-140. 33. Mathison GW, Okine EK, McAllister TA, Dong Y, Galbraith J, Dmytruk OIN. Reducing methane emissions from ruminant animals J Appl Anim Res 1998;14:1:1-28. 34. Posada SL, Noguera RR. Técnica in vitro de producción de gases: Una herramienta para la evaluación de alimentos para rumiantes (In vitro technique of gas production: a tool for feed assesment for ruminants). Livest Res Rural Dev 2005;17Art. #36. 35. García-González RR, González JS, López SS. Decrease of ruminal methane production in Rusitec fermenters through the addition of plant material from rhubarb (Rheum spp). and alder buckthorn (Frangula alnus). J Dairy Sci 2010;938:3755-3763. 36. Jarrige R, Ruckbusch Y, Demarquily C, Farce MH, Journet M. Nutrition des ruminants domestiques: Ingestion et digestion. Paris: INRA editions. 1995. https://books.google.com.co/books?id=pIbmTs7_DDIC 37. Lee MRF, Merry RJ, Davies DR, Moorby JM, Humphreys MO, Theodorou MK, MacRae JC, Scolland ND. Effect of increasing availability of water-soluble carbohydrates on in.vitro rumen fermentation. Anim Feed Sci Technol 2003;104(4):59-70. 38. Merry RJ, Lee MR, Davies DR, Dewhurst RJ, Moorby JM, Scollan ND, Theodorou MK. Effects of high-sugar ryegrass silage and mixtures with red clover silage on ruminant digestion. 1. In vitro and in vivo studies of nitrogen utilization. J Anim Sci 2006;8411:30493060. 39. Abreu A, Carulla JE, Kreuzer M, Lascano CE, Diaz TE, Cano A, Hess, HD. Efecto del fruto, del pericarpio y del extracto semipurificado de saponinas de Sapindus saponaria sobre la fermentación ruminal y la metanogenesis in vitro en un sistema RUSITEC. Rev Col Cienc Pecu 2003;162,147-154. 40. Satter LD, Slyter LL. Effect of ammonia concentration on rumen microbial protein production in vitro. British J Nutr 1974;32:199-208.

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41. Holguín VA. Optimización de Tithonia diversifolia ensilada como alimento para ovinos de pelo [tesis doctorado]. Palmira, Colombia: Universidad Nacional de Colombia; 2016. 42. La O O, Valenciaga D, González H, Orozco A, Castillo Y, Ruíz O, Gutiérrez E, Rodríguez C, Arzola C. Efecto de la combinación de Tithonia diversifolia y Pennisetum purpureum vc. Cuba CT.115 en la cinética y producción de gas in vitro. Rev Cuba Ciencia Agrí 2009;43:149152. 43. Patra AK, Saxena J. Exploitation of dietary tannins to improve rumen metabolism and ruminant nutrition. J Sci Food Agric 2011;91(1):24-37. 44. Verdecia D, Ramírez J, Leonard I, Álvarez Y, Bazán Y, Bodas R, Andrés S, Álvarez J, Giráldez F, López S. Calidad de la Tithonia diversifolia en una zona del Valle del Cauto. REDVET 2011; 125.

https://doi.org/10.22319/rmcp.v11i1.4913 Article

Growth dynamics and senescence of digit grass as a response to several canopy heights

José Dantas Gusmão Filho a* Daniela Deitos Fries b Braulio Maia de Lana Sousa c Jailson Lara Fagundes c Alfredo Acosta Backes c Daniel Lucas Santos Dias d Sarita Socorro Campos Pinheiro e Fábio Andrade Teixeira b

Instituto Federal de Educação, Ciência e Tecnologia de Sergipe - Rodovia Juscelino Kubitschek, s/n - Zona Rural, Nossa Senhora da Glória - SE, 49680-000. b

Universidade Estadual do Sudoeste da Bahia, Bahia, Brasil.

Universidade Federal de Sergipe, São Cristovão, Sergipe, Brasil.

Universidade Estadual de Feira de Santana, Bahia, Brasil.

Instituto Federal de Educação, Ciencia e Tecnologia de Sergipe. São Cristovão, Sergipe, Brasil.

*Corresponding author: dantas.zoot@hotmail.com

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Abstract: The purpose of this study was to examine the growth and senescence dynamics of Digitaria eriantha cv. Survenola as a response to several canopy heights (25, 35, 45, and 55 cm) of harvests in two seasons of the year (rainy and dry). The experiment was established at the Federal University of Sergipe, in São Cristóvão - SE, Brazil, from 03/26/2015 to 03/28/2016, under a randomized-complete-block design with four replicates. Plots were irrigated, and upon reaching the pre-established canopy heights, they were cut to a 10 cm-residual height. Increasing canopy heights in the dry season led to lower tiller density, for basal and aerial tillers. However, irrespective of tiller type and season, this variable increased after the rest period. Light interception rose with canopy heights (P<0.05) in the dry period and it showed a quadratic response in the rainy season. Greater canopy heights led to a higher (P<0.05) daily leaf senescence rates and daily stem growth rates. Regardless of the season, the total accumulation and net herbage accumulation rates of basal tillers increased as canopy heights did. The greatest canopy height promoted the daily stem production, whereas the lowest height did not allow the grass to express its production potential. The defoliation-height range of 35 to 45 cm is the most recommended, as it favors the control of stem growth and leaf senescence. Key words: Forage accumulation, Digitaria eriantha cv. Survenola, Light interception, Morphogenesis.

Received: 24/05/2018 Accepted 10/12/2018

Introduction

Digitaria eriantha Steud cv. Survenola, named recently for the standardization of scientific writing(1), was once known as Digitaria umfolozi and is popularly identified in Brazil as ‘faixa-branca’ or ‘pangolão’. It is a low-fertility hybrid plant obtained from the cross between D. setivalva Stent and D. valida Stent that has a tussock form of growth and is propagated via stolons. It is somewhat tolerant to low-rainfall periods by reason of its ability to capture dew, that condense together forming water droplets. The plant has a high regrowth capacity, which favors its use for grazing and harvesting(2). It is also the most largely used grass species 39

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in northeast Brazil, notably in the states of Sergipe and Bahia, mainly because of its persistence in the soil and climatic conditions of that region, which has aroused the interest of producers, however, information on the production of this forage plant is still incipient, and the existing results often originate from regions of different environmental conditions(3). Net herbage accumulation in a pasture is the result of the balance between growth, senescence, and death of tissues — which are a consequence of the growth of new structures(4) like leaves and stems on individual tillers — and of the number of existing tillers (density), associated with tillering patterns (appearance, mortality, and survival)(5). However, other factors such as the amount and quality of light, temperature, water, and nutrients available in the local environment and the management strategy adopted interfere with photosynthesis and with the growth and senescence dynamics of a pasture(6). Increases in forage mass influence the leaf area index (LAI) and consequently light interception. Canopy height can be used as an indicator of the right time for defoliation, since LAIs above the ‘critical limit’ — when the canopy intercepts 95% of the incident light — favor stem and senescent-material accumulation(7). However, adopting a fixed or predetermined rest period for a grass species is not an effective management strategy to monitor the pasture growth and structure, given the physical and structural alterations the plant undergoes throughout the year. In view of the above considerations, the present study was proposed to evaluate the herbageaccumulation dynamics of Digitaria eriantha cv. Survenola subjected to different canopy heights at two seasons of the year (rainy and dry).

Material and methods

The study was conducted in the Forage Plants Section of the Federal University of Sergipe (UFS), located in the municipality of São Cristóvão - SE, Brazil (10°55'53.7" S, longitude 37°06'18.8" W, 5 m asl). According to the Köppen classification, the climate in the region is a tropical Awa type. The average annual precipitation, temperature, and air relative humidity in São Cristóvão are 1,200 mm, 25.5 ºC, and 75 %, respectively(8). The National Institute of Meteorology (Instituto Nacional de Meteorologia) delivered the climatic data recorded during this study (Figures 1 and 2), where rainy and dry seasons are shown.

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300

Rainy

Dry

35 30 25 20 15 10 5 0

250 200 150 100 50 0

Precipitation (mm) Maximum Temperature Minimum Temperature

Temperature (ºC)

Precipitation and Evapotranspiration (mm)

Figure 1. Precipitation, potential evapotranspiration and average, maximum and minimum temperatures during the experimental period(9)

Potential Evapotranspiration Average Temperature

1800

Rainy

Dry

80.0

1600

75.0

1400

70.0

1200 65.0 1000 60.0

800 600

55.0

400

50.0

Global Radiation (KJ/M²)

Relative Humidity (%)

Global Radiation (Kj m²)

Figure 2. Global radiation (Kj m2) and relative humidity of the air during the experimental period(9)

Relative Humidity (%)

The soil in the experimental area was classified as a Quartzipsamment of clayey texture(10) with a flat relief. Before the experiment was established soil samples with a soil auger from three areas in each plot, at the 0-20 cm layer, and mixed to generate a composite sample. Subsequently, these were sent to the Technological and Research Institute of Sergipe State (Instituto Tecnológico e de Pesquisas do Estado de Sergipe - ITPS) for an analysis of chemical and particle-size properties that revealed the following composition: organic 41

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matter= 10.6 g.dm‒3; pH in H20= 6.15; P= 45.4 mg.dm‾3; Na= 0.053 cmolc.dm⁻3; Ca= 3.78 cmolc.dm‒3; Mg= 1.925 cmolc.dm‒3; Al= 0.08 cmolc.dm⁻3; H+Al= 0.67 cmolc.dm‒3; sum of bases= 5.77 cmolc.dm⁻3; CEC= 6.44 cmolc.dm‒3; base saturation= 89.60 %, and clay content 9.97 %. According to the results of the soil analysis and in conformity with the recommendations of the Soil Fertility Committee of Minas Gerais State (Comissão de Fertilidade do Solo do Estado de Minas Gerais), no liming was required, since the base saturation content of the soil was 89.6 %. However, maintenance fertilization was necessary, and so 200 kg ha‒1 K2O in the form of potassium chloride were applied, split in three fractions(11). During the experimental period, fertilization was performed using 300 kg N ha‒1 yr‒1 in the form of ammonium sulfate. Because the harvest intervals depended on the time the plants reached the target canopy heights were imposed as treatments, different quantities of nitrogen fertilizer were applied after each harvest. The grass was established in a total area of 90 m2 in June 2014. The area was divided into sixteen 5.2 m-2-experimental plots. In March 2015, a uniformity cut was made in all plots at 10 cm-stubble to start the study. Evaluations began on 03/26/2015 and ended on 03/28/2016, totaling 368 d of experimental period. Plots were irrigated with 5 mm of water the periods of water stress each two days due to the soil low water-retention capacity and the need for improving fertilizer utilization and maximizing herbage growth. Treatments consisted of four canopy heights (25, 35, 45, and 55 cm) of harvest evaluated at two times of the year: rainy (March 26 to September 20, 2015), and dry seasons (September 21 to March 20, 2016). After every evaluation finished, were clipped the plants in all the experimental plots to a 10 cm of residual herbage. A randomized-complete-block experimental design was adopted, with four replicates, with 16 experimental units. Canopy height was measured twice weekly, at five points per experimental unit, using a centimeter-graduated ruler(12). Whenever the canopies reached the pre-established heights, was monitored the rest period (PD) (time required for the canopy to reach the established heights), their leaf area index and light interception using a SunScan® canopy analyzer (Delta Devices Ltd., Cambridge, United Kingdom) at three random points per experimental unit (plots). Evaluations corresponded to a reading performed above the canopy and another at the soil level (below the canopy). The forage accumulation dynamics was evaluated weekly in five basal and five aerial tillers randomly selected and marked (after emergence) per experimental unit measuring the elongation of leaf blades and stems and senescence of leaf blades. On the last day of each evaluation, all marked tillers were cut at the soil level (basal tillers) or at the insertion point (aerial tillers), wrapped in a plastic bag, and immediately transported to a cold room to minimize moisture losses. With these data leaf and stem elongation rates and the leaf 42

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senescence rate (cm tillers‒1 day‒1) were estimated the, used to calculate the forage accumulation rate(13). Then, were dried the basal and aerial tillers in a forced-air oven at 65 ºC for 72 h and weighted them. Were calculated a length-mass conversion factor dividing the mass of each component by its respective growth, which was used to transform all field readings from cm tiller ‒1 d‒1 into mg tiller‒1 d‒1. Finally, were multiplied these values by their respective tiller density in each experimental unit in order to compute the forage dry matter (DM) in kg ha‒1 d‒1. Were assessed the live tillers density using 0.25-m2–metal-frame placed at random per experimental unit, always pre-harvest. Thus, the values for leaf and stem elongation rates and leaf senescence rate were transformed into leaf and stem growth rates and leaf senescence rate (kg ha‒1 d‒1 dry matter), respectively, for basal and aerial tillers. The sum of leaf growth and stem growth resulted in the total growth rate, whereas forage accumulation rate was calculated as the difference between total growth rate and leaf senescence rate(14). The variance analyzes were performed, considering a randomized block design with four replicates, and orthogonal decomposition of the sum of treatment squares into linear, quadratic, and cubic effects to probe the best fit of the model. The significance of effects was analyzed by the F test, at α=0.05, using the Computational Package Statistical Analysis System (SAS), version 9.0.

Results and discussion

Tiller density (TD) decreased linearly (P<0.05) for basal (Figure 3A) and aerial (Figure 3B) tillers in the dry season as the canopy heights increased. The same was not influenced (P>0.05) during the rainy season.

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Figure 3. Tiller density (TD, A and B), rest period (RP; C) and light interception (LI; D) of basal (A) and aerial (B) tillers of digitgrass as a function of canopy heights during the rainy () and dry (○) seasons 1 Ŷ(○) = 277,44-1,8892*D R² = 0,80

2 3 4 5

Ȳ () = 144 Ŷ(○) = 5,5647+0,7832*D R2 = 0,99 Ȳ () = 540

6 7 8 9 10 11

Ŷ() = 55,109+1,556*D-0,015*D2 R2 = 0,99

Ŷ(○) = 900,2-7,5357*D R² = 0,72

Ŷ() = 2,1426+0,7798*D R2 = 0,96

Ŷ(○) = 75,063+0,3136*D R2 = 0,88

12 13

The rest period (Figure 3C) of the basal tillers, in the two seasons; and light interception (LI) (Figure 3D) in the dry period increased linearly (P<0.05) with the canopy heights. In the rainy season, this last variable responded quadratically (P<0.05) with a maximum LI value of 95.5 % at the canopy height of 55 cm (Figure 3D). The reduction in the density of Basal (Figure 3A) and aerial (Figure 3B) tillers in the dry season, as the canopy heights increased can be explained by the longer rest period (Figure 3C); i.e., during the time to reach the target canopy heights, leaf production and stem elongation enlarged, which initially contributed to increasing light interception (Figure 3D), but ultimately reducing the incidence of light under the canopy. Reduced incidence of light at the base of the canopy caused the decrease of tiller density, as the activation of basal and axillary buds for the production of new tillers was inhibited(15), as the rest time was longer for the greater canopy heights. In an experiment with Marandu Palisadegrass, longer harvest intervals negatively affected tiller densities, which was possibly due to the amount and quality of light reaching the canopy(16). The reduction of light at the base of the lawn with increasing pasture height, influences the reduction of the population density of tillers(17). In the dry period, the intervals between harvests for the canopy to reach the pre-defined heights was on average 11.5 % longer than in the rainy period. Even though the plots were irrigated, evapotranspiration (Figure 1) and limited soil water retention capacity may explain 44

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these results; i.e., the amount of water was not sufficient to provide the ideal plant-growth conditions. In the rainy season, the climatic conditions (e.g., higher precipitation (Figure 1) and solar radiation of 1197.3 kj m2 (Figure 2) positively influenced plant growth. These results are likely due to the higher photosynthesis rates, which may culminate in elevated production of photo assimilates, thereby providing better conditions for plant growth. In an evaluation of the structural traits of Tanzania grass, more leaves had to be produced for the canopy to reach 95 or 97 % of LI, so grass plants could intercept more light and required longer rest periods(15). The longer the canopy needs to attain a pre-established height, the larger the forage accumulation will be, especially under favorable conditions, such as higher precipitation, temperature, and light. However, this larger forage mass may result from the growth of stem and dead material, since leaf production increase is stabilized and stem growth and senescence processes are accelerated(7). Leaf growth rate (LGR) in basal (Figure 4A) and aerial (Figure 4B) tillers was not influenced (P>0.05) by the increasing canopy heights during the rainy and dry seasons. However, the leaf senescence rate of basal (Figure 4C) and aerial (Figure 4D) tillers, and the stem growth rate (SGR) of basal (Figure 4E) and aerial (Figure 4F) tillers in both seasons increased linearly (P<0.05) as canopy heights were greater. As a result, because of its longer rest period (Figure 3C), the highest canopy height (55 cm) would reduce the grass productivity, since no record higher daily growth rates under this treatment. The results for leaf senescence rate (Figures 4C and D) may be a consequence of the longer rest periods (Figure 3C), which led the leaves to reach their maximum lifespan and increase senescence rate. Higher canopy heights granted further plant development, as a consequence, more leaves completed their lifespan and senescent tissue accumulated (18). The senescence rates of basal (Figure 4C) and aerial (Figure 4D) tillers while raining were 43 % and 26 % higher, on average, than in the dry season, respectively. This is explained by the higher rainfall (Figure 1) in the wet period. Solar radiation and temperature in this last season (Figure 2) averaged 1197.3 kj m2 and 27.8 ยบC, in that order. Despite the irrigation during the months with sparser precipitation, evapotranspiration (Figure 1) might have influenced these results.

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Figura 4. Leaf growth (LGR, A and B), leaf senescence (LSR, C and D) and stem growth rates (SGR, E and F) of basal (A,C and E) and aerial (B, D and F) tillers of digitgrass as a function of canopy heights during the rainy () and dry (○) seasons 1 2

Ȳ () = 5,63 Ȳ(○) = 6,14

3 4 5

Ȳ () = 48,07 Ȳ(○) = 44,05

6 7 8 9 Ŷ() = -2,5623+0,1272*D R2 = 0,99

10 11 12 13

Ŷ(○) = -1,9077+0,0919*D R2 = 0,97

Ŷ() = -5,0635+0,9572*D R2 = 0,83 Ŷ(○) = -4,1136+0,7602*D R2 = 0,94

14 15 16 17

Ŷ(○) = -29,014 +1,9077*D R2 = 0,96

Ŷ() = 2,6293+ 0,1935*D R2 = 0,96

Ŷ(○) = -0,0635+0,2111*D R2= 0,95

19 20

Ŷ() = -22,047+1,4237*D R2 = 0,98

21 22

The increasing canopy height provided a longer rest period (Figure 3C), and favored the stem and dead material to build up, which was likely due to the shading of basal leaves. At the greatest canopy heights, stem elongation might occur as an attempt to rise the younger leaves in the upper stratum of the pasture, where canopy receives more photosynthetically active radiation. Increasing stem elongation and growth rates should reduce the pasture quality, because stems are the most fibrous fraction of forage, restricting its digestibility(15). The shading of leaves at the base of the canopy may reduce their photosynthetic efficiency and tiller density in a mechanism known as population size/density compensation, in addition to elevating the accumulation of old tillers, which have leaf appearance and elongation rates reduced and senescence rate increased(19). 46

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Total growth rate (TGR) (Figure 5A) of basal tillers rose linearly (P<0.05) at both seasons, but the net herbage accumulation rate (NHAR) (Figure 5C) just did it during the dry season (P<0.05) as canopy heights were greater. About aerial tillers, the TGR (Figure 5B) improved during the dry season, but remained with no change during the rainy season.

Figura 5. Total growth rate (TGR; A and B) and net herbage accumulation rate (NHAR; C and D) in basal (A and C) and aerial (B and D) tillers of digitgrass as a function of defoliation heights during the rainy () and dry (○) seasons 1 2

Ŷ() = 14,145+1,7367*D R2 = 0,96

Ȳ () = 14,01 Ŷ(○) = 4,9763+0,2882*D R2 = 0,99

3 4 5

Ŷ(○) = 14,888+1,9227*D R2 = 0,99

6 7 8 9

Ŷ() = 19,208+0,7795*D R2 = 0,55

Ȳ () = 11,49

10 Ȳ (○) = 14,73

11 12

Ŷ(○) = 19,002+ 1,1625*D R2 = 0,99

13 14

NHAR (Figure 5D) did not change at the two seasons (P>0.05) because of the canopy heights. The population density of basal and aerial tillers (Figures 3A and 3B), leaf senescence rate (Figures 4C and 4D) and stem growth rate (Figures 4E and 4F) influenced, at different magnitudes, the TGR and NHAR of basal and aerial tillers during the dry and rainy seasons. Because the canopy heights did not influence leaf growth rate (Figures 4A and 4B), then, the stem growth rate (Figure 4E and 4F) and hence possibly the tiller size:density ratio (17) may explain the higher total growth rate (Figures 5A and B) and consequently NHAR (Figure 5C) as canopy heights increased. Results probed that the density of basal (Figure 4A) and aerial (Figure 4B) tillers in the dry season declined, as the canopy heights were greater; whereas 47

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was did not find any influence in the rainy season. However, the increasing canopy height may require heavier tillers to support its structure, which influenced the stem growth (Figures 4E and 4F) and senescence rates (Figures 4C and 4D). Other authors found that seasons of the year and canopy heights also modified the tiller size:density ratio: Decreasing tiller densities are compensated by an increase in tiller weight, which results from higher stemand leaf-elongation rates(20). They observed that seasonal variations influenced the results. In an study with Tanzania grass subjected to three grazing intervals (90, 95, and 100 % LI) and two defoliation intensities (25 and 50 cm height), long rest periods caused changes in the canopy structure, with greater contribution of stem and dead material(21). In this experiment, the increasing canopy heights elicited responses similar to those reported in this last study, with larger proportions of stem and greater senescence. At the lowest canopy height (25 cm), results indicated an increase in the density of basal (Figure 3A) and aerial (Figure 3B) tillers during the dry season. For basal and aerial tillers in both seasons, however, there was a decrease in the rest period (Figure 3C), light interception percentage (Figure 3D), leaf senescence rate (Figures 4C and 4D), and stem growth rate (Figures 4E and 4F). On the other hand, TGR (Figures 5A and 5B) for basal tillers in the two seasons and aerial tillers in the dry season was lower at the 25-cm-canopy height. The same was true for NHAR (Figure 5C) of basal tillers in both seasons. Based on these results, it is suggested that, at the lowest height, senescence and stem elongation were lessened, implying a better forage nutritional quality. Nevertheless, higher defoliation frequencies, with shorter rest periods, may deplete the energy reserve of grass plants for canopy growth and, at the end, reduce the persistence of this grass over time. The greatest defoliation height (55 cm) provided the lowest tiller density (Figures 3A and 3B) for basal and aerial tillers in the dry season; and the highest leaf senescence rate (Figures 4C and 4D) and stem growth rate (Figures 4E and 4F) for basal and aerial tillers in the two periods, which may negatively influence the herbage digestibility. A longer rest period may bring about an increase in stem and senescent-material growth rates, which may reduce the pasture quality(15). Therefore, letting the canopy to reach between 35 and 45 cm can benefit herbage accumulation as well as provide better quality to digit grass, and ultimately improving its productivity. Depending on the time of the year and growth conditions, a shorter rest period with lower defoliation heights may lead to yield losses, whereas longer rest periods may induce nutritional and quantity losses. Moreover, both cases can result in pasture degradation(7). As previously discussed, the tiller size:density ratio influenced the results; stem elongation was higher possibly because the rest period to reach the greater canopy heights was longer. Other research probed that the weight of tillers in the vegetative stage is lower than in the reproductive stage for Brachiaria decumbens, which also bore inflorescences(22). The same authors reported that taller plants had heavier vegetative tillers, but a lower tiller density. These findings can explain the present results, where the increasing canopy heights provided an increase in TGR and NHAR. In the dry season, the vegetative tillers changed to a 48

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reproductive stage that resulted in higher stem growth rates. In an evaluation of the nutritional value of tillers from Brachiaria decumbens cv. Basilisk plants, researchers found a greater stem elongation rate when tillers progressed from the vegetative to the reproductive state, contributing to a lower leaf:stem ratio(23).

Conclusions and implications

Digit grass should be managed in a defoliation-height interval of 35 to 45 cm, because when defoliated above this range, it reaches a greater accumulation of forage, to the detriment of greater accumulation of stem and dead material. Further studies should be undertaken focusing on the residual height with animals involved in the evaluation procedures, under different environmental conditions.

Acknowledgments

The authors thank the department of Animal Science of the Universidade Federal de Sergipe, the Animal Science Graduate Program of Universidade Estadual do Sudoeste da Bahia, and the Instituto Federal de Educação, Ciência e Técnologia de Sergipe, Brazil for the support provided for the development of this research. This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001, and also Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) and Fundação de Apoio à Pesquisa e à Inovação Tecnológica do Estado de Sergipe (FAPITEC).

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12. Pena KS, Junior DN, Silva SC, Euclides VPB, Zanine AM. Características morfogênicas, estruturais e acúmulo de forragem do capim-tanzânia submetido a duas alturas e três intervalos de corte. Rev Bras Zootec 2009;38(11):2127-2136. 13. Lemaire E, Chapman D. Tissue flows in grazed plant communities. In: Hodgson I, Illius AW, editors. The ecology and management of grazing systems. Wallingford: CAB International; 1996:3-36. 14. Sousa BML, Nascimento-Júnior D, Monteiro HCF, Da-Silva SC, Vilela HH, Silveira MCT, Rodrigues CS, Sbrissia AF. Dynamics of forage accumulation in Elephant grass subjected to rotational grazing intensities. Rev Bras Zootec 2013;42(9):629-638. 15. Cutrim Junior JAA, Cândido MJD, Valente, BSM, Carneiro MSS, Carneiro HAV. Características estruturais do dossel de capim tanzânia submetido a três frequências de desfolhação e dois resíduos pós pastejo. Rev Bras Zootec 2011; 40(3):489-497. 16. Difante GS, Junior DN, Da Silva SC, Euclides VPB, Montagner DB, Da Silveira MCT, Pena KS. Características morfogênicas e estruturais do capim-marandu submetido a combinações de alturas e intervalos de corte. Rev Bras Zootec 2011;40(5):955-963. 17. Sbrissia AF, Da-Silva SC. Compensação tamanho/densidade populacional de perfilhos em pastos de capim-marandu. Rev Bras Zootecn 2008;37(1):35-47. 18. Santos MER, Fonseca DM, Braz TGS, Silva SP, Gomes VM, Silva GP. Características morfogênicas e estruturais de perfilhos em locais do pasto de capim-braquiária com alturas variáveis. Rev Bras Zootec 2011;40(3):535-542. 19. Paiva AJ, Silva SC, Pereira LET, Caminha FO, Pereira PM, Guarda VDA. Morphogenesis on age categories of tillers in marandu palisadegrass. Sci Agric 2011;68(6):626-631. 20. Paciullo DSC, Campos NR, Gomide CAM, Castro CRT, Tavela RC, Rosiello ROP. Crescimento de capim-braquiária influenciado pelo grau de sombreamento e pela estação do ano. Pesq Agrop Bras 2008;43(7):917-923. 21. Barbosa RA, Nascimento-Júnior D, Vilela HH, Da-Silva SC, Euclides VPB, Sbrissia AF, Sousa BML. Morphogenic and structural characteristics of guinea grass pastures submitted to three frequencies and two defoliation severities. Rev Bras Zootec 2011;40(5):947-957. 22. Santos MER, Fonseca DM, Pimentel RM, Silva GP, Gomes VM, Silva SP. Número e peso de perfilhos no pasto de capim-braquiária sob lotação contínua. Acta Scient Animal Sci 2011;33(2):131-136.

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https://doi.org/10.22319/rmcp.v11i1.4565 Article

Forage yield and nutritional quality in Leucaena leucocephala and Megathyrsus maximus cv. Tanzania in an intensive silvopastoral system

Manuel Hernández Hernández a Silvia López Ortiz a* Jesús Jarillo Rodríguez b Eusebio Ortega Jiménez a Sergio Pérez Elizalde a Pablo Díaz Rivera a María Magdalena Crosby Galván a

Colegio de Postgraduados. Campus Veracruz. Km. 88.5 Carr. Fed. Xalapa−Veracruz, Predio Tepetates, Mpio. Manlio F. Altamirano, 91690, Veracruz, México. a

Universidad Nacional Autónoma de México. Facultad de Medicina Veterinaria y Zootecnia, Centro de Enseñanza, Investigación y Extensión en Ganadería Tropical, Veracruz, México.

*Corresponding author: silvialopez@colpos.mx

Abstract: The biomass and nutritional value of Leucaena leucocephala cv. Cunningham (5,000 trees ha-1) and Megathyrsus maximus cv. Tanzania was assessed in a silvopastoral system in a tropical hot sub-humid climate in the rainy and dry seasons. Samplings were done from August-October 2014 (rainy) and March-April 2015 (dry). The treatments were harvests at 20-, 30-, 40- and 50-d intervals in both seasons, randomly assigned to twelve (24 m2) paddocks. The grass accounted for most of the total available forage in the silvopastoral system (80 vs 20 %). In both seasons, the association yielded more forage at the 50-d interval (5,300 kg DM ha-1 in the rainy season and 1,620 kg DM ha-1 in the dry season) (P<0.05). During the rainy season, crude protein (CP) in the tree forage was

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higher at the 50-d interval (22 %; P<0.05), but did not change over the intervals during the dry season (28 %; P>0.05); neutral detergent fiber (NDF) did not change over time (44 %; P>0.05) and acid detergent fiber (ADF) increased in the 50-d interval (25 %, P<0.05) but in vitro dry matter digestibility (IVDMD) decreased (49 %; P<0.05), regardless of season. Crude protein (10%; P<0.001) and IVDMD (58 %; P<0.03) of M. maximus remained high from the 20- to 40-d intervals, although in both seasons NDF and ADF fractions significantly increased after the 40-d interval. The evaluated silvopastoral system attains highest yield between the 40- and 50-d intervals. The highest nutritional quality of M. maximus was at 40 ds, after which the nutritional quality of L. leucocephala may compensate for the lost nutritional quality of the grass, regardless of season. Key words: Tree-grass association, Silvopastoral system, Nutritional quality, Season.

Received: 30/07/2017 Accepted:07/01/2019

Introduction Climatic conditions in the tropical regions of Mexico favor livestock forage production. However, the favorable temperatures and rainfall of the summer/fall rainy season can become limiting during the winter/spring dry season(1). The low temperatures and high cloudiness common during the transition from rainy to dry seasons can decrease growth, and the absence of precipitation in the spring can slow growth in grasses, resulting in poor forage quality and shortages in quantity(2,3). Associating grasses and forage trees in silvopastoral systems can extend forage availability yearround while improving forage chemical-nutritional quality(4,5). Different associations of grasses and forage trees can be more productive than grass-only pastures(6,7), and lengthen forage availability, even in conditions of seasonal precipitation(8). Moreover, forage nutritional quality (tree foliage plus grasses) is superior to grass monocultures(5,9). Grass/forage tree associations can therefore increase total forage production and improve the quality of livestock diets(10,11). Obtaining optimum forage yield and quality requires evaluation of possible forage tree/grass combinations to ensure they are viable, convenient and manageable. Megathyrsus maximus cv. Tanzania is widely accepted by producers because of its high production capacity, 10 to 14 % protein content, good digestibility (up to 60-70 %), acceptance by livestock, and adaptability to diverse edaphic and climatic conditions(12,13). In the state of Veracruz, Mexico, this cultivar exhibits high forage production (up to 8,317 kg DM ha-1 at a 42-d interval in the rainy season; up to 1,027 54

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kg DM ha-1 at a 35-d interval in the dry season)(14). The productive potential of this forage grass can be complemented by forage trees grown in rows and high densities(15). The legume tree Leucaena leucocephala is the most widely used tree species in silvopastoral systems because it contributes to improving cattle diet quality(16) and increasing the amount of forage available in silvopastoral systems. When managed properly it conserves its green leaves in the dry season (March-June) and becomes the most important forage source. Moreover, it provides better nutritional quality than grasses during this season, when both forage availability and crude protein content are lower(17,18). It also positively affects biomass production capacity and the chemical composition of the grasses with which it is associated(9,16). The grasses and trees in silvopastoral systems have different growth habits(19). These determine their regrowth and forage production capacities over time(20) and need to be considered in management plans(21). In Leucaena sp.-M. maximus (Tanzania) associations, rest intervals are recommended that allow the trees to recover without negatively effecting the grass. This means implementing intervals apt for both species. These cannot be overly long because the grass matures more rapidly and its nutritional quality changes apace(13), but Leucaena sp. requires more time to recover than grasses(22). Season can also affect the recovery rate of each component. The present study objective was to determine the rest interval resulting in the highest forage production and best forage nutritional quality in a silvopastoral system containing L. leucocephala and M. maximus, in the rainy and dry seasons, in a warm weather climate under a seasonal rainfall regime.

Material and methods Experimental site location and characteristics

The experiment was done in Juan Rodríguez Clara Municipality, in the state of Veracruz, Mexico (18°00′11″ - 17°59′5″ N; 95°16′29″ - 95°16′30″ W). Located at 107 m asl, regional climate is warm sub-humid with summer rains (AW2), with the highest mean temperature (28 oC) in April and the lowest (20 oC) in January(23). During the study period rainfall was highest (235 mm/month) from August to October and lowest (28 mm/month) from December to April(24) (Figure 1).

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350

300

250

200

Rainfall

150

Temperature

15 10

100

Temperature (oC)

Rainfall (mm)

Figure 1: Study region mean monthly rainfall (mm) and temperature (Â°C) from 2014-2015

50 0

0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Months

Experimental site and parcels

The experimental site was a 0.5 ha pasture planted in 2011 with a silvopastoral system constituting the grass M. maximus cv. Tanzania and the legume tree L. leucocephala cv. Cunningham. The grass was propagated via vegetative material and the trees by seed. The latter were planted at a 5,000 plants ha-1 density in rows 2.0 m apart with 1.0 m between plants. Prior to the experiment, the pasture had been grazed-browsed starting twelve months after planting using traditional management practices. It was grazed for 3 to 4 h a day after milking for approximately seven continuous days with irregular rest periods (>25 d) and an animal load of 20 to 27 AU. Within the site a 288 m2 experimental area was marked off and divided into twelve 24 m2 (6 x 4 m) plots, each of which was an experimental unit.

Soil physicochemical composition

Soil samples were collected at the experimental site using a zig-zag pattern. Eight samples were taken at a depth of 30 cm and these pooled to form a composite sample for physical and chemical composition analysis(25). The analyses were performed in the Soil, Water and Plants Laboratory of 56

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the Postgraduate College (COLPOS), Veracruz Campus following established methods(25). Soils in the pasture were a sandy loam containing 64 % sand, 17 % clay and 19 % silt (Bouyoucos method, AS-09). The pH was slightly acidic (6.6, electrometric method, AS-02), and organic matter content was low (0.15 %) (Walkley and Black method, AS-07). The chemical composition included 100 mg L-1 nitrates (cadmium method), 70 mg L-1 ammonium (Nessler method), 108 mg L-1 potassium (Turbidimeter method) and 27 mg L-1 phosphorus (Amino acid method). Soil electrical conductivity at the site was 45 dS m-1 as estimated with the saturation extract method(26).

Treatments and experimental design

The treatments consisted of four post-harvest rest intervals (20, 30, 40 and 50 d) randomly assigned to each of the twelve experimental plots, with three replicates per treatment. Two biomass evaluations were done, the first from August 22 to September 21, 2014 (rainy season) and the second from May 23 to April 22, 2015 (dry season).

Experimental procedure

The experiment was carried out from August 2014 to April 2015. In both periods an initial cut of the aerial biomass was made to standardize forage plant height: M. maximus was cut at 20 cm above ground level and L. leucocephala was pruned at 1.0 m height. Pruning consisted of cutting the main and/or most woody branches(27). After the initial cut successive cuts were done according to the rest intervals defined for each treatment.

Variables

Total available biomass of the trees and grass, and forage nutritional quality at each interval were quantified. For each sampling period (rainy/dry season), four sampling points (2 x 1 m rectangles) were randomly assigned inside each of the three plots (replicates) of each treatment. Within each rectangle all new growth foliage (leaves and tender stems) on the trees was harvested as a means of simulating animal browsing, and simultaneously all grass green matter was harvested at 20 cm above ground level(12,28). From each sampling point two sub-samples of green biomass were taken: one to quantify dry matter and the other for nutritional quality analyses. Both grass and tree foliage samples were dried in a forced air oven at 60 Â°C for 48 h.

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Grass and tree foliage nutritional quality were assessed separately. Crude protein (CP) content was quantified with the Microkjeldahl method(29), neutral (NDF) and acid detergent fiber (ADF) with the filter bag technique (ANKOM2000; Ankom Technology, NY, USA) and in vitro dry matter digestibility (IVDMD) with the ANKOM Daisy incubator using Model F57 bags (ANKOM Technologies, Macedon, NY, USA)(30,31). Analyses were performed at the Animal Nutrition Laboratory at the COLPOS Montecillo Campus.

Statistical analysis

Variables for biomass (total, grass and tree) and nutritional quality (CP, NDF, ADF and IVDMD), were analyzed with a completely randomized design using a 4 x 2 factorial arrangement: four pasture rest periods and two seasons. The model included the effects of treatment (intervals 20, 30, 40 and 50 d), season (rainy and dry) and the season/interval interaction. The analyses were run with the GLM (Generalized Linear Model) procedure of the SAS statistical package(32). When statistical differences (P<0.05) were identified between treatments the LSMeans (Least Square Means) method was used to compare average biomass and nutritional quality for the grass and tree foliage.

Results Forage biomass

Total forage biomass (M. maximus + L. leucocephala) differed (P<0.001) in response to the season/interval interaction (Table 1). In the rainy season production was highest at 50 d (P<0.05), lowest at 20 d (P<0.05) and did not differ between 30 and 40 ds. In the dry season the highest yields were at 40 and 50 d, which did not differ (P>0.05), production was moderate at 30 d, which did differ from 40 d (P<0.05), and was lowest at 20 d, although this did not differ from 30 d (P>0.05).

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Table 1: Forage biomass for Megathyrsus maximus cv. Tanzania, Leucaena leucocephala cv. Cunningham and total biomass (M. maximus + L. leucocephala; kg DM ha-1) in a silvopastoral system at 20-, 30-, 40- and 50-d rest intervals in the rainy and dry seasons Rainy

Dry

Rest Intervals

Total

1140 ± 240c

60 ± 20c

1200 ± 24c

330 ± 250c

40 ± 20a

370 ± 240c

2270 ± 240b 100 ± 20c 2370 ± 24b

680 ± 240bc

20 ± 20a

700 ± 240bc

2330 ± 260b 300 ± 20a 2630 ± 26b

1090 ± 240ab

30 ± 20a

1120 ± 230ab

5110 ± 240a 190 ± 20b 5300 ± 24a

1580 ± 240a

30 ± 20a

1610 ± 230a

abc

Mm = M. maximus; Ll = L. leucocephala. Different letter superscripts in the same column indicate significant difference (P< 0.05).

The individual forage contributions of M. maximus and L. leucocephala also differed in response to the season/interval interaction (P<0.001). In the rainy season the amount of forage produced by both species increased as the interval lengthened. Between the 20- and 50-d intervals biomass for M. maximus increased from 1,140 to 5,110 kg DM ha-1 and that of L. leucocephala from 60 to 190 kg DM ha-1. Between the same intervals in the dry season M. maximus availability increased from 330 to 1,580 kg DM ha-1, whereas L. leucocephala biomass remained low (around 30 kg DM ha-1 at all intervals) (P>0.05) (Table 1). The grass (M. maximus) contributed more biomass than the legume tree (L. leucocephala) in both seasons: 96.3 vs. 88.6% in the rainy season; 97.7 vs. 88.0% in the dry season.

Biomass chemical-nutritional quality

Tree foliage CP contents differed in response to the season/interval interaction (P<0.05). In the rainy season CP content ranged from 22 to 29 % with the highest content at the 20-d interval (P<0.05) (Table 2). In contrast, during the dry season CP did not vary between intervals (P>0.05), but was higher overall than in the rainy season. This interaction had no effect on any other tree nutritional quality variable (P>0.05).

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Table 2: Crude protein content (%) of Leucaena leucocephala cv. Cunningham foliage in a silvopastoral system in association with M. maximus cv. Tanzania at 20-, 30-, 40- and 50-d intervals in the rainy and dry seasons Intervals

Rainy Season

Dry Season

29 ± 1.2a

23 ± 1.2b

26 ± 1.2a

23 ± 1.2b

30 ± 1.2a

22 ± 1.2b

28 ± 1.2a

Different letter superscripts in the same column indicate significant difference (P<0.05).

Neutral detergent fiber content (NDF) in the L. leucocephala foliage did not differ (P>0.91) between intervals (Table 3). In contrast, ADF was lowest at 20 ds (P<0.03), and higher (P<0.05) but not different among the remaining intervals (P>0.05). Foliage digestibility (IVDMD) was lowest at 50 d (P<0.05), while the remaining intervals were all higher by two to three percentage points (P<0.03).

Table 3: Neutral detergent fiber, acid detergent fiber and in vitro dry matter digestibility of Leucaena leucocephala cv. Cunningham foliage in a silvopastoral system in association with M. maximus cv. Tanzania at 20-, 30-, 40- and 50-d intervals Intervals

NDF (%)

ADF (%)

IVDMD (%)

45 ± 1.0a

21 ± 0.8b

52 ± 0.7a

44 ± 1.0a

24 ± 0.8a

52 ± 0.7a

45 ± 1.0a

23 ± 0.8ab

51 ± 0.7ab

45 ± 1.0a

25 ± 0.8a

49 ± 0.7b

NDF= neutral detergent fiber; ADF= acid detergent fiber; IVDMD= in vitro dry matter digestibility. ab Different letter superscripts in the same column indicate significant difference (P<0.05).

Overall CP and IVDMD values decreased in M. maximus with each subsequent harvest. Crude protein content (CP) varied between the intervals (P<0.01), with the highest value at 20 d (P<0.05), a slightly lower content at 30 and 40 d (P>0.05) and the lowest content at 50 d (P<0.05) (Table 4). Digestibility also varied between intervals (P<0.03) following a trend like that of CP, with the highest values at 20 d and the lowest at 50 d (P<0.05).

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Table 4: Crude protein (%) and in vitro dry matter digestibility (%) of Megathyrsus maximus cv. Tanzania in a silvopastoral system in association with Leucaena leucocephala cv. Cunningham, at 20,- 30-, 40- and 50-d intervals in the rainy and dry seasons Intervals

IVDMD

12 ± 0.5a

60 ± 1.3 a

10 ± 0.5b

58 ± 1.3 a

10 ± 0.5b

58 ± 1.3 a

7 ± 0.5c

54 ± 1.3 b

abc

CP= crude protein; IVDMD= in vitro dry matter digestibility. Different letter superscripts in the same column indicate significant difference (P<0.05).

The season/interval interaction affected both NDF (P<0.002) and ADF (P<0.001) in M. maximus. During the rainy season NDF accumulation did not differ between the 20-, 30- and 40-d intervals (P>0.05), which were lower overall than at 50 d (P<0.05) (Table 5). In the dry season, NDF was highest at 40 and 50 d, followed by contents at 30 ds and 20 ds (P<0.05). The same trend held for ADF, with the highest contents (P>0.05) at 40 and 50 ds (no difference between them, P>0.05) and the lowest at 20 and 30 d (P<0.05). Table 5: Neutral detergent fiber (%) and acid detergent fiber (%) of Megathyrsus maximus cv. Tanzania in a silvopastoral system in association with Leucaena leucocephala cv. Cunningham, at 20-, 30-, 40- and 50-d intervals in the rainy and dry seasons Rainy Season

Dry Season

Intervals

NDF

ADF

NDF

ADF

69 ± 0.8b

37 ± 0.7b

62 ± 0.8c

28 ± 0.7c

68 ± 0.8b

38 ± 0.7b

66 ± 0.8b

32 ± 0.7b

69 ± 0.8b

39 ± 0.7b

70 ± 0.8a

36 ± 0.7a

74 ± 0.8a

44 ± 0.7a

71 ± 0.8a

36 ± 0.7a

abc

NDF= neutral detergent fiber; ADF= acid detergent fiber. Different letter superscripts in the same column indicate significant difference (P<0.05).

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Discussion Total biomass remained higher at the longest cutting interval (50 ds) in both seasons. This increase can be associated with the longer recovery time allowed both the tree and grass species, which allowed them to accumulate more root and stem reserves(33,34) and therefore exhibit more vigorous regrowth. However, the overall contribution of L. leucocephala biomass was lower than that of M. maximus, most probably due to the lower density of the legume tree (5,000 plants ha-1) in the evaluated silvopastoral system(6). At densities of up to 35,000 trees ha-1 L. leucocephala is reported make a larger contribution to total forage biomass(7). The season/interval interaction affected yield in both L. leucocephala and M. maximus because growth conditions for these species differ between seasons. This coincides with previous studies carried out in seasonal precipitation conditions(12), which show that the climatic conditions (temperature and precipitation) during the rainy season in the present study favored forage production in these species(35,36). For instance, in the rainy season the 50-d harvest was made at 25 Â°C and 287 mm accumulated rainfall, both of which favor growth in L. leucocephala and M. maximus. During the dry season, by contrast, low rainfall (21 mm) and higher temperatures (28 Â°C) prevented the plants from fully expressing their production potential. Moreover, when a silvopastoral system depends on moisture from rainfall, some rest intervals may coincide with periods of more homogeneous moisture availability than others; this was the case at the 40-d interval in which production values were similar to those at 30 d in both seasons(37,38). Of note is that growth in L. leucocephala varied minimally during the dry season, exhibiting similar behavior among intervals. In part this is because moisture levels are more homogeneous over time in this season, changing little between intervals. In addition the response of L. leucocephala differs from that of grasses (the growth of which varies widely in the dry season), possibly because they have different growth habits and survival strategies(39,40). This allows legume trees like L. leucocephala to explore deeper soil layers in search of water and other resources. Agroecological conditions (e.g. soil type and climate) can vary widely between regions and management strategies must respond in kind. This makes direct comparisons between the present results and those from other regions a challenging prospect(1,41). Total forage biomass in the present study at 50 ds in the rainy season (5,300 kg DM ha-1) was comparable to the 4,350 kg at a 42-d interval reported for a Cynodon nlemfuensis-L. leucocephala association in the rainy season(42). However, it is lower than the 7,080 kg DM ha-1 at a 40-d interval in the rainy season reported for an association of L. leucocephala with Brachiaria ruziziensis (Dawar napier) and Pennisetum sp. (Taiwan A25) grasses(22). Variation is also apparent during the dry season. For instance, total biomass was 2,690 kg at a 45-d interval in the dry season for a L. leucocephala-M. maximus

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association under irrigation(7). But it was 3,221 kg at a 42-d interval during the dry season in a Cenchrus ciliaris-L. leucocephala association without irrigation(43). Forage biomass in the studied L. leucocephala-M. maximus silvopastoral system had the highest nutritional quality between the 40- and 50-d intervals. In M. maximus nutritional quality tended to decrease after 40 d as fiber fractions increased, and CP and IVDMD decreased. However, in L. leucocephala it varied little over time as the foliage retained relatively steady CP levels and IVDMD values while the fiber fractions (NDF and ADF) were unchanged. These results agree with previous reports that L. leucocephala can maintain protein content up to 70 d (24 %) during rainy seasons(44), and that grasses, regardless of species, decrease their nutrient concentration more rapidly than trees because their growth cycles are shorter and they reach maturity more quickly, consequently reducing their chemical-nutritional quality(20). For example, nutritional quality is known to decline in the grass C. nlemfuensis in the rainy season beginning at a 42-d interval(45), as is also the case in the grasses B. ruziziensis (Dawar napier) and Pennisetum sp. (Taiwan A25) at a 40-d interval(22). Season defined biomass nutritional quality. In L. leucocephala the foliage exhibited clearly higher protein levels (up to 8 percentage points) during the dry season. For M. maximus the dry season resulted in lower NDF and ADF contents. This was variable since in the rainy season the fiber fractions in this grass remained stable up to 40 ds and then increased significantly up to 50 d, while in the dry season fiber content gradually increased at longer intervals. The higher biomass nutritional quality in the dry season can be attributed to the fact that water deficit limits plant growth by retarding maturity. Less growth translates into less demand for cellular content metabolites to build structural tissue, maintaining NDF and ADF fractions more stable during the dry season(46). For example, M. maximus had a lower proportion of stems in its biomass in the dry season than in the wet season. There are also reports of higher protein concentrations and lower fiber fractions in the foliage of L. leucocephala(44,47,48) and grasses(49,50) in the dry season. Nutritional quality of L. leucocephala was not compared to M. maximus in the present study. However, the low digestibility of the L. leucocephala foliage coincides with previous reports(51,52) and has been attributed to greater lignification in trees. Although at the 50-d interval new L. leucocephala stems exhibited no signs of lignification, tree and bush branches require lignification to maintain their structure(45) and lignin content limits dry matter digestibility(53). In L. leucocephala this may also be related to the presence of condensed tannins(54) which can reduce dry matter digestibility by binding to protein, making it unavailable in the small intestine(55). Nonetheless, the growth habit and resource absorption strategies of trees allows them to maintain better nutritional quality for longer periods than in grasses(56). In silvopastoral systems these components can therefore complement each other to consistently produce forage of greater overall nutritional quality.

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Nutritional quality in the L. leucocephala studied here was similar to that reported for the same species (29 % CP, 49 % NDF, 23 % ADF and 59% IVDMD) at a 42-d interval(44), and at a 30-d interval in the dry season (30 % CP, 38 % NDF and 20% ADF)(48). Nutritional quality of the M. maximus was comparable to that of C. ciliaris at a 42-d interval (11 % CP and 48 % IVDMD)(48,56), and M. maximus at 45-d intervals during the northwinds season (11 % CP, 62 % NDF and 59 % IVDMD)(16).

Conclusions and implications Under the present study conditions the L. leucocephala-M. maximus association reached its highest production during the wet season at the 50-d interval. Nutritional quality decreased in M. maximus after 40 d while in L. leucocephala it remained largely unchanged up to 50 ds, regardless of season. Defining the optimal grazing point in a silvopastoral system such as this one requires quantification of the amount of available biomass and nutritional quality of both forage components. At 40 d M. maximus exhibited its highest nutritional quality, but total system forage biomass was 50 % lower than at 50 d. This means that, in terms of forage production, grazing is best done between 40 and 50 ds even though the M. maximus nutritional quality will be slightly lower within this interval. However, this nutrient shortfall is compensated for through the constant foliage quality of L. leucocephala. The forage biomass provided by the 5,000 ha-1 L. leucocephala density used in the present silvopastoral system is too low for practical purposes but could be changed by increasing sowing density.

Acknowledgements Thanks are due to Mr. José Barrera Morfin for allowing to his silvopastoral system and for support throughout the field phase of this research.

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https://doi.org/10.22319/rmcp.v11i1.5226 Article

Erythrina americana Miller foliage intake in Blackbelly x Pelibuey ewes

Diana Fabiola Hernández-Espinoza a Jesús Alberto Ramos-Juárez a Roberto González-Garduño b Luz del Carmen Lagunes-Espinoza a María Aurelia López-Herrera c Jorge Oliva-Hernández d*

Colegio de Postgraduados, Campus Tabasco. Tabasco, México.

Universidad Autónoma Chapingo, Unidad Regional Universitaria Sursureste. Tabasco, México. c

Instituto Nacional de Investigaciones Forestales, Agrícolas y Pecuarias, Campo Experimental Mocochá. Yucatán, México. d

Instituto Nacional de Investigaciones Forestales, Agrícolas y Pecuarias, Campo Experimental Huimanguillo. Km 1 Carretera Huimanguillo-Cárdenas, 86400. Tabasco, México.

*Corresponding author: olivajh20@yahoo.com.mx

Abstract: Legume tree foliage can be used as a supplement to grasses in some livestock species. A study was done of the influence that live weight category (LWC) in Blackbelly x Pelibuey ewes has on voluntary intake and digestibility of Erythrina americana foliage, productive efficiency, changes in blood variables and in the number of gastrointestinal nematode eggs per gram feces (EGF). The experimental design was completely random. The factors were

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LWC (light: 22.2 kg, heavy: 34.4 kg) and evaluation period (EP). Evaluated variables included live weight (LW), daily weight gain (DWG), in situ dry matter degradability (IDMD), daily dry matter intake (g kg-1 LW), crude protein (CP; g kg-1 LW), structural carbohydrates (SC; %), metabolizable energy (ME; Mcal kg-1 LW), condensed tannins (CT; g kg-1 BW) and EGF. Both LWC and EP affected (P<0.01) nutrient intake. The light LWC exhibited a higher nutrient and CT intake (P<0.01) than the heavy LWC, although without a commensurate increase in DWG. The blood variables and EGF were unaffected (P>0.05) by the studied factors and their interaction. Erythrina americana foliage CP, SC and CT contents suggest that it can be used as a sole feed source for short periods (less than 28 days). In both live weight categories E. americana intake produced a positive evolution in DWG and did not affect health status. Key words: Agroforestry trees, Intake, Hair sheep, Humid tropics.

Received: 18/01/2019 Accepted: 28/05/2019

Introduction The foliage of tree legumes contains a higher crude protein (CP) concentration than do creeping and bunch type tropical grasses(1). Incorporating tree legumes into sheep grazing systems is therefore recommended as a complementary CP source(2). For multiple reasons use of tree legume foliage in small ruminant feed systems is infrequent. Primary among them being a lack of knowledge of the presence and concentration of secondary compounds and the levels at which they can be included in sheep diets without affecting productive efficiency and animal health condition(3). Among forage tree legumes, the genus Erythrina stands outs because of its distribution in the tropics and subtropics, which facilitates acquisition of vegetative material for establishment and propagation(4,5). Coral tree Erythrina americana is widely used as a live fence on livestock farms in tropical regions, making it readily available for harvesting foliage for small ruminant feed(6,7). During the dry season, cattle in the tropics, mainly lactating cows and calves, are fed Erythrina foliage as a feed supplement. Foliage is collected from trees in pastures and live fences, and in some cases from cultivated orchards. It is freely supplied to animals as cut branches and as foliage in feed troughs(8).

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Studies of Erythrina inclusion in sheep diets have proven inconclusive. Some indicate that Erythrina foliage is easily consumed at up to 30 % inclusion(9,10), others report negative daily weight gain (DWG) (-20 g animal-1) at a 50 % inclusion level, and still others report a positive DWG (74 g animal-1) when Erythrina foliage is the sole feed(11,12). However, there is limited information on the productive behavior and health condition of sheep when fed E. americana foliage as the sole feed source(11), a promising option during short environmental contingencies (e.g. droughts). Previous studies of E. goldmanii indicate its foliage contains condensed tannins (CT)(9). No data is available to date on CT concentration in foliage from unpruned E. americana (very common in live fences), nor is their information on the CT intake tolerated in sheep when E. americana is the sole feed source(13). Understanding CT tolerance levels is vital because at concentrations greater than 50 g kg-1 dry matter (DM) this type of plant secondary metabolite can bind and precipitate soluble proteins and carbohydrates, negatively affecting DM degradability(14). However, consumption of CT-containing foliage can help control gastrointestinal nematodes in livestock(15). The present study objective was to quantify the influence of live weight category (LWC) in Blackbelly x Pelibuey sheep on voluntary intake and digestibility of E. americana foliage, productive performance, blood variables and gastrointestinal nematode egg counts in feces.

Material and methods Study area and housing

The study was done at the sheep experimental unit of the National Institute of Forestry, Agricultural and Livestock Research (Instituto Nacional de Investigaciones Forestales Agrícolas y Pecuarias - INIFAP), in Huimanguillo, Tabasco, Mexico (17°50’ N, 93°23’ W). Regional climate is warm humid with year-round rains [Af (m)] and a 27.8 °C average annual temperature(16). During the study period, minimum and maximum temperature was measured daily at 0800 h (24 hours) with a Six’s type thermometer. Weekly and general averages were calculated from this data: average minimum temperature was 23.0 ± 1.1 and average maximum was 35.5 ± 2.1 °C. The E. americana foliage was fed to sheep in individual pens with a 2.4 m2 area, a concrete floor, drinker, feed trough and asbestos sheet roof.

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Animal handling

Experimental animals were nine non-gestating, non-lactating Blackbelly x Pelibuey ewes distributed into two groups based on live weight category (LWC) and age. Four animals of two years of age were included in the light LWC (22.2 ± 1.2 kg LW), while five animals of three years of age were included in the heavy LWC (34.4 ± 1.1 kg LW). Prior to beginning the experiment each animal was injected with 1 ml ADE vitamins (Vigantol Bayer®) (500,000 IU vitamin A, 75,000 IU vitamin D, 50 mg vitamin E per ml). Animal management practices complied with established institutional guidelines (Reglamento para el Uso y Cuidado de Animales Destinados a la Investigación en el Colegio de Postgraduados, CP02.11.16). The experimental period was 42 days, including 14 d of adaptation to the diet and 28 d for the feeding trial. Initially, all the sheep were allowed to graze Cynodon plectostachyus pasture from 0800 to 1300 h after which each group was placed in a pen with free access to E. americana foliage (300 g sheep-1 d-1), water and mineral salts (Magnophoscal®, phosphorus 17.5 g; calcium 6.5 g; sodium 10.5 g; magnesium 4.5 g; sulfur 2.0 g). The grazing period was gradually reduced at a rate of one hour every two days until the sheep spent all day in the pen. The amount of E. americana foliage provided was increased by 100 g sheep1 day-1 until it became the sole feed source. During the 28-day feeding trial each animal was housed in an individual pen and provided free access to water and E. americana foliage from 0800 to 1800 h, supplied at a rate that resulted in at least 10% rejected feed. When the feeding trial ended all the light LWC sheep were housed in one pen and all the heavy LWC sheep in another. They were kept there overnight for safety, with free access to water and mineral salts.

Collection and chemical analysis of E. americana foliage

Foliage (leaves and petioles) collection was done during the late northwinds season and early dry season (February-March 2017). Collections were taken from trees with no history of pruning and which formed part of live fences marking sheep pastures. Pruning shears and a machete were used to remove branches and the foliage then removed from them. The collected foliage was dried by spreading in layers no thicker than 3 cm on a concrete floor under a roof at room temperature (28.2 ± 1.3 °C) for 72 h. It was turned over and mixed twice daily to improve drying.

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Evaluated variables

Data on chemical composition of and secondary metabolites in the foliage of E. americana was collected from foliage samples taken every week during the experimental period. Duplicate analyses were done of dry matter content (DM); ash; organic matter (OM) and crude protein (CP) using AOAC methods(17). Other techniques were used to quantify neutral detergent fiber (NDF) and acid detergent fiber (ADF)(18); in situ DM degradation (IDMD)(19), metabolizable energy (ME, Mcal kg-1 DM)(20), total polyphenols (g kg-1 DM), non-tannin phenols (g kg-1 DM)(21), condensed tannins (CT; g kg-1 DM), hydrolysable tannins (g kg-1 DM) and total tannins (g kg-1 DM)(22,23,24). The nylon bag technique used to quantify foliage IDMD(19), was implemented with three male cattle (Bos indicus x Bos taurus)(average LW = 500 ± 20 kg), that had been castrated and fitted with a rumen cannula. They were grazed in a pasture containing predominantly white gramalote grass (Paspalum fasciculatum) which provided 22.04 % DM, 6.73 % CP, 78.55 % NDF and 53.8 % ADF. This was supplemented with 2 kg of feed consisting of 70 % chickpea, 20 % rice polish and 10 % molasses (83.87% DM, 20.80 % CP, 28.43 % NDF and 7.42 % ADF). For the IDMD trial 5 g dry and ground E. americana foliage (Thomas-Willey mill, model 4 Laboratory Mill) was incubated in each rumen cannula with a 2 mm sieve, in polysilk bags (10 x 20 cm, 45µm porosity), in duplicate for 24 h. The bags were removed, washed with running water, and dried in a forced air oven at 105 °C for 72 h. Dry matter degradation was calculated with the formula: (g initial DM - g residual DM) / (g initial DM) X 100. Changes in live weight (LW) were quantified by weighing the sheep on two consecutive days at 14-d intervals during the feeding trial. A platform scale (Oken®) was used with 200 g accuracy. Daily weight gain (DWG) was calculated by the difference of final weight minus initial weight divided by the number of days in the experimental period. Foliage offered and rejected was weighed per pen weekly over three consecutive days. Weekly intake per pen was calculated by subtracting the quantity offered and that rejected. The foliage consumption index (%) was calculated at seven-day intervals for four periods by multiplying total DM intake by 100 and dividing by animal LW. Mineral salt intake was measured by weighing the salt offered and rejected per pen weekly over three consecutive days. Weekly intake per pen was calculated by subtracting the quantity offered and that rejected.

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Crude protein (CP), metabolizable energy (ME) and condensed tannins (CT) intake were calculated by multiplying total DM intake by foliage nutrient content and dividing by 100. Body condition (BC) was calculated at 14-day intervals during the feeding trial using a oneto-five scale(25). FAMACHAÂŠ monitoring was done based on ocular mucosa color as determined by the fivepoint FAMACHAÂŠ card color scale(26); intense red corresponds to a value of 1 (healthy) while white corresponds to a value of 5 (anemia = heavily infected). This evaluation was performed by the same person at the beginning and end of the feeding trial. Blood variables were measured by taking blood samples with the jugular vein puncture technique and collecting the blood in 4 ml vacutainer tubes containing EDTA. Blood collection was done at 0800 h on days 1 (beginning) 14 and 28 of the feeding trial. Blood samples were transferred to the laboratory for analysis in an automated hematology device (Medonic CA 620/530). The components analyzed included red blood cells (x1012 L), hemoglobin (g dl-1), hematocrit (%), mean red blood cell corpuscular volume (x 1015 L), white blood cells (x 109 L), lymphocytes (x 109 L) and granulocytes (x 109 L). Gastrointestinal nematode egg counts were done be taking fecal samples from each sheep at 0700 h at 14-day intervals throughout the experimental period. Each sample was collected directly from the rectum of each animal using a plastic bag and 2 g processed with the McMaster technique to determine egg count per gram of feces (EGF)(27).

Experimental design and statistical analysis

During the feeding trial (28 d) measurements were taken of the same animals at 7- and 14-d intervals, therefore evaluation period (EP) was considered an independent variable. An experimental two-factor design was used with repeated measures in one factor(28). The first factor was sheep LWC (light and heavy). The second factor was the EP (two 14-d periods to evaluate changes in LW, and four 7-d periods to evaluate changes in nutrient intake). The experimental unit was one sheep. Statistical analyzes were done with the SAS statistical package(29). Descriptive statistics (mean Âą standard deviation) were used to describe the values of E. americana foliage chemical composition, IDMD, DM, phenols and their fractions, as well as daily mineral salt intake. The Shapiro-Wilk test was applied to the remaining data to verify normal data distribution and the Levene test to confirm variance homogeneity. The EGF results were transformed with the natural logarithm (Log EGF +1) to provide them a normal distribution. 75

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The experimental unit was one sheep. Statistical analyzes of LW and total DWG were run with the GLM PROC. The PROC MIXED(30) was applied to identify the influence of EP, LWC and their interaction on DM, CP, ME and CT intakes, DWG, IDMD, EGF, and the blood variables. The means were compared with a Student t test and least mean squares using the pdiff option in SAS. The body condition (BC) and FAMACHA variables were analyzed with the Wilcoxon rank sum test for unpaired data(31).

Results and discussion The E. americana foliage results for chemical composition, IDMD, DM, phenols and their fractions showed it to be generally within reported ranges, although structural carbohydrates were higher than in previous studies (Table 1). The 18.9 % average CP value in the present results was within the 14.5 to 25.6 % range reported for E. americana foliage from a humid tropical region in the state of Tabasco, Mexico(2,32). The IDMD result (42.7 %) was also similar to the 42.7 % reported for E. americana foliage harvested during the dry season(32). However, structural carbohydrates content (71.6 % NDF, 56.7 % ADF) was higher than reported elsewhere (52.4% NDF, 40.1% ADF)(2). Increases in structural carbohydrates content is commonly associated with greater plant age. This coincides with the present study in which the foliage was harvested in the early spring when E. americana in the study area bloom and a significant proportion of leaves are mature(4); this would explain the high structural carbohydrate content, and low IDMD and DM values. Table 1: Chemical composition, in situ dry matter degradability (IDMD), metabolizable energy (ME), phenols and their fractions in Erythrina americana foliage Number of components

Component

Mean ± SD 84.9 ± 7.3

Dry matter (DM), %

Organic matter , %

90.2 ± 0.3

Crude protein , %

18.9 ± 1.8

Neutral detergent fiber, %

71.6 ± 3.2

Acid detergent fiber, %

56.7 ± 9.7

Ash, %

9.8 ± 0.3

IDMD, %

42.7 ± 3.1

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ME, Mcal kg-1 DM

1.45 ± 0.11

Total polyphenols, g kg-1 DM

17.27 ± 3.85

Non-tannin phenols, g kg-1 DM

0.80 ± 0.08

Condensed tannins, g kg-1 DM

5.77 ± 0.36

Hydrolysable tannins, g kg-1 DM

10.71 ± 3.84

Total tannins, g kg-1 DM

16.48 ± 3.80

Previous studies indicate that foliage contains phenolic compounds, including CT which can reduce IDMD and mitigate gastrointestinal nematodes infections in sheep(33). However, the CT content in E. americana observed in the present results (5.77 g kg-1 foliage DM) was less than half that reported for E. goldmanii (16.3 g kg-1 foliage DM)(9). Differences in Erythrina CT content can be attributed to harvest season, foliage age, species and foliage drying method(9,34). The relatively low foliage CT concentration in the present study can be partially attributed to the drying method since a delay in the drying process can allow enzymes in the plant to react with phenolic compounds(34). In intact plant tissue, phenolic compounds are found in vacuoles in free form or linked to carbohydrates. However, when the foliage is harvested and air dried, plant tissue dehydration begins which leads to cell membrane and organelles damage, releasing enzymes that can decompose phenolic compounds. For example, the enzymes peroxidase and polyphenol oxidase are located in the chloroplasts and when these are damaged they produce hydroxylation and oxidation of phenolic compounds, forming quinones and then dark pigments called melanins(35,36).

Dry matter and nutrient intake

No interaction (P>0.05) was found between the studied factors. The light LWC sheep exhibited higher DM, CP, ME and CT intakes than the heavy LWC sheep (Table 2). This higher nutrient intake in the light sheep can be attributed to their not yet having reached mature weight(37,38). Concentrations of CT greater than 5% in diet DM and the high effectiveness of CT in forming complexes with saliva proteins can reduce DM intake in sheep(33). However, no reduction in DM intake was observed, probably because the E. americana used in the present study had a low CT level.

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Table 2: Dry matter, crude protein, metabolizable energy and condensed tannins intakes by live weight category (LWC) in Blackbelly x Pelibuey sheep fed Erythrina americana foliage (means ± standard error) Variable

Intake index, % DM intake, g kg-1 LW CP intake, g kg-1 LW ME intake, Mcal kg-1 LW CT intake, g kg-1 LW

Factor LWC

** ** ** ** **

LWC LWC x EP ns ns ns ns ns

Light¥

Heavyφ

2.5a ± 0.1 24.7a ± 0.9 4.6a ± 0.2 0.036a ± 0.001 0.142a ± 0.005

1.9b ± 0.1 19.2b ± 0.8 3.6b ± 0.2 0.028b ± 0.001 0.111b ± 0.005

Each value is the average of four sheep; φ Each value is the average of five sheep; EP= evaluation period; LW= live weight; DM = dry matter; CP = crude protein; ME= metabolizable energy; CT= condensed tannins. ** Significant (P<0.01); ns= not significant. a,b Different letter superscripts in the same row indicate significant difference (P<0.01). ¥

The IDMD, and DM, nutrient and CT intakes increased up to the third week (Figure 1), after which nutrient intake remained constant. In a study of male Blackbelly sheep fed E. poeppigiana forage intake index was 3.5 %(11), which is higher than in the present results. Differences in IDMD between studies can be attributed to differences in Erythrina species chemical quality, sheep sex and breed(11,39). Another consideration is that when sheep are fed diets containing CT, feed intake may decline due to an astringent reaction to the feed associated with formation of CT-protein complexes and reduction in IDMD(33). This could at least partially explain the lower DM intake observed in the present study during the first two weeks of the trial. This response suggests that the sheep and their rumen reticulum microbes required a period of two weeks to adapt to the new diet. When sheep eat a diet containing CT their salivary glands produce proteins that bind to both CT and hydrolysable tannins, thus making them more tolerable(33,40). In addition, ruminants exposed to diets with CT can develop microbe populations with the ability to alter and degrade CT, thereby preventing the animal from experiencing reductions in DM intake and/or IDMD(33,41).

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Figure 1: Erythrina americana foliage intake (g DM kg-1 LW) during feeding trial in Blackbelly x Pelibuey sheep

abc

▲ Each value is the least mean square (± SE) of nine animals. Different lowercase letters indicate significant difference (Student t test), P<0.05.

Mean (± SE) daily mineral salt intake was 23.7 ± 1.1 g animal-1 in the light LWC sheep and 17.6 ± 2.1 g animal-1 in the heavy LWC sheep. Mineral salt intake stabilized in both groups between the second and fourth week (Figure 2). Ash content (<10 %) in the E. americana foliage (Table 1) was within ranges reported for E. americana foliage of different regrowth ages(2,13,32). Foliage from this tree legume has a lower ash content than tropical grasses such as C. nlemfuensis and Panicum maximum(42,43). Consequently, it is important to provide mineral supplementation to sheep fed E. americana. In addition, the CT present in legumes can form complexes with some minerals, reducing their availability(33). There are no studies to date on the mineral requirements of hair sheep under different feeding scenarios (grazing, penned)(44), but sheep fed E. americana exhibit higher mineral salt intake than hair sheep in a grazing system under a different feed supplementation regime(38,45,46). Differences between studies can be attributed at least in part to sheep LW, feed supplement level and composition, mineral salt composition and season.

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Figure 2: Mineral salt intake (g d-1 sheep-1) by live weight category in Blackbelly x Pelibuey sheep fed Erythrina americana

â&#x2013;˛ Each value is the average (standard errors) of four sheep. â&#x2014;? Each value is the average (standard errors) of five sheep.

Changes in live weight

Sheep LWC and the LCW/EP interaction did not affect (P>0.05) DWG. However, EP alone did affect (P<0.01) DWG, since it was lower at fourteen days than at 28 d (Figure 3). The negative DWG observed at 14 d was probably due to lower nutrient intake (Figure 1). At 28 d, however, DWG increased substantially, a response that can be attributed to higher nutrient intake and compensatory growth(47,48).

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Figure 3: Daily weight gain over time in Blackbelly x Pelibuey sheep fed Erythrina americana foliage

â&#x2013;˛ Each value is the mean square (Âą standard errors) of nine sheep. Different letters on the same line, indicate difference (test of "t"), P<0.01.

Total DWG, BC and FAMACHA index values were unaffected by LWC (Table 3). Total DWG in the present results was positive and higher than reported in male Pelibuey lambs fed Pennisetum purpureum and E. poeppigiana(12) but lower in growing Blackbelly male lambs fed only E. poeppigiana foliage. These differences in DWG between studies can be attributed to animal age, sex and breed(11).

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Table 3: Changes in live weight, body condition and FAMACHA index values by live weight category (LWC) in Blackbelly x Pelibuey sheep fed Erythrina americana foliage (means ± standard error). Variable

LWC Light¥ 24.1b, ± 1.1 25.2b ± 1.0 40.5 ± 21.6 2.8 ± 0.3 2.8 ± 0.3 3.2 ± 0.5 3.2 ± 0.5

Initial weight, kg Final weight, kg Total DWG, g Initial body condition Final body condition Intial FAMACHA Final FAMACHA ¥

Heavyφ 34.8a, ± 1.0 36.1a ± 0.9 47.3 ± 19.3 3.0 ± 0.0 3.0 ± 0.0 3.0 ± 0.0 3.0 ± 0.0

Each value is the average of four sheep; φ Each value is the average of five sheep. ab Different lowercase letters indicate significant difference (P<0.01).

Blood components

No interaction (P>0.05) was found between the studied blood components. Day number (i.e. 1, 14 and 28 d) only affected (P<0.05) hemoglobin and hematocrit levels. The general mean (± SD) was 8.1 ± 1.5 (x 1012 L) for red blood cells; 10.2 ± 1.6 (g dl-1) for hemoglobin; 25.1 ± 4.1 (%) for hematocrit; 31.2 ± 1.9 (x 1015 L) for mean red blood cell corpuscular volume; 10.2 ± 2.8 (x 109 L) for white blood cells; 7.3 ± 2.2 (x 109 L) for lymphocytes; and 1.0 ± 0.3 (x 109 L) for granulocytes. The least mean square (± SE) for hemoglobin (g dl-1) was 11.2a ± 0.5 at d 1, 10.1b ± 0.5 at d 14 and 9.4b ± 0.5 at d 28. For hematocrit they were 22.5b ± 1.3 at d 1, 26.6a ± 1.3 at d 14 and 26.9a ± 1.3 at d 28. The blood variable values observed in the present results are within the ranges reported for grazing hair sheep in tropical regions(49). Erythrina americana foliage intake levels during the four-week feeding trial maintained blood variables at levels appropriate for non-gestating, non-lactating sheep.

Gastrointestinal nematode eggs

None of the studied factors affected EGF (P>0.05), and the overall mean (± SD; unprocessed data) for EGF was 264 ± 670. Consumption of CT in the diet (15 % CT from Acasia molissima, based on DM) can reduce EGF in small ruminants(15,33), but the CT intake level in the present study was insufficient to detect any changes in EGF that could be attributed to 82

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LWC or EP. In addition, in the present study the sheep were fed E. americana in pens and were thus prevented from sustaining a natural nematode infection level, explaining in part the low EGF values.

Conclusions and implications Erythrina americana foliage can be used as the sole feed source in Blackbelly x Pelibuey sheep for short periods, as indicated by its CP, structural carbohydrates and CT contents, as well as voluntary intake levels. Live weight class (LWC) and EP number did affect nutrient and CT intake levels in that lighter sheep had higher nutrient and CT intake per kg LW than heavier sheep. However, over the 28-d feeding trial their higher nutrient intake did not result in greater increases in DWG in the lighter sheep than in the heavier sheep. In both live weight categories E. americana intake did not cause negative changes in their productive behavior and health status as quantified in DWG, blood variables and EGF. Erythrina americana should only be used as a sole feed source for short periods in response to environmental contingencies.

Acknowledgements

The principal author received financing through the Consejo Nacional de Ciencia y Tecnología (CONACYT) and financing for a Masters degree in the Programa de Producción Agroalimentaria en el Trópico (CPOS-PROPAT-CT-078/2016).

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34. FAO. Quantification of tannins in tree foliage. Vienna, Austria: Food Agricultural and Agricultural Organization/International Atomic Energy Agency; 2000 http://wwwnaweb.iaea.org/nafa/aph/public/pubd31022manual-tannin.pdf. Consultado 9 Sept, 2017. 35. Dicko MH, Gruppen H, Traoré AS, Voragen AGJ, van Berkel WJH. Phenolic compounds and related enzymes as determinants of sorghum for food use. Biotechnol Mol Biol Rev 2006;1(1):21-38. 36. Morante CJ, Agnieszka OA, Bru-Martínez R, Carranza PM, Pico-Saltos R, Nieto RE. Distribución, localización e inhibidores de las polifenol oxidasas en frutos y vegetales usados como alimento. Ciencia y Tecnología 2014;7(1):23-31. 37. Dzib CA, Ortiz de Montellano A, Torres-Hernández G. Variabilidad morfoestructural de ovinos Blackbelly en Campeche, México. Arch Zootec 2011;60(232):1291-1301. 38. Zamora-Zepeda R, Oliva-Hernández J, Hinojosa-Cuéllar JA. Complementación energética y proteínica en corderas Blackbelly x Pelibuey en pastoreo. Nova Scientia 2015;7(15):245-264. 39. Lewis RM, Emmans GC. Feed intake of sheep as affected by body weight, breed, sex, and feed composition. J Anim Sci 2010;88:467-480. 40. Ventura-Cordero J, Pech-Cervantes A, Sandoval-Castro CA, Torres-Acosta JFJ, González PPG, Sarmiento FLA. Relación herbívoro-tanino: adaptación de ovinos y caprinos a la vegetación rica en taninos de la península de Yucatán. Bioagrociencias 2013;6(1):19-25. 41. Smith AH, Zoetendal E, Mackie RI. Bacterial mechanisms to overcome inhibitory effects of dietary tannins. Microb Ecol 2005;50(2):197-205. 42. Juárez RAS, Cerrillo SMA, Gutierrez OE, Romero TEM, Colín NJ, Bernal BH. Estimación del valor nutricional de pastos tropicales a partir de análisis convencionales y de la producción de gas in vitro. Tec Pecu Mex 2009;47(1):55-67. 43. Villalobos L, Arce J. Evaluación agronómica y nutricional del pasto Estrella Africana (Cynodon nlemfuensis) en la zona de monteverde, Puntarenas, Costa Rica. II Valor nutricional. Agron Costarricence 2014;38(1):133-145. 44. Oliva HJ. Crecimiento y desarrollo postdestete de corderas de razas de pelo. Explotación en pastoreo y con complementación alimenticia en regiones tropicales. Saarbrücken, Alemania: Editorial Académica Española; 2012.

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45. Pascual-Córdova A, Oliva-Hernández J, Hernández-Sánchez D, Torres-Hernández G, Suárez-Oporta ME, Hinojosa-Cuéllar JA. Crecimiento postdestete y eficiencia reproductiva de corderas Pelibuey con un sistema de alimentación intensiva. Arch Med Vet 2009;41:205-212. 46. Cadenas JA, Oliva-Hernández J, Hinojosa JA, Torres-Hernández G. Suplementación alimenticia durante el crecimiento post destete de corderas Pelibuey x Blackbelly en pastoreo en el trópico húmedo de México. Arch Zootec 2010;59(226):303-306. 47. Lawrence TLJ, Fowler VR. Growth of farm animals. 2nd ed. NY, USA: CABI Publishing; 2002. 48. Manni K, Rinne M, Joki-Tokola E, Huuskonen A. Effects of different restricted feeding strategies on performance of growing and finishing dairy bulls offered grass silage and barley based diets. Agr FSci 2017;26:91-101. 49. Bezerra LR, Oliveira WDC, Silva TPD, Torreão JNC, Marques CAT, Araújo MJ, et al. Comparative hematological analysis of Morada Nova and Santa Inês ewes in all reproductive stages. Pesq Vet Bras 2017;37(4):408-414.

https://doi.org/10.22319/rmcp.v11i1.5083 Article

Pasture structure and sheep performance supplemented on different tropical grasses in the dry season

Leonardo Santana Fernandes a Gelson dos Santos Difante b Marcone Geraldo Costa a João Virgínio Emerenciano Neto c Itânia Maria Medeiros de Araújo b Joederson Luiz Santos Dantas a Antonio Leandro Chaves Gurgel b*

Federal University of Rio Grande do Norte. Academic unit specializing in agricultural science. Rodovia RN106 - km 03, District of Jundiaí- 59280000. Macaíba, Rio Grande do Norte, Brazil. b

Federal University of Mato Grosso do Sul. Faculty of Veterinary Medicine and Animal Science. Campo Grande, Mato Grosso do Sul, Brazil. c

Federal University of Vale do São Francisco. Campus of Agricultural Sciences. Petrolina, Pernabuco, Brazil.

*Corresponding author: antonioleandro09@gmail.com

Abstract: The objective was to evaluate the productive and structural characteristics of tropical grasses and the performance of sheep supplemented during the dry season. The treatments consisted of Marandu, Piatã, Massai and Aruana cultivars managed under intermittent stocking with seven occupation days and 35 d of rest, with a variable stocking rate. The evaluated variables were the forage masses, the morphological components, the chemical composition of the pasture and sheep performance. The forage mass was similar among the cultivars, while the leaf blade mass and percentage were higher in the Massai cultivar. There were differences between the cultivars for the NDF, ADF, ADL and ash contents in the two grazing cycles. The lowest gains per 89

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animal and gain per area were observed in the Aruana grass pastures, while there were no differences for these variables among the other cultivars. Massai, Marandu and PiatĂŁ cultivars can be used as a forage option for the dry period when associated with protein supplementation for sheep being raised for meat. Key words: Brachiaria, Panicum, Livestock production.

Received: 28/09/2018 Accepted: 28/01/2019

Introduction Sheep breeding may be a promising alternative for livestock production in pastures, as complete usage of cultivated pastures is not a common practice in; there is no pasture cultivation on most of the properties, and native pasture with practically no pasture management is the main forage source(1). Introducing production systems in cultivated pastures can increase the productive capacity of the properties and result in a substantial increase in the profitability of the agricultural activities and will favor the permanence and the improvement in the quality of life of farmers. Grasses of the Brachiaria and Panicum genus are among the most used forages in animal production systems in countries of tropical climate due to their adaptation to tropical and subtropical climates and high productivity(2). In spite of this, forage mass aging in the dry season can reduce the leaf supply and crude protein content and increase the fiber content, compromising animal performance(3,4). Studies on forage supply and their effects on defoliation intensity are scarce in tropical forage grasses in the time of scarcity of water resources(5). The dynamics of defoliation can aid in the understanding of plant and animal interaction; there is a conceptual basis for the causal relationships between pasture structural characteristics and forage consumption(6), characterizing in terms of frequency, plant defoliation severity in the pasture ecosystem(7;8), being related to the spatial distribution of biomass among grazing areas. In view of this, animal performance in pasture is not uniform during the year, which justifies searching for adapted tropical grasses that are able to minimize the adverse effects of the dry season on pasture animal production when they are associated with supplementation. Therefore, identifying and implementing forage plants with greater support capacity and those enable greater weight gain can result in greater efficiency in the animal production system in pasture.

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Based on the above, the objective was to evaluate the productive and structural characteristics of tropical forages of the Brachiaria and Panicum genera under grazing and the performance of sheep supplemented during the dry season.

Material and methods Site, treatments and experimental design

The experiment was carried out at the Experimental Area of the Forage Research Group (GEFOR) of the Federal University of Rio Grande do Norte - UFRN, in Macaíba/RN, located at 5° 53' 34'' S and 35° 21' 50'' W and 50 m of altitude. The experimental period was 84 d (10/24/2011 to 01/16/2012), characterized as the dry period of the year. According to Thornthwaite’s climate classification(9), the region’s climate is dry sub-humid with water surplus from May to August. The annual average historical precipitation is 1,048 mm and potential annual cumulative evapotranspiration of 1,472 mm. the precipitation during the experiment was 33 mm. Rainfall data were obtained using a stainless steel Ville de Paris rain gauge installed at the site. The area’s fertility was estimated by soil analysis, then 80 kg ha-1 of P2O5 and 50 kg/ha of K2O in order to raise the base saturation by around 60 %, phosphorus content between 8 and 12 mg dm3 (P-Mehlich1) and potassium content between 80 and 100 mg/dm3, while 100 kg/ha of N as ammonium sulfate was also applied in two post-grazing applications between April and June 2011. The pastures were implanted in June 2010. Sowing was done with the sowing, and the sowing density considered the recommendation for each cultivar and the CV% (cultural value) of the seeds used. Four tropical forage grasses were evaluated: Marandu and Piatã (Brachiaria brizantha cv.) and Aruana and Massai (Panicum maximum cv.) The experimental area of 2.88 ha was divided into two blocks of 1.44 ha, with four modules of 0.36 ha for each cultivar, which was subdivided into six peaks of the same area (0.06 ha). In the rainy season preceding the experiment (01/01/2011 to 09/30/2011), the pastures were grazed by sheep managed under intermittent stocking(10) with pre-grazing height goal of 50 cm and post-grazing of 25 cm, so that approximately 50 % of the available mass was removed(11). In the dry period the pastures were managed under rotational stocking with seven occupation days and 35 d of rest, with variable stocking rate. The adjustment of the stocking rate was done weekly according to the forage mass, maintaining at least six test animals per experimental plot.

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Forage mass

All evaluations in the pastures were performed immediately before the animals entered the pasture (pre-grazing) and in the post-grazing period after the animals exited from the paddock. The pasture height was measured using a one-meter ruler graduated in centimeters, in 40 representative points paddock. The canopy height at each point corresponded to the average height of the leavesâ&#x20AC;&#x2122; curvature around the ruler. The forage mass (FM) was obtained by cutting output to the forage soil contained in four representative areas in four paddock of each module, a metal frame 1 m long by 0.5 m wide (0.5 mÂ˛ of area). The collected samples were identified and weighed to obtain the green weight. To evaluate the dry forage mass, approximately 50 % of the green mass collected from each sample was packed in paper bags and dried in a forced air ventilation oven at 55 ÂşC for 72 h, then they were reweighed.

Morphological composition

For evaluating the morphological components of the pasture in the pre-grazing, the four collected samples (after removal of the subsamples to determine the dry mass) constituted two composite samples. The composite samples were manually separated into leaf blade, stem (stem + sheath) and dead material to determine the masses and percentages of participation of each component in the pasture structure. The quotient between leaf blade mass and stem mass was obtained to determine the leaf:stem ratio. Post-grazing forage harvesting and the respective evaluations of the morphological components, the leaf:stem and green:dead material ratios occurred in a manner similar to pre-grazing.

Nutritive value

Whole plant subsamples were used to evaluate the chemical composition, ground in a Wiley mill with a 20 mesh screen and later analyzed for crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF), acid detergent lignin (ADL) and ash (ASH), using methodologies described by AOAC (1995)(12).

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Animal live weight gain and stocking rate

Thirty-two (32) male Santa Inês breed sheep with an initial mean live weight of 26.57 ± 4.05 kg were used, with four animals distributed per module. They went through a period of 7 d of adaptation to concentrate and handling. The animals were kept in the pasture during the daytime period (0730 to 1630 h) and were collected from a covered sheepfold to be supplemented and kept at night. Protein supplementation (39.1 % corn in milled grain, 30.0 % cotton cake, 25.1 % soybean meal, 3.0 % mineral supplement and 2.8 % of livestock urea) was formulated according to recommendations of the NRC (1985)(8) for gains of 150 g/d, with the amount being offered to the animals adjusted weekly according to the weight obtained at each weighing, were supplied an amount of 1.38 % of PV concentrate (with DM base). The bays had an area of 9 m2 and were equipped with a feeder, water fountain and salt lick. The average daily weight gain (g day-1) was monitored weekly and calculated by the difference in the weight of the animals at the beginning and end of the experiment divided by the grazing days. The stocking rate (animals 30 kg ha-1) was calculated by dividing the mean animal load values of the grazing period by 30 to express in animal units of the category used per hectare. The average weight gains per area (kg day ha-1) was obtained by multiplying the average daily gain of the test animals by the number of animals kept per hectare during the experimental period.

Statistical analysis

The experimental design was a randomized complete block (RCB), the data were submitted to analysis of variance and the means were compared by the Tukey test, adopting a 5% level of significance. The following model was used for the forage variables: Yijk=μ+Fi+Ij+FIij+Ck+eijk in which: Yijk = observed value of cultivar i and cycle j in the block k; μ = general constant (population mean); Fi = effect of cultivar i, i= 1, 2, 3, 4; Ij= effect of cycle j, j= 1, 2; FIij = interaction of cultivar i and cycle j; Ck = effect of block k, k= 1, 2; eijk = random error associated with each observation Yijk(13).

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For the variables evaluated in the animals, the model: Yijk=μ+Fi+Cj+eijk in which: Yijk = observed value of the cultivar i in block j in the repetition k; μ = general constant (population mean); Fi = effect of the cultivar i, i= 1, 2, 3, 4; Cj = effect of the block j, k = 1, 2; eijk = random error associated with each observation Yijk(13).

Results and discussion There was interaction between cultivar and cycle for all structural variables of pasture in the pre-grazing (P<0.05), except for the stem mass. The highest heights in the first cycle were observed in the Massai cultivar, and the highest pasture height in the second grazing cycle was observed in the Marandu cultivar (Table 1). Table 1: Grass structure in Brachiaria brizantha and Panicum maximum pastures at pregrazing Marandu Piatã Aruana Massai SEM Variables Cycle 1 1.6 Canopy height, cm 30.3Bb 31.6Ab 32.2Ab 39.5Aa Total forage mass, kg/ha DM 4689.2Aab 3728.1Aab 2775.5Ab 5706.8Aa 549.6 Leaf blade mass, kg/ha DM 376.0Abc 535.4Ab 79.8Ac 1170.1Aa 80.4 Stem mass, kg/ha DM 821.0Aa 931. 0Aa 1024.4Aa 552.0Aa 162.9 Dead material mass, kg/ha DM 3492.2Aab 2022.2Aab 1671.3Ab 3984.8Aa 447.6 Leaf blade/Stem ratio 0.5Ab 0.6Ab 0.1Ab 2.4Aa 0.2 Cycle 2 Canopy height, cm 37.1Aa 34.5Aab 30.0Ab 32.2Bb 1.6 Aa Aa Aa Aa Total forage mass, kg/ha DM 3584.4 3288.0 2005.3 4569.5 549.6 Ab Bb Ab Ba Leaf blade mass, kg/ha DM 222.4 154.9 0.0 611.1 80.4 Aa Aa Aa Aa Stem mass, kg/ha DM 576.0 737.2 829.8 504.2 162.9 Aab Aab Ab Aa Dead material mass, kg/ha DM 2786.0 2396.0 1775.4 3454.2 447.6 Aab Aab Ab Ba Leaf blade/Stem ratio 0.4 0.2 0.0 1.2 0.2 SEM= standard error of the mean. Means followed by lower case letters in the row (cultivars) and upper case in the column (cycles) differ by the Tukey test (P<0.05).

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The largest forage mass was observed in the Massai cultivar and the lowest in Aruana, not differing from the Marandu and Piatã cultivars; this result can be explained by the high population density of Massai cv. tillers(14), as Massai cv. produced greater forage mass during the rainy season when compared to the others(15), and the structural characteristics of the canopy in the dry season reflect the responses observed in the higher forage production season(16). When evaluating Mombasa grass and Massai pastures grazed by cattle, Euclides et al(17) observed higher total forage mass in the Massai cultivar in relation to Mombaça guinea grass in pregrazing condition. This shows the high productive potential of this cultivar even in conditions of water stress. Fernandes et al(18) point out that this cultivar is an excellent alternative for sheep production systems supplemented in pastures during the dry season. The lowest forage mass and the morphological constituents of Aruana cv. can probably be explained by the higher requirement in fertility and water than the other cultivars, which characterizes less drought tolerance(19). The highest leaf blade mass (LBM) was observed in Massai cv., (P<0.05). being 67, 54 and 93 % higher than the Marandu, Piatã and Aruana cultivars, respectively, in the first grazing cycle. Even with lower LBM in the second cycle compared to the first (P<0.05), this cultivar was higher in 63, 74 and 100 % in relation to the Marandu, Piatã and Aruana cultivars, respectively, indicating a more favorable condition for grazing on Massai cv., since the leaf blade is the component with greater nutritional value in detriment to the others (Table 1). The stem mass (SM) did not differ between cultivars (P<0.05) with a mean of 746.9 kg/ha DM. The absence of effect for SM is a reflection of the low elongation rate of this component in the grasses of the Brachiaria brizantha and Panicum maximum species during the dry season(20). The dead material mass (DMM) was similar among the Massai, Marandu and Piatã cultivars, but when compared to Aruana cv., the Massai cultivar presented 88 % more DMM in the first grazing cycle. The high DMM in Massai cv. may have been a result of higher forage production of Massai cv. during the rainy season that preceded the experiment(9), which senesced during the dry period and resulted in higher DMM. For Gurgel et al(16), the amount of dead material in the dry period is influenced by the forage mass produced during the rainy period. The leaf blade:stem (LB/C) ratio was higher (P<0.05) in the Massai cultivar in the first grazing cycle which was due to the Massai cultivar having presented the highest LBM, and there was no difference between the cultivars for SM. There were no differences between the Brachiaria cultivars and the Massai cultivar in the second cycle, with only the Aruana cultivar showing a lower value since this cultivar had no leaf blades in its morphological composition in the second grazing cycle. The leaf blade/stem ratio is a variable of great importance for managing forage plants due to the fact that it is associated with the ease with which the animals harvest the preferred forage (leaves). The values found were higher than 1.0 for Massai cv. (Table 2), characterizing favorable conditions to grazing in this cultivar, even in the dry season of the year. Values lower than one, imply a fall in the quality of fodder offered(19).

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Post-grazing canopy height did not differ between forages or between cycles (P>0.05), with a mean value of 30.3 cm (Table 3). There were no significant differences (P>0.05) in post-grazing for TFM, SM and DMM, indicating that regardless of the cultivar, SM and DMM may have been a physical barrier to lower canopy height(3), since there was only a 10% reduction in the pre-grazing canopy height (Table 2) to that of post grazing. Table 2: Grass structure in Brachiaria brizantha and Panicum maximum pastures at in postgrazing Marandu Piatã Aruana Massai SEM Variables Cycle 1 1.5 Canopy height, cm 29.6Aa 29.3Aa 30. 9Aa 30.6Aa Aa Aa Aa Aa 633.2 Total forage mass, kg/ha DM 4676.4 2650.5 3104.7 4645.5 Ab Ab Ab Leaf blade mass, kg/ha DM 175.4 96.8 33.0 547.7Aa 52.5 Stem mass, kg/ha DM 790.9Aa 554.3Aa 1453.7Aa 513.4Aa 217.5 Dead material mass, kg/ha DM 3710.2Aa 1866.5Aa 1617.9Aa 3584.3Aa 473.0 Leaf blade/Stem ratio Canopy height, cm Total forage mass, kg/ha DM Leaf blade mass, kg/ha DM Stem mass, kg/ha DM Dead material mass, kg/ha DM Leaf blade/Stem ratio

0.2Ab Cycle 2 29.8Aa 3454.1Aa 23.5Ab 636.1Aa 2794.6Aa 0.0Ab

0.2Ab

0.0Ab

1.1Aa

0.3

31.5Aa 2194.0Aa 0.0Ab 425.9Aa 1768.1Aa 0.0Ab

30.7Aa 2294.9Aa 0.0Ab 1031.4Aa 1263.5Aa 0.0Ab

30.1Aa 4032.3Aa 458.7Aa 570.9Aa 3002.6Aa 0.9Aa

1.7 708.0 58.7 243.2 528.8 0.1

SEM= standard error of the mean. Means followed by lower case letters in the row (cultivars) and upper case in the column (cycles) differ by Tukey’s test (P<0.05).

Massai cv. obtained higher LBM in post-grazing in relation to the other cultivars in the two grazing cycles, which in turn showed no differences between them. This can be explained by the fact that there was a greater amount of LBM in the Massai cultivar in the pre-grazing period (Table 1), and the initial stocking rate was not enough to promote the harvest of this constituent in the same proportion as in the Marandu, Aruana and Piatã cultivars (Table 2). The highest LB/S ratios were observed in the Massai cultivar due to the higher LBM in comparison to the other cultivars, since there was no difference in the SM, but the LB/S ratio values were extremely low, except for those of the Massai cultivar in the first cycle. There was no difference between cultivars for crude protein (CP) contents in the first grazing cycle, but there was a significant (P<0.05) effect among cultivars in the second cycle. This result is associated to the reduced leaf blade participation in the forage mass of this cycle, as this component is the one with the highest CP content. All observed values were below the 7 % value considered critical(21),

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Table 3: Chemical composition of Brachiaria brizantha and Panicum maximum pastures in pre-grazing (%) SEM Marandu PiatĂŁ Aruana Massai Variables (%) Cycle 1 0.3 Crude protein 3.3Aa 3.6Aa 4.7Aa 3.8Aa 1.0 Neutral detergent fiber 76.9Aab 73.2Abc 71.8Ac 79.3Aa 0.8 Acid detergent fiber 44.5Aab 40.7Ab 46.3Aa 46.3Ba 0.5 Acid detergent lignin 8.0Aab 7.5Ab 10.4Aa 8.5Aab 0.3 Ash 4.4Ab 5.0Ab 7.2Aa 5.8Ab Cycle 2 Crude protein Neutral detergent fiber Acid detergent fiber Acid detergent lignin Ash

3.3Aab 77.5Aab 45.9Abc 8.8Ab 4.1Ab

3.0Ab 72.6Ac 43.6Ac 9.0Ab 4.8Ab

4.6Aa 74.1Abc 49.0Aab 11.7Aa 6.7Aa

3.1Ab 79.6Aa 50.8Aa 10.5Aab 4.8Ab

0.3 1.0 0.8 0.5 0.3

SEM= standard error of the mean. Means followed by lower case letters in the row (cultivars) and upper case in the column (cycles) differ by Tukeyâ&#x20AC;&#x2122;s test (P<0.05).

The highest NDF values were observed in the Massai cultivar in the two grazing cycles (Table 3), the lowest values in the Aruana cv., and intermediate values in the other cultivars in the two grazing cycles. According to Batistotti et al(21), the epidermis of the Massai cultivar is very secure to the rest of the leaf by a thick-walled cell support formed by the sclerenchyma and a vascular bundle of sheath cells (girder structure), where Massai grass presents higher frequency of the girder structure, being one of the probable causes for the greater participation of the NDF fraction. The highest ADF values were observed in the Massai cultivar in the second grazing cycle, but there was no difference in the first cycle between the Massai and Aruana cultivars, while intermediate ADF values were observed in the Marandu grass. The ADF is within the NDF fraction, and as the Massai grass presented higher NDF content, higher ADF values were expected. On the other hand, a greater stem and dead material mass was observed in the Aruana cultivar; these components are rejected, resulting in a decrease in the cellular content and increase in the cellular wall(22). The highest lignin levels were observed in the Aruana cultivar in the two grazing cycles and intermediate values in the Massai cultivar. This may be related to the fact that the chemical analysis was carried out on the whole plant, and the Aruana grass pastures presented higher amounts of stem, being the component with greater cell wall thickening, thus raising the lignin forage content.

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Although the Massai cultivar obtained higher structural fraction values and these fractions could lead to limitations in consumption and performance of the animals(3,4) in the dry period of the year, what determines the animal performance the most is the amount of forage available for grazing, with the pasture being primarily used for attending base fiber requirements. There was no difference between the cultivars for the final weight of the animals, with a mean of 32.4 kg (Table 4). The lowest average daily gain (ADG) was observed in sheep kept in Aruana grasses. No differences were observed between the animals kept in the Marandu and Piat達 cultivars, and intermediate ADG values were observed in the animals kept in the Massai pasture. The lower performance observed in the Aruana cultivar can be explained by the lower leaf blade mass in the first cycle of grazing and absence of leaf blades in the second cycle, being the constituent of greater preference by the animals and which has higher nutritional value.

Table 4: Sheep performance in pastures of of Brachiaria brizantha and Panicum maximum Variables Marandu Piat達 Aruana Massai SEM a a Final weight, kg 34.7 31.9 29.5a 34.0a 3.8 Average daily weight gain, g/d

133.7a

142.0a

82.1b

122.4ab

1.9

Stocking rate, UA/ha

8.9ab

5.4b

6.4b

9.6a

1.0

Gain by area, g/ha/d ab

1189.9

766.8

525.4

1175.0

73.4

M SEM= standard error of the mean. Means followed by distinct letters differ from each other by the Tukey test (P<0.05).

The stocking rates in the Massai and Marandu cultivars were higher than in the Aruana cultivar (P<0.05). This result can be attributed to the higher forage mass and leaf blade mass of these cultivars in pre-grazing (Table 3). In addition, there was not enough forage to keep animals in the Aruana cultivar during the last 35 d of the experiment, so a zero stocking rate was used in this period. This leads to confirm the lack of aptitude by this cultivar for livestock production in pasture in the dry period without using irrigation. The live weight gain per hectare was lower in the Aruana grasses when compared to the Marandu and Massai cultivars, and these did not differ from the Piat達 cultivar. This result can be attributed to the lower ADG and stocking rate observed in the Aruana cultivar, since pasture productivity is a result of the combination of individual performance and stocking rate for each situation(3,4). Piat達 cultivar presented a lower stocking rate than those of the Massai and Marandu pastures; however, the individual gain compensated for this difference, with a reflection observed in the area gain, since the weight gain per area is the product of the stocking rate for the individual gain.

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Conclusions and implications Pastures are recommended as Massai, Marandu and Piatã cultivars can be used as a forage option associated with protein supplementation for producing sheep raised for meat in the dry period of the year, because they present more adequate structures for sheep grazing, which reflected in higher animal productivity.

Conflict of Interest and Acknowledgements The authors certify that they have no affiliations with any organization or entity with any financial or non-financial interest in the subject matter or materials discussed in this manuscript. This research was funded by the Coordination for the Improvement of Higher Education Personnel - Brazil (CAPES) - Financing Code 001 and the National Council for Scientific and Technological Development (CNPq) and supported by the Federal University of Rio Grande do Norte e Federal University of Mato Grosso do Sul.

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Emerenciano Neto JV, Bezerra MGS, França AF, Assis LCSLC, Difante GS. A agricultura familiar na cadeia produtiva de carne ovina e caprina no semi-árido. R Bras Agr Sust (RBAS) 2011;(2):1-5.

Gomes RA, Lempp B, Jank L, Carpejani GC, Morais MG. Características anatômicas e morfofisiológicas de lâminas foliares de genótipos de Panicum maximum. Pesq Agropec Bras 2011;46(2):205-211.

Euclides VPB, Macedo MCM, Valle CB, Difante GD, Barbosa RA, Cacere ER. Valor nutritivo da forragem e produção animal em pastagens de Brachiaria brizantha. Pesq Agropec Bras 2009;44(1):98-106.

Difante GS, Euclides VPB, Nascimento Júnior D, Da Silva, SC Barbosa RA, Torres Júnior RAA. Desempenho e conversão alimentar de novilhos de corte em capim-tanzânia submetido a duas intensidades de pastejo sob lotação rotativa. Rev Bras Zootec 2010;39(1):33-41.

Braga GJ, Pedreira CGS, Herling, VR, Luz PHC. Eficiência de pastejo de capim-marandu submetido a diferentes ofertas de forragem. Pesq Agropec Bras 2007;42(11):1641-1649.

HODGSON, J. The significance of sward characteristics in the management of temperate sown pastures. International Grassland Congress. 1985:63-66.

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Fonseca L, Mezzalira JC, Bremm C, Gonda HL, Carvalho, PDF. Management targets for maximizing the short-term herbage intake rate of cattle grazing in Sorghum bicolor. Livest Sci 2012;145(1):205-211.

Mezzalira JC, Carvalho PCDF, Fonseca L, Bremm C, Cangiano C, Gonda HL, Laca EA. Behavioural mechanisms of intake rate by heifers grazing swards of contrasting structures. App Anim Beh Sci 2014;153(1):1-9.

Thorthwaite CW. An approach toward a rational classification of climate. Geog Rev 1948; 38:55-93.

10. Allen VG, Batello C, Berretta EJ, Hodgson J, Kothmann M, McIvor X. Li J, Milne J, Morris C, Peeters A, Sanderson M. An international terminology for grazing lands and grazing animals. Grass Forage Sci 2011;66:2–28. 11. NRC. National Research Council. The nutrient requirements of sheep. Washington, DC, USA: National Academy Press; 1984. 12. AOAC. Oficial methods of analysis. 15th ed. Arlington, VA, USA: Association of Official Analytical Chemists. 1990. 13. Euclides VBP, Carpejani GC, Montagner DB, Nascimento Junior D, Barbosa RA, DIfante GS. Maintaining post-grazing sward height of Panicum maximum (cv. Mombaça) at 50 cm led to higher animal performance compared with post-grazing height of 30 cm. Grass Forage Sci 2017;73(1):174–182. 14. Lopes MN, Cândido MJD, Pompeu RCFF, Silva RG, Bezerra FML Componentes estruturais do resíduo pós-corte em capim-massai adubado com cinco doses de nitrogênio. Rev Ciên Agr 2011;42(2):518-525. 15. Emerenciano Neto JV, Difante GS, Aguiar EM, Fernandes LS, Oliveira HCB, Silva MGT. Performance of meat sheep, chemical composition and structure of tropical pasture grasses managed under intermittent capacity. Biosci J 2014;30(3):834-842. 16. Gurgel ALC, Difante GS, Emerenciano Neto JV, Souza JS, Veras ELL, Costa ABG, et al. Estrutura do pasto e desempenho de ovinos em capim-massai na época seca em resposta ao manejo do período das águas. Bol Ind Anim 2017;74(2):86-95. 17. Euclides VPB, Macedo MCM, Zimmer AH, Jank L, Oliveira MP. Avaliação dos capins mombaça e massai sob pastejo. Rev Bras Zootec 2008;37(1):79-86. 18. Fernandes LS, Difante GS, Montagner DB, Emerenciano Neto JV, Araújo IMM, Campos NRF. Structure of massai grass pasture grazed on by sheep supplemented in the dry season. Grassl Sci 2017;63(3):177-183. 19. Costa KAP, Oliveira IPO, Faquin V, Neves BPN, Rodrigues C, Sampaio FMT. Intervalo de corte na produção de massa seca e composição químico-bromatológica da Brachiaria brizantha cv. mg-5. Ciênc Agrotec 2007;31(4):1197-1202. 100

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20. Luna AA, Difante GS, Montagner DB, Emerenciano Neto JV, Araújo IMM, Oliveira LEC. Características morfogênicas e acúmulo de forragem de gramíneas forrageiras, sob corte. Biosci J 2014;30(6):1803-1810. 21. Batistoti C, Lempp B, Jank L, Morais MG, Cubas AC, Gomes RA, Ferreira MVB, Correlations among anatomical, morphological, chemical and agronomic characteristics of leaf blades in Panicum maximum genotypes. Anim Feed Sci Tech 2012:71:173–180. 22. Paula CCL, Euclides VPB, Montagner DB, Difante GS, Carloto MN. Estrutura do dossel, consumo e desempenho animal em pastos de capim-marandu sob lotação continua. Arq Bras Med Vet Zootec 2012; 64(1):169-176.

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https://doi.org/10.22319/rmcp.v11i1.4757 Article

In vitro production of porcine embryos with use of chemically semi-defined culture media system

David Urbán Duarte a Horacio Álvarez Gallardo a Sandra Pérez Reynozo a José Fernando De la Torre Sánchez b*

Instituto Nacional de Investigaciones Forestales, Agrícolas y Pecuarias (INIFAP), Centro Nacional de Recursos Genéticos. Blvd. de la Biodiversidad Nº 400, Tepatitlán de Morelos, Jalisco. CP 47600, México. b

INIFAP, oficinas centrales. Ciudad de México, México.

*Corresponding author: delatorre.fernando@inifap.gob.mx

Abstract: The objective of this study was to determine the effect of a semi-defined culture media system developed in laboratory, named Pigs Media System (PMS) on the in vitro production of porcine embryos. In a first assay, the cummulus-oocytes complexes (COCs) were matured, fertilized and cultured for embryo development in PMS supplemented with bovine serum albumin (BSA), and in North Carolina State University-23 (NCSU-23) supplemented with follicular fluid, until blastocysts evaluation. In the assay 2, maturation and culture were performed in PMS using BSA or polyvinyl alcohol (PVA) in a 2 × 2 factorial arrangement (PMS-BSA/BSA, PMS-BSA/PVA, PMS-PVA/PVA, PMS-PVA/BSA). The PMS had a positive effect on the total cell number (58.04) and the decrease of the total lipids (49.4 %) regarding the NCSU-23 medium (37.98 and 59.2 % respectively; P<0.05). The percentage of monospermic fertilization was significantly lower (42.3 %; P<0.05) when oocytes were matured with PMS-BSA than in PMS-PVA (52.6 %). The supplementation of BSA in the PMS for embryo culture, increased the blastocyst development, the cell number of blastocysts and decreased the content of total lipids (36.8 %, 46.9 and 49.6 % 102

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respectively; P<0.05), in comparison with the supplementation of PVA in the PMS for embryo culture. These results suggest that the semi-defined culture media system developed by the National Genetic Resources Center (CNRG), have proved favorable effects on the total cell number and the decrease of total lipids of porcine blastocysts in vitro produced. Key words: Culture media, Pigs, Embryo, In vitro production.

Received: 26/01/2018 Accepted:08/08/2018

Introduction For many years, the in vitro production of porcine embryos has been the object of study of multiple investigations, and although there are currently several research groups working in this technique, the success rate remains low, especially compared with other species(1). This makes it difficult to gain any progress implementing this technology in the production units, limiting its use only for research purposes. The low rate of development of in vitro produced porcine embryos, could be due to inadequate conditions of culture and the high incidence of polyspermy(1, 2, 3). Currently, the standard medium for the in vitro embryo production is the North Carolina State University (NCSU) 23 or NCSU-37, supplemented with follicular fluid for maturation (medium chemically undefined)(4). The defined or semi-defined culture media removes unknown factors present in biological materials such as the follicular fluid, fetal bovine serum or serum albumin, and the use of these media for in vitro embryo production have had major progress. In addition, the use of defined and semi-defined media, facilitates the physiological evaluation of substances on maturation, fertilization and embryo development, enhances the reliability of the media and allows a high repeatability and reproducibility of the results(5). There are substrates that can replace the biological materials in the culture media as the polyvinyl alcohol (PVA), hyaluronic acid, bovine serum albumin (BSA) fatty acids free, recombinant albumin and serum synthetic. The objective of this study was to determine the effect of a semi-defined culture media system developed at the National Genetic Resources Center (CNRG), named Pigs Media System (PMS) on the in vitro production of porcine embryos.

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Material and methods The study was conducted at the CNRG, of the Instituto Nacional de Investigaciones Forestales Agrícolas y Pecuarias (INIFAP), located in Tepatitlán of Morelos, Jalisco, Mexico. It was developed a semi-defined system culture media, named PMS, for in vitro production of porcine embryos that consists of the following solutions: oocytes washing pre-maturation (H-PMS-M), maturation (PMS-M), oocytes washing pre-fertilization (H-PMS-F), fertilization (PMS-F), zygotes washing pre-embryo culture 1 (H-PMS-E1), embryo culture 1 (PMS-E1), embryos washing preembryo culture 2 (H-PMS-E2) and embryo culture 2 (PMS-E2) (Table 1). The PMS was supplemented with 0.4% BSA fatty acids free. All chemicals used in this study were acquired in the company Sigma-Aldrich (St. Louis, MO, USA). The preparation of the media was performed with ultra-pure water. The osmolarity of the media was of 270 to 290 milliosmoles (mOsm) and the pH was adjusted to 7.4. Table 1: Composition of cultured media for in vitro production of porcine embryos PMS Component H-PMSH-PMSPMSPMS-M H-PMS-F PMS-F PMS-E1 H-PMS-E2 (mM) M E1 E2 NaCl 100 94 97 94 100 94 100 94 KCl 10 10 10 10 10 10 10 10 KH2PO4 1.2 1.2 1.2 1.2 1.2 1.2 MgSO4 7H2O 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 Glucose 5.6 5.6 5.6 5.6 5.6 5.6 Alanine1.9 1.9 1.9 1.9 1.9 1.9 1.9 1.9 Glutamine Arginine 0.104 0.104 0.104 0.104 0.104 0.104 0.104 0.104 NaHCO3 5 25 5 25 5 25 5 25 Hepes 20 20 20 20 Na-pyruvate 2 2 0.33 0.33 Na-Lactate 4.5 4.5 Melatonin (µM) 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 CaCl2 2H2O 1.7 1.7 7 7 1.7 1.7 1.7 1.7 Caffeine 2 2 Taurine 7 7 7 7 7 7 Hypotaurine 5 5 5 5 5 5 NEAA´S* ml/L 10 10 10 10 10 10 10 10 EAA'S* ml/L 20 20 20 β-mercaptoetanol 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 Cysteine 0.6 EGF* (ng/ml) 10 Osmolarity 287 286 283 287 291 289 288 286 * NEAA´S= non-essential amino acids; EAA'S= essential amino acids; BSA= bovine serum albumin; EGF= Epidermal growth factor.

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Collection of oocytes and in vitro maturation

Oocytes were obtained from ovaries collected from gilts at the local slaughterhouse and were transported in saline solution 0.9% at 35°C. Ovarian follicles of 3-6 mm were pick up and aspirated with a needle caliber 18-gauge and 10 ml syringe. The cummulus-oocytes complexes (COCs) with a compact cumulus mass and a dark evenly granulated cytoplasm were selected and washed in HPMS-M. The COCs were cultured in 1 ml of medium of maturation in four-well multidish (Nunc, Roskilde, Denmark) during 22 h with 0.5 μg/ml of LH, 0.5 μg/ml of FSH and 1 millimolar (mM) dibutiryl cAMP, and subsequently for 22 h in the same medium, but without hormones and dibutiryl cAMP, at 38.5 °C with 5% CO2 in air.

In vitro fertilization After maturation, thirty COCs were placed in 90 μl of fertilization medium and covered with mineral oil, until fertilization. Frozen semen was thawed for 30 sec in water at 37 °C and centrifuged (700 ×g for 20 min) in gradients of Percoll 45:90 %. The sperm pellet was resuspended and washed by centrifugation (400 ×g for 5 min) with fertilization medium. The COCs were cultured during 3 hours with sperm at a final concentration of 5 × 105 cells/ml at 38.5 °C with 5% CO2 in air.

Embryo culture

The presumptive zygotes were removed from the fertilization media, washed and ten zygotes were placed in 90 μl of early culture medium, and cultured 48 h at 38.5 °C with 5% CO2, 5% O2 and 90 % N2. Afterwards, embryos were transferred to late culture medium, where they remained for 120 h under the previous conditions.

Evaluation of nuclear maturation, activation and fertilization

After maturation, some oocytes were removed from the cumulus cells, fixed with 25% (v/v) acetic acid and ethanol, for 48 to 72 h. The samples were stained with aceto-orcein 1% (w/v) and the percentage of mature oocytes (oocytes in metaphase II and first polar body formed) was evaluated with a clear field microscope. After 10 h post fertilization, some presumptive zygotes were 105

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removed from the cumulus cells, fixed, stained and evaluated as previously mentioned. The variables measured were: percentage of oocytes penetrated (the proportion of whole oocytes having a single female pronucleus and a single or multiple penetrated sperm nuclei or male pronuclei; the pronuclei with sperm tail were regarded as male pronuclei); monospermy (the proportion of monospermic penetration oocytes having female and male pronuclei); polyspermy (the proportion of oocytes having a single female pronucleus and multiple penetrated sperm nuclei or male pronucleus); and formation of male pronuclei (the proportion of whole oocytes with male pronuclei).

Evaluation of embryo development The following variables were evaluated for embryo development: percentage of embryos divided at 48 h and blastocyst development at 120 h per observation, under inverted microscope (200X); total cell number of the blastocysts were counted with staining Hoechst-33342 in an Eclipse 200 microscope equipped with fluorescence at a wavelength of 330 to 380 nm (Nikon Corp., Tokyo, Japan).

Lipid quantification The lipid quantification in the blastocyst cytoplasm was made through the Sudan-Black B. The embryos were fixed in 70% (v/v) formalin by at least 2 h. Afterwards, the embryos were washed in ultra-pure water for 1 min and subsequently in a 50% (v/v) ethanol solution for 2 min. The embryos were stained with 1% (w/v) Sudan-Black B in 70% ethanol for 30 sec to 1 min and were washed three times in a 50% (v/v) ethanol solution, for 5 min each time. Then, the embryos were washed in a 0.05% (w/v) PVA solution for 5 min and were mounted on a slide with glycerol. Pictures of each embryo were taken with an inverted microscope (Leica, DM IL-LED; camera Leica, DFC295; the equatorial part of the embryo was set in focus). The images were digitized and analyzed with the Software ImageJâ&#x201E;˘. The percentage of lipids was expressed as relative values with respect to the area occupied by the stained lipids of the embryo total area. The experimental unit was each dyed embryo and the space occupied by the lipids was expressed in percentage.

Experimental design

Assay 1. Effect of PMS on the in vitro production of porcine embryos. The COCs were washed with H-PMS-M or NCSU-23 media (added with follicular fluid)(4) and matured in PMS-M or NCSU-23 media. The mature oocytes were washed in H-PMS-F or Tris-buffer medium (TBMm)(6) 106

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and cultured with sperm in PMS-F or TBMm. The presumptive zygotes were washed in H-PMSE1 or NCSU-23 media and cultured in PMS-E1 or NCSU-23 media, during 48 h and then, the embryos were washed in H-PMS-E2 or NCSU-23 media and cultured in PMS-E2 or NCSU-23 media, during 120 h as previously described. Two groups were defined: group 1, PMS; group 2, NCSU-23. Assay 2: Effect of PMS with different macromolecules on the in-vitro oocytes maturation, fertilization and production of porcine embryos. The COCs were washed with H-PMS-M and maturated in PMS-M supplemented with 0.4% BSA or 0.01% of PVA; after maturation, the oocytes were washed using H-PMS-F and cultured with sperm in PMS-F. Then, the zygotes were washed in H-PMS-E1 and cultured in PMS-E1 supplemented with 0.4% BSA or 0.01% of PVA, 48 h. After this step, the embryos were washed in H-PMS-E2 and cultured in PMS-E2 supplemented with 0.4% BSA or 0.01% of PVA, for 120 h as previously described. Maturation and culture were performed in PMS using BSA or PVA in a 2 × 2 factorial arrangement. It was defined four groups: PMS-BSA/BSA. PMS-BSA/PVA, PMS-PVA/PVA, PMS-PVA/BSA.

Statistical analysis

Data was submitted to an analysis of variance, for a completely randomized design (on experiments 2, a 2 × 2 factorial arrangement, being the factors: BSA or PVA in the maturation, and BSA or PVA in the culture), the GLM procedure (SAS Version 9.3, 2012; SAS Institute, Cary, NC, USA) was used. Prior to the analysis, the data expressed as proportions (p) were subjected to a variance homogeneity test, if necessary, they were transformed to its arcsine (√p), to be analyzed using GLM and subsequently transformed back to real values and are expressed as percentages in the results.

Results Assay 1

There were no significant differences for the oocytes maturation and fertilization, between the group PMS (88.6 ± 0.8 %) and the group NCSU-23 (87.5 ± 3.4 %) (Figure 1; Table 2). The use of PMS significantly increased the total cell number in blastocyst and reduced the percentage of total lipids (58.04 ± 1.8 and 49.4 ± 5.6 %; P<0.05) compared with the group NCSU-23 (37.9 ± 1 and 59.2 ± 2.2 %) (Table 3). However, there were no significant differences in the percentages of embryo division and blastocyst development between groups. 107

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Figure 1: In vitro maturation of porcine oocytes with different media. The graphic shows the Least Square Means ± SEM. Data from five replicates 100 88.6

87.5

PMS

NCSU-23

% Maturation

Assay 2 Table 2: In vitro fertilization of porcine oocytes matured in vitro with different media Oocytes Medium Percentage of oocytes examined Penetrated

Monospermy* Polyspermy*

MPN-formed*

PMS

109

82.6 ± 1.2

45.4 ± 1.6

46.6 ± 0.6

92.1 ± 1.3

NCSU-23

84.9 ± 1.4

41.5 ± 2.7

43.7 ± 4.5

85.1 ± 6.0

Data from five replicates. Percentages are expressed as Least Square Means ± SEM. *Calculated as a percentage of penetrated oocytes.

Table 3: In vitro development of porcine oocytes matured in vitro with different media after in vitro fertilization Medium

Presumptive zygotes cultured

Cleaved at Blastocyst day 2 (%) day 7 (%)

PMS

236

72.0 ± 3.3

25.4 ± 7.1

58.0a ± 1.8

49.4a ± 5.6

NCSU-23

253

77.6 ± 5.7

23.7 ± 2.6

37.9b ± 1.0

59.2b ± 2.2

at Total No. of cells Total lipids in blastocysts (%)

Data from five replicates. Percentages are expressed as least square means ± SEM. Values with different superscripts within each column are significantly different (P<0.05).

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There were no significant differences in the oocyte maturation between the group PMS-BSA (92.8 ± 0.9 %) and the group PMS-PVA (91.5 ± 1.3 %) (Figure 2). However, the percentage of monospermic fertilization was significantly lower (42.3 ± 3.1 %; P<0.05) when the oocytes were matured with PMS-BSA in comparison with those matured with PMS-PVA (52.6 ± 3.3 %) (Table 4). Figure 2: In vitro maturation of porcine oocytes in medium PMS-M with different macromolecule. The graphic shows the Least Square Means ± SEM. Data from five replicates 100

92.8

91.5

PMS-BSA

PMS-PVA

%Maturation

Table 4: In vitro fertilization of porcine oocytes matured in vitro with different media Oocytes Medium Percentage of oocytes examined MPNPenetrated Monospermy* Polyspermy* formed* PMS-BSA

100

94.9 ± 2.5

42.3a ± 3.1

43.3a ± 2.0

85.6 ± 4.0

PMS-PVA

103

88.7 ± 2.1

52.6b ± 3.3

34.2b ± 2.8

86.8 ± 4.0

abc

Data from five replicates. Percentages are expressed as Least Square Means ± SEM. Values with different superscripts within each column are significantly different (P<0.05). *Calculated as a percentage of penetrated oocytes

The interaction of using either BSA or PVA in maturation and culture PMS was not significant, for any of the variables evaluated. Nevertheless, the percentage of blastocyst development was significantly higher in the group PMS-BSA/BSA (36.8 ± 6.0 %; P<0.05), compared to the PMSBSA/PVA and PMS-PVA/PVA (23.5 ± 3.2 and 23.9 ± 4.1 %, respectively) groups, whereas the group PMS-PVA/BSA (30.5 ± 5.1 %) was intermediate. The cell number in the blastocyst was significantly higher for the group PMS-PVA/BSA (46.9 ± 2.5; P<0.05), compared to the PMSBSA/PVA and PMS-PVA/PVA (38.0 ± 2.3 and 32.8 ± 1.3 respectively) groups, while the group 109

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PMS-BSA/BSA (44.9 ± 3.0 was intermediate. The group PMS-BSA/BSA (49.6 ± 3.0 %; P<0.05) was significantly lower for the content of total lipids, compared to the PMS-BSA/PVA and PMSPVA/PVA (62.4 ± 3.2 % and 61.3 ± 2.0 %) groups, the group PMS-PVA/BSA (51.2 ± 5.6 %) was intermediate (Table 5). Table 5: In vitro development of porcine oocytes matured in vitro with different media after in vitro fertilization Presumptive Total No. of Cleaved at Blastocyst at Total lipids Medium zygotes cells in day 2 (%) day 7 (%) (%) cultured blastocysts PMS-BSA/BSA

160

80.2 ± 2.3

36.8a ± 6.0

44.9ab ± 3.0

49.6a ± 2.9

PMS-BSA/PVA

155

76.8 ± 5.4

23.5b ± 3.2

38.0bc ± 2.3

62.4b ± 3.2

PMS-PVA/PVA

147

79.3 ± 3.9

23.9b ± 4.1

32.8c ± 1.3

61.3b ± 2.0

PMS-PVA/BSA

148

79.4 ± 3.2

30.5ab ± 5.1

46.9a ± 2.5

51.2ab ± 5.6

Discussion Results obtained in the first experiment showed that the porcine oocytes can be matured, fertilized and developed in vitro until the blastocyst stage using the semi-defined PMS. There were no significant differences for the oocytes maturation using PMS (88.6 %) and NCSU-23 medium (87.5 %) supplemented with follicular fluid during this study. These results are similar to other studies that used the NCSU-32 medium supplemented with follicular fluid and a defined medium supplemented with PVA(5,7). Similar data for the rate of penetration and monospermic fertilization were obtained (87.6 % and 44.8 %) in oocytes matured in media supplemented with follicular fluid and subsequently fertilized(5), compared to this study (82.6 % and 45.4 %). Percentages of embryos divided and blastocyst production were reported (79.4 % and 28.8 %) in a defined medium(8). In this work, was obtained 25.4 % and 23.7 % of blastocysts for PMS and NCSU-23 medium respectively. Other studies reported similar data for production of blastocysts with defined medium and the NCSU-23 medium supplemented with follicular fluid(5,7,9). In pigs, the supplementation of follicular fluid in maturation medium has a beneficial effect on the nuclear maturation of oocytes, fertilization and embryo development in vitro(10,11,12). However, follicular fluid can be replaced by other macromolecules such as the PVA or BSA fatty acids free(5,13). The PMS contains BSA, a total of 22 amino acids, supplement of arginine, melatonin and βmercaptoethanol, whereas the NCSU-23 medium does not, this perhaps could be favoring the maturation, fertilization, development and embryo quality in this study. It has been demonstrated that the amino acids in a culture medium play an important role, as osmoregulator(14), intracellular 110

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buffers(15), heavy metals chelators(16) and energy substrates(17). The beneficial effects of the essential and non-essential amino acids in a chemically defined NCSU-23 medium on the porcine oocytes maturation have been reported(13). The melatonin and its metabolites are effective antioxidants, which scavenger the reactive oxygen species (ROS) and regulate several antioxidant enzymes(18,19). Melatonin has been found to regulate the oocyte maturation in carp(20) and improves the in vitro embryo development and total cell number in porcine blastocyst(21). The PMS showed a lower percentage of lipids (49.4 %), compared to the NCSU-23 medium (59.2 %). It also has been demonstrated that melatonin has large lipolytic properties(22). Melatonin promotes lipid metabolism have been found in porcine oocytes, providing a source of essential energy for oocyte maturation and subsequent embryo development (23). It has been reported that the decrease of intracitoplasmatic lipids in embryos, increases their cryotolerance due to a lower lipid peroxidation and therefore a lower cell damage(24,25). Arginine is a vital amino acid for many metabolic processes in the cell, such as protein synthesis, creatine production, polyamines synthesis and nitric oxide generation(26). Arginine has a positive effect on the oocytes maturation(27) and improves the in vitro embryo development in pig(28). The addition of arginine in the embryo culture medium increases the percentage of embryos that develop up to the stage of blastocyst and the total cell number of blastocyst(29). The PMS showed a significant greater total cell number (58.04) compared to the NCSU-23 medium (37.9). An indicator of the embryo quality is the total cell number of blastocyst(29). The implementation of a semi-defined or defined cultured media system for in vitro embryo production is considered important to observe the effects of some supplements of interest in the medium on the maturation, fertilization and embryo development by eliminating these unknown factors that the follicular fluid provides to the medium(30). In the second assay, the results showed a percentage of monospermic fertilization significantly lower (42.3 Âą 3.1 %; P<0.05) when the oocytes were matured with PMS-BSA compared with PMSPVA (52.6 Âą 3.3 %). It has been demonstrated that the addition of PVA to maturation medium improves the percentage of monospermic embryos during the in vitro fertilization of porcine oocytes(5,8). When the maturation medium is supplemented with PVA, monospermic fertilization can reach between up to 70-80 % of success(5,7). However, a decline has been observed in the penetration rate of matured oocytes when replacing the follicular fluid with PVA in the NSCU-37 medium, perhaps due to that, the number of oocyte that reach the metaphase II stage during fertilization, decreases(5). During this study, was observed that the sperm penetration does not decrease when replacing BSA with PVA in the maturation medium, probably due to the fact that the PMS has a higher content of amino acids and factors, that could be contributing conditions than the BSA provides. Future histological and biochemical analysis of matured and fertilized oocytes are required to understand the mechanism of polyspermic fertilization in the system of in vitro production of porcine embryos with the addition of different macromolecules. 111

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Addition of BSA during the embryo culture, improves the embryo development, the cell number in the blastocyst and decreases the total lipids, probably due to the nutrients that BSA brings. BSA plays a role in embryo development(31), formation and hatching of blastocyst(32). However, it did not find differences in the percentage of bovine embryos that reached the stage of blastocyst in a medium supplemented with PVA, BSA or fetal bovine serum(33). However, the blastocysts produced in PVA had a lower amount of cell number. Future studies are required to determine if there is a relationship between the total cell number and lipids in the porcine blastocyst.

Conclusions and implications Results suggest that the semi-defined PMS, has favorable effects on the total cell number and decrease of total lipids of blastocyst in pigs; so they can be used for the in vitro production of porcine embryos. The use of PVA instead of BSA during the maturation, has a positive effect on the rate of in vitro monospermic fertilization of porcine oocytes. Future histological and biochemical analysis on the oocytes maturation and fertilization, as well as the embryo development, are required to understand the mechanisms of action of macromolecules during in vitro production of porcine embryos. The PMS developed by the CNRG could be used to favor the cryopreservation of in vitro produced porcine embryos.

Acknowledgements The authors acknowledge to PIGAMEX and Efren Altamirano from â&#x20AC;&#x153;Posta el Cuatroâ&#x20AC;?, for providing with the biological material.

Literature cited: 1. Grupen CG. The evolution of porcine embryo in vitro production. Theriogenology 2104;(81):2437. 2. Funahashi H. Polyspermic penetration in porcine IVM-IVF systems. Reprod Fertil Dev 2003;(15):167-77. 3. Kikuchi K, Somfai T, Nakai M, Nagai T. Appearance, fate and utilization of abnormal porcine embryos produced by in vitro maturation and fertilization. J Reprod Fertil 2009;66(Suppl):135-47.

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4. Petters RM, Wells KD. Culture of pig embryos. J Reprod Fertil 1993;(48): 61-73. 5. Yoshioka K, Suzuki C, Onishi A. Defined System for in vitro production of porcine embryos using a single basic medium. J Reprod Dev 2008;(54):208-213. 6. Abeydeera LR, Day BN. In vitro penetration of pig oocytes in a modified Tris buffered medium: effect of BSA, caffeine and calcium. Theriogenology 1997;(48):537-544. 7. Hong JY, Yong HY, Lee BC, Hwang WS, Lim JM, Lee ES. Effects of amino acids on maturation, fertilization and embryo development of pig follicular oocytes in two IVM media. Theriogenology 2004;(62):1473-1482. 8. Yoshioka K, Suzuki C, Itoh S, Kikuchi K, Iwamura S, Rodriguez HM. Production of piglets derived from in vitro-produced blastocysts fertilized and cultured in chemically defined media: Effects of theophylline, adenosine, and cysteine during in vitro fertilization. Biol Reprod 2003;(69):2092-1099. 9. Kohata C, Izquierdo-Rico MJ, Romar R, Funahashi H. Development competence and relative transcript abundance of oocytes derived from small and medium follicles of prepubertal gilts. Theriogenology 2013;(80):970-978. 10. Yoshida M, Ishizaki Y, Kawagishi H, Bamba K, Kojima Y. Effects of pig follicular fluid on maturation of pig oocytes in vitro and on their subsequent fertilizing and developmental capacity in vitro. J Reprod Fertil 1992;(95):481-488. 11. Vatzias G, Hagen DR. Effects of porcine follicular fluid and oviduct-conditioned media on maturation and fertilization of porcine oocytes in vitro. Biol Reprod 1999;(60):42-48. 12. Yoon KW, Shin TY, Park JI, Roh S, Lim JM, Lee BC, et al. Development of porcine oocytes from preovulatory follicles of different sizes after maturation in media supplemented with follicular fluids. Reprod Fertil Dev 2000;(12):133-139. 13. Hong J, Lee E. Intrafolicular amino acid concentration and the effect of amino acids in a defined maturation medium on porcine oocyte maturation, fertilization, and preimplantation development. Theriogenology 2007;(68):728-735. 14. Abeydeera LR, Wang WH, Cantley TC, Prather RS, Day BN. Glutathione contentand embryo development after in vitro fertilization and various concentrations of cysteine. Zygote 1999;(7):203–210. 15. Edwards LJ, Williams DA, Gardner DK. Intracellular pH of the mouse preimplantation embryo: amino acids act as buffer of intracellular pH. Hum Reprod 1998;(13):3441– 3448. 16. Bavister BD. Culture of preimplantation embryos: facts and artifacts. Hum Reprod Update 1995;(1):91–148. 113

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17. Rose-Hellekant TA, Libersky-Williamson EA, Bavister BD. Energy substrates and amino acids provided during in vitro maturation of bovine oocytes alter acquisition of developmental competence. Zygote 1998;(6):285–294. 18. Tomas-Zapico C, Coto-Montes A. A proposed mechanism to explain the stimulatory effect of melatonin on antioxidative enzymes. J Pineal Res 2005;(39):99–104. 19. Tan DX, Manchester LC, Terron MP, Flores LJ, Reiter RJ. One molecule, many derivatives: a never-ending interaction of melatonin with reactive oxygen and nitrogen species? J Pineal Res 2007;(42):28–42. 20. Chattoraj A, Bhattacharyya S, Basu D, Bhattacharya S, Bhattacharya S, Maitra SK. Melatonin accelerates maturation inducing hormone (MIH): induced oocyte maturation in carps. Gen Comp Endocrinol 2005;(140):145–155. 21. Shi JM, Tian XZ, Zhou GB, Wang L, Gao C, Zhu SE, et al. Melatonin exists in porcine follicular fluid and improves in vitro maturation and parthenogenetic development of porcine oocytes. J Pineal Res 2009;(47):318-323. 22. Paradies G, Petrosillo G, Paradies V, Reiter RJ, Ruggiero FM. Melatonin, cardiolipin and mitochondrial bioenergetics in health and disease. J Pineal Res 2010;(48):297-310. 23. Jin J-X, Lee S, Taweechaipaisankul A, Kim GA, Lee BC. Melatonin regulates lipid metabolism in porcine oocytes. J Pineal Res 2017;(62):e12388. 24. Gómez E, Rodríguez A, Muñoz M, Caamaño JN, Hidalgo CO, Morán E, et al. Serum free embryo culture medium improves in vitro survival of bovine blastocysts to vitrification. Theriogenology 2008;(69):1013–1021. 25. Paschoal D, Sudano M, Maziero R, Guastali M, Magalhães L, Landim-Alvarenga F, et al. Cryopreservation of in vitro produced bovine embryos after lipid decrease with forskolin. Reprod Fertil Dev 2016;(28):212-213. 26. Wheatley DN, Campbell E. Arginine deprivation, growth inhibition and tumour cell death: 3. Deficient utilisation of citrulline by malignant cells. Br J Cancer 2003;(89):573–576. 27. Coburn RF. Polyamine effects on cell function: possible central role of plasma membrane PI (4,5) P2. J Cel Physiol 2009;(221):544-551. 28. Bauer BK, Isom SC, Spate LD, Whitworth KM, Spollen WG, Blake SM, et al. Transcriptional profiling by deep sequencing identifies differences in mRNA transcript abundance in in vivoderived versus in vitro cultured porcine blastocyst stage embryos. Biol Reprod 2010;(83):791798.

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29. Redel BK, Tessanne KJ, Spate LD, Murphy CN, Prather RS. Arginine increases development of in vitro-produced porcine embryos and affects the protein arginine methyltransferasedimethylarginine dimethylaminohydrolase-nitric oxide axis. Reprod Fertil Dev 2015;(27):655666. 30. Wang WH, Day BN. Development of porcine embryos produced by IVM/IVF in a medium with or without protein supplementation: effect of extracellular glutathione. Zygote 2002;(10):109-115. 31. Kim HS, Lee GS, Hyun SH, Lee SH, Nam DH, Jeong YW, et al. Improved in vitro development of porcine embryos with different energy substrates and serum. Theriogenology 2004;61(7):1381-1393. 32. Gardner DK, Lane M, Spitzer A, Batt PA. Enhanced rates of cleavage and development for sheep zygotes cultured to the blastocyst stage in vitro in the absence of serum and somatic cells: amino acid, vitamins and culturing embryos in groups stimulate development. Biol Reprod 1994;(50):390-400. 33. Kubisch HM, Larson MA, Ealy AD, Murphy CN, Roberts RM. Genetic and environmental determinants of interferon-tau secretion by in vivo- and in vitro-derived bovine blastocysts. Anim Reprod Sci 2001;(66):1â&#x20AC;&#x201C;13.

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https://doi.org/10.22319/rmcp.v11i1.5018 Article

Transmission of Anaplasma marginale by unfed Rhipicephalus microplus tick larvae under experimental conditions

Itzel Amaro Estrada a Miguel A. García-Ortiz b Jesús F. Preciado de la Torre a Edmundo E. Rojas-Ramírez a Rubén Hernández-Ortiz a Francisco Alpírez-Mendoza c† Sergio D. Rodríguez Camarillo a*

Instituto Nacional de Investigaciones Forestales Agrícolas y Pecuarias (INIFAP). Centro Nacional de Investigación Disciplinaria en Salud Animal e Inocuidad. Tel: +52 777 3192860 ext. 125, Fax: +52 777 3192850 ext. 129. Carr. Cuernavaca - Cuautla No 8534, Col. Progreso, Jiutepec, Mor. 62550, México. b

Independent Scientist. México.

INIFAP. Campo Experimental La Posta, Paso del Toro, Veracruz, México.

†

This work is dedicated to Dr. Francisco Alpírez Mendoza whom passed away of natural causes while this work was in progress.

*Corresponding author: rodriguez.sergio@inifap.gob.mx; sergeiyevsky@yahoo.com

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Abstract: The current description of biological transmission of Anaplasma marginale by Rhipicephalus microplus ticks, includes of the biological intrastadial and transstadial transmission. Both transovarian transmission of Anaplasma from engorged ticks to their progeny and, transmission from infected unfed larvae to the mammalian host is controversial. In order to demonstrate vertical transmission of A. marginale by R. microplus ticks under experimental conditions, feed-acquisition infected engorged females were incubated at 18 °C or 28 °C for oviposition. Larvae hatched from these ticks were used to infest two steers for each incubation temperature. None of the four steers infested with either lot of larvae developed clinical disease, yet subclinical infection was observed in the steers infested with larvae from engorged ticks incubated at 28 °C for hatching. gDNA from, larvae used for the infection of the carrier tick donor, gDNA from larvae oviposited at 28 ºC, gDNA from blood of A. marginale-positive steers, were positive for amplification of msp5 and msp1α the variable region by PCR. All other DNA samples from the original stabilate, blood from the donor steer, larvae from ticks incubated at 28 °C and blood from steers infested with these same larvae were positive to both, msp5 and msp1α PCR. msp1α sequences of all PCR products were the same and are consistent with previously reported Tlapacoyan-2 sequence. The present evidence indicates that R. microplus is capable of passing A. marginale to its progeny and that these infected larvae can transmit the infection to susceptible hosts. Key words: Anaplasma marginale, Transovarian transmission, Ticks, Rhipicephalus microplus.

Received: 15/08/2018 Accepted: 30/01/2019

Introduction Ticks are globally widespread ectoparasites and their eco-epidemiology is dependent on the regional environmental conditions(1). Ticks are arthropods with great capacity for transmission of human and animal pathogens and are considered the most important vectors of disease-causing pathogens in domestic and wild animals second to mosquitoes(1,2). There are many species of ticks present in Mexico(3) but the most economically important in the cattle industry is Rhipicephalus microplus both in Mexico and Latin America. R. microplus

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is responsible for direct damage and transmission of bovine babesiosis and bovine anaplasmosis(3,4). While transovarian transmission of bovine babesiosis has been clearly established(5), transovarian transmission of bovine anaplasmosis is still controversial. Bovine anaplasmosis a rickettsial tick-borne disease of worldwide distribution(6). Anaplasma marginale, the causal agent, infects mature erythrocytes of several ruminant species but it is of greater impact in adult beef cattle; the clinical syndrome includes fever, anemia, losses in weight and production and, death if timely treatment is not provided(7,8). In cattle, A. marginale infects mature erythrocytes and endothelial cells(9,10) and, despite specific treatment, cattle may remain as asymptomatic carriers for the rest of their lives(11,12). The emergence of antigenic variants of membrane proteins of the rickettsia in the mammalian host has also been shown to be fundamental for its permanence and transmission to naĂŻve hosts(13). Transmission of A. marginale between cattle occurs both mechanically and biologically. Mechanically, by blood sucking arthropods and veterinary procedures that transfer infected blood from carriers to naĂŻve hosts(14,15). Biological transmission is carried mainly by Rhipicephalus and Dermacentor ticks(8) but in Latin America, the cattle tick Rhipicephalus microplus is the main biological vector(4). Ticks can transmit biologically the rickettsia within the same stage (intrastadial) and from one stage to another (transstadial). Tick larvae, nymphs and adults acquire the rickettsia by feeding on cattle and these replicate within R. microplus midgut cells(16,17,18). After an initial cycle of replication, tick transmissible Anaplasma strains migrate from the midgut through the hemolymph to other tissues, including the salivary gland acinar cells where the rickettsia undergoes several cycles of final logarithmic replication(19). Upon a second round of feeding, and usually, after molting (transstadial transmission), ticks secrete the infective forms of the rickettsia in their saliva while feeding, thus transmitting the rickettsia(18). Previous evidence has shown that hand-transferred adult R. microplus males transmit A. marginale(4,20). A. marginale infected R. microplus nymphs and young adults (larvae and nymphs incubated in the laboratory and allowed to molt to the next stage) and hand-transferred to susceptible animals were capable to transmit Mexican Aguascalientes and Yucatan A. marginale strains of high and low virulence respectively in the laboratory(21). R. microplus is a one-host tick which spends its entire parasitic life on the same animal until engorged females drop to lay their eggs. Adult male ticks can migrate through physical contact from one host to another(22,23). Their importance as A. marginale vector between different animals though has not been fully evaluated. The apparent inefficiency of male ticks as transmitters, and the presence of anaplasmosis outbreaks at the beginning of the tick season has led to propose that, larvae of infected ticks may acquire the infection through the ovary 118

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(transovarian transmission). Larvae are then hatched infected, becoming potential vectors for A. marginale(24). Further experimental efforts to prove transovarian transmission in Dermacentor ticks have been inconclusive(25). In an effort to clarify transovarian transmission in R. microplus, Shimada and coworkers(26) collected R. microplus larvae from an infected pasture during the first five months of the year in Brazil, and found that 7/50 samples were positive when tested for msp5 by nested PCR (nPCR). In this same study, female ticks engorged on an A. marginale infected carrier were incubated at 18 ºC or 28º C for oviposition; eleven percent of larvae from engorged ticks incubated at 18 ºC and none from those incubated at 28 ºC were positive when tested for msp5 by nPCR. These authors however, make no reference of msp5-positive larvae from any of these groups to be infested onto susceptible cattle to confirm feed-transmission(26). In light of these findings it was hypothesized that R. microplus larvae can acquire A. marginale from their A. marginale-engorged progenitor (transovarian transmission) and when incubated at 18 ºC and, through feeding, transmit the infection to uninfected cattle under laboratory conditions

Material and methods Ethics statement

This study was approved by the CENID-PAVET branch of the INIFAP Animal Experimentation and Ethics Committee and conducted considering ethic and methodological aspects in agreement with the Mexican regulations related to use, housing and transport of experimental animals NOM-062-ZOO-1999.

Pathogen and vector strains

The Anaplasma marginale Tlapacoyan-2 strain used in this study was originally collected in the Municipality of Tlapacoyan, Veracruz state, Mexico, from a natural outbreak and has been characterized with regards to the msp1 variable region and msp4 genes(27). This strain has been shown to be transmissible by R. microplus adult males in CENID-PAVET laboratory.

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The “Media Joya” colony of R. microplus was originally collected from the Tapalpa Municipality, Jalisco State, Mexico(28,29), and is routinely maintained through passages in tick-borne disease-free steers at the CENID-PAVET. The colony efficiently transmits multiple A. marginale strains, including the Tlapacoyan-2 strain(21). To ascertain that the strain is free of A. marginale, ticks from every generation are routinely tested for the absence of A. marginale by nPCR for the msp5 gene (see below). Five 12-month old Bos taurus-cross steers were purchased from a local breeder in the Municipality of Cuauhtémoc, west-central Chihuahua state, Mexico which is classified as tick-free by The Mexican National Service of Health, Safety and Agro-Food Quality (http://www.gob.mx/senasica/documentos/34495). These steers were certified free of tuberculosis and brucellosis by Federally certified laboratories. The animals were tick-free, and were also free of A. marginale as certified by endpoint nPCR for msp5 gene. Steer 027 was purchased first and the remaining four steers (1756, 1776, 6963 and 6964) were purchased later from the same breeder to assure they all met sanitary standards as required by Mexican authorities and our own, with regards to age and absence of ticks and, tick-borne and other infectious diseases. The CENID-PAVET laboratories and stalls are located on the outskirts, within the city limits of the small urban area of Progreso, in the Jiutepec Municipality of the state of Morelos, central Mexico. The quarters are free of ticks. Tick treatment is required for animals entering these quarters and all animals housed in outdoor stalls are periodically sprayed for fly control. All animals used in these experiments were housed at the Cattle Isolation Unit of the CENIDPAVET, a tick and fly-proof confinement stall.

Infection of carrier animal Steer 027 was intravenously inoculated with a dose of 8.2 x 109 infected erythrocytes of A. marginale Tlapacoyan-2 strain preserved under liquid nitrogen. The infection was monitored and the animal required no treatment. Steer 027 remained as an asymptomatic carrier as tested both by microscopic examination of Giemsa-stained blood slides and amplification of msp5 gene by nPCR, for the 15 mo prior to infestation with R. microplus for this study. Steer 027 was infested with (approximately 10,000) Media-Joya R. microplus mature larvae hatched from 0.5 g of eggs to feed-acquire the infection. Twenty-one (21) days later, mature engorged females were collected directly from steer 027, rinsed in distilled water to eliminate debris and groups of 10 females were set into petri dishes and incubated at 80 % humidity.

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Incubation for oviposition

Engorged females were set in two different lots to complete oviposition as follows. The first lot was incubated at 18 ºC for oviposition in a climatized room which is set to have maximal variations of 2 ºC. In order to avoid temperature variations due to regular use of the room, ticks were kept within a small portable cooler and 80 % humidity was provided by use of damp wicks and controlled by use of a Traceable hygrometer (Fisher Scientific). An equal number of dishes were set at 28 ºC for oviposition into a Nor-Lake Scientific incubator (NorLake LRF201WWW-0). Humidity was maintained at 80 % saturation as described. Once oviposition was complete, egg masses from each temperature were pooled, weighted and divided into 0.25 g lots and kept in 5 ml glass vials capped with cotton plugs. Both egg-lots were incubated at 28 ºC and 80 % humidity as described, for another two weeks until hatching. Mature larvae (approximately 5,000) from 0.25 g egg-lots were used for feedtransmission on intact steers. Additional mature larvae from 0.25 g lots from females kept at 18 ºC and 28 ºC were frozen for further determination and identification of A. marginale DNA by amplification of msp5 and msp1 variable region.

Feed-transmission infection of naïve steers, clinical monitoring, and sample collection

Four non-splenectomized steers were each infested with mature larvae from 0.25 g egg lots; steers 1756 and 1776 were infested with larvae from engorged females incubated at 18 ºC while steers 6963 and 6964 were infested with larvae from engorged females incubated at 28 ºC.

Clinical monitoring

Clinical monitoring of experimental animals included daily registration of rectal temperature (between 8 and 9 in the morning), daily collection of blood with anticoagulant by venipuncture of the caudal vein for examination of Giemsa-stained blood smears and evaluation of packed cell volume by the microhematocrit method and weekly amplification of msp5 gene by nPCR and, msp1 gene variable region by PCR and sequencing(27).

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DNA extraction, PCR, cloning and sequencing

Larvae from engorged females incubated at 18 ºC and at 28 ºC were used for extraction of genomic DNA (gDNA). Larvae from 100 mg eggs masses were extracted as follows: frozen (–70 ºC) larvae were pulverized using a –70 ºC frozen mortar. The pulverized larvae were then solubilized in 1M Tris-HCl, 0.5 M EDTA, proteinase K (1 mg/7 ml) solution and centrifuged 10,000 xg; the supernatant was separated from DNA with two cycles of phenol-chloroform-isoamyl alcohol and chloroform. Supernatants were washed stepwise first with absolute ethanol and then with 70% ethanol. The DNA was hydrated in double distilled-deionized sterile water and kept frozen at –20 ºC until use. Anticoagulated blood samples from transmission–infected steers were centrifuged at 2,250 xg for 15 min at 4 °C: plasma and buffy coat were discarded. gDNA was extracted by means of a commercial kit (UltraClean® BloodSpin® DNA Isolation Kit, MO-BIO Laboratories Inc.), following manufacturer’s instructions. gDNA was kept at –20 ºC until use. DNA samples from blood and larvae were assayed for msp5 gene as a universal marker for A. marginale by nested PCR using forward: 5’-GCATAGCCTCCGCGTCTTTC-3’ and reverse 5’-TCCTCGCCTTGCCCTCAGA-3’ primers in the first round of amplification and forward 5’-TACACGTGCCCTACCGACTTA-3’ and reverse (30) 5’-TCCTCGCCTTGCCCTCAGA-3’ primers in the second round as described . msp5 nPCR was run in two rounds in a 25 µl final volume with a commercial kit (PCR master mix, system, Promega, Madison, WI, USA) in a T-Professional Thermocycler (Biometra, Germany), 0.1 – 1 ng DNA and 10 pM primers. Cycling conditions for msp5 were a preheating step at 95 °C for 3 min and 35 cycles of 95 °C for 30 s, 65 °C for 58 s, and 72 °C for 30 s with final extension step at 72 °C for 10 min. msp5 nPCR positive samples were assayed for the msp1 variable region by PCR (forward: 5’ –GTGCTTATGGCAGACATTTCC-3’ and reverse (27,31) 5’-CTCAACACTCGCAACCTTGG-3’ primers) for strain verification. For the msp1α variable region cycling conditions were preheating step 95 ºC for 3 min and 35 cycles 60 s, 58 ºC 60 s, 72 ºC 60 s, and final extension at 72 ºC for 10 min. nPCR and PCR products were separated in 2% agarose gels following electrophoresis in 1x TAE buffer and staining with 0.015% ethidium bromide at 100 volts. msp1α variable region PCR products were cloned in pJet1.2 plasmid system using CloneJet PCR cloning kit (Thermo Fisher Scientific), and E. coli TOP10 competent cells were transformed with the constructions following manufacturer instructions. Positive colonies were grown in LB+ampicillin (100 mg/ml) and plasmid DNA was isolated by use of Wizard® Plus SV Minipreps (Promega, Madison WI, USA). Plasmid DNA from at least three isolated colonies was sequenced for determination of the consensus 122

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sequence. DNA sequences derived from Sanger sequencing were analyzed with ApE Plasmid Editor v2.0.47. Consensus sequences were aligned with ClustalW (http://www.clustal.org/).

Results Initial infection and feed-acquisition of Anaplasma marginale

Intravenous inoculation of steer 027 with A. marginale Tlapacoyan-2 strain resulted in positive blood-smears and mild clinical signs of anaplasmosis (39 ºC rectal temperature, depression, loss of appetite and anemia), reaching a 3.2 % maximal rickettsemia, and a loss of 50 % packed cell volume by d 25. Chemotherapy was no required and steer 027 returned to normal clinical values within 2 wk after onset of infection. Steer 027 remained as a subclinical carrier for the next 15 mo, as corroborated by periodic nPCR for msp5 gene amplification. Mature R. microplus larvae negative to A. marginale as determined by msp5 nPCR, were infested on steer 027 for feed-acquisition infection. Engorged females collected 21 d later and incubated at 28 ºC, completed oviposition over 15 d, a period considered normal. In contrast, engorged females collected at the same time but incubated at 18 ºC took over 30 d to complete oviposition. Regardless of the temperature at which the mothers were incubated, larvae from both lots completed hatching within 15 d after oviposition.

Feed–Transmission

Steers were infested with R. microplus larvae from engorged females incubated at 18 ºC (steers 1756 and 1776) and 28 ºC (steers 6963 and 6964), respectively. Mature unfed larvae were allowed to feed and reach adult stage on designated steers. None of the four steers developed clinical signs of anaplasmosis or showed infected erythrocytes at microscopic evaluation of blood smears during this period. Eight weeks after infestation, all four animals were subjected to experimental splenectomy in order to immunosuppress and induce rickettsemia. Steer 6964 (larvae oviposited at 28 ºC) developed a 7.5 % rickettsemia detectable by microscopy recorded 2 d after splenectomy moment when the animal received specific treatment (oxytetracyclin 20 mg/kg for three consecutive days). Despite splenectomy, none of the other three steers developed microscopically detectable rickettsemia. msp5 specific nPCR amplification corroborated the presence of A. marginale DNA in steers 6964 and 6963 but did not amplify in blood from steers 1756 and 1776 (Figure 1). 123

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Figure 1: Anaplasma marginale msp5 nPCR detection. nPCR products were separated by electrophoresis in 1% agarose gel

M. Molecular weight marker; 1, Tlapacoyan-2 original frozen stabilate; 2, steer 027; 3, steer 1756; 4, steer 1776; 5, steer 6963; 6, steer 6964

In order to corroborate that Tlapacoyan-2 strain was the same pathogen infecting steers 027, 6964 and 6963, blood samples from these steers, a sample of the original cryopreserved stabilate and, larvae hatched from ticks incubated a 28 °C, were assayed for the msp1 variable region. Figure 2 shows a 750 bp PCR product (lane 2) for Tlapacoyan-2 cryopreserved stabilate, in agreement with the reported sequence(27); (GenBank accession number JN564641.1). A band with the same apparent molecular weight was present in all other samples tested for the variable region of msp1 in blood samples from steers 027 (Lane 3), 6964 (Lane 5) and 6963 (lane 6) and R. microplus larvae from engorged ticks incubated at 28º C (Lane 4).

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Figure 2: msp1a variable region specific PCR

Panel A; M, molecular weight marker; lane 1, (–) control; lane 2(+) control Mex-31 infected blood; lane 3, Tlapacoyan-1 infected blood; lane 4, Tlapacoyan-2 infected blood. Panel B: lane 1, Tlapacoyan-2 cryostabilate; lane 2, steer 027 blood sample; lane 3, steer 6963 week 9 blood sample; lane 4, R. microplus larvae from engorged ticks incubated at 28º C and lane 5, steer 6964 week 9 blood sample.

All sequences derived from either blood or larvae were identical for the msp1 variable region of Tlapacoyan-2 strain as reported(27). This finding is consistent with the hypothesis that R. microplus larvae from engorged ticks acquire the infection from their mothers and are capable of transmitting the infection to naïve hosts. It was not demonstrated presence (PCR or blood smear) of A. marginale in either larvae from engorged ticks incubated at 18 ºC nor steers infested with them.

Discussion Intrastadial and transstadial transmission of A. marginale during the vector parasitic stages have been well documented in Dermacentor and Rhipicephalus ticks(4,32,33). The role of R. microplus ticks as the most important biological vector of Anaplasma marginale in areas where Dermacentor ticks are not present has also been documented(4). Efforts to document 125

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transovarian transmission however, have been carried without success or have been inconclusive. Step-wise infestations on splenectomized calves with unfed R. microplus larvae from engorged ticks fed on cattle infected with Babesia bovis, B. bigemina, A. marginale and other blood-borne pathogens were carried in Madagascar(34). Patent infection was demonstrated with B. bovis and B. bigemina but not with A. marginale, in these splenectomized calves. In two different studies carried in Australia, unfed larvae hatched from acquisition-fed engorged ticks were used only four days or, four and 15 d after hatching respectively(23,35); in both cases, engorged females were incubated at 28 ºC to complete oviposition. Infection with A. marginale was not corroborated in either of these works. A study carried in Colombia(36), reported transmission of anaplasmosis to naïve 6 mo-old calves by larvae hatched from experimentally acquisition-fed ticks. These authors reported that transmission also occurred when the second-generation larvae were infested on a non-splenectomized steer. The cattle housing conditions for this study however were not fully described. Recently, authors in Brazil(26) documented the presence of A. marginale DNA in larvae progeny of engorged ticks collected from anaplasmosis endemic paddocks and unfed larvae from experimentally acquisition-fed females engorged on Anaplasma infected calves. These authors however showed no evidence of infestation of susceptible cattle with msp5 PCR positive larvae. In order to determine transovarial transmission of A. marginale, a range of conditions have been reported for oviposition, length of maturation of “infected larvae”, variable values of observable rickettsemia both in naturally or experimentally infected donors, use of intact and splenectomized recipients of unfed larvae and even locations where the studies were conducted. In order to guaranty that the animals were free of A. marginale, they were purchased from a tick-free area and were PCR and serology tested at purchase and right before infection or infestation. Housing conditions for the experimental steers in this study precluded transmission of the rickettsia amongst themselves or from the carrier steer (027) by flies or ticks. In an attempt to replicate natural conditions, a bovine carrier with no detectable rickettsemia fed ticks at the moment of feed-acquisition of progenitor ticks. Conventional 28 ºC and low 18 ºC temperatures for oviposition were chosen, as there were reports, that transmission could occur at any of these temperatures(26). The original hypothesis postulated that incubation of engorged ticks at 18 ºC lengthened the oviposition period in such a manner that allowed A. marginale to reach and infect the ovary and therefore the progeny as well. Consistent with previous results, incubation at 18 ºC lengthened the oviposition period twofold compared to conventional 28 ºC incubation(37). It was also confirmed the presence of A. marginale DNA in the progeny from acquisition-fed ticks incubated at 28 ºC, but not in larvae from ticks incubated at 18 ºC however. Consistent 126

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with the presence of A. marginale DNA in these larvae, it was found that one of the two steers infested with larvae from ticks incubated at 28 ºC developed observable rickettsemia on blood smears (6964) 2 d after splenectomy. Steer 6963 also infested with the same larvae, was msp5 nPCR positive. It was hypothesized that infestation with larvae from ticks incubated at 18 ºC would transmit the rickettsia yet the present results show that these larvae failed to induce patent rickettsemia while infestation with larvae from incubation at 28 ºC did. The results however are consistent, with others who used larvae from females engorged on infected cattle and achieved infection to susceptible 6-mo-old cattle(36). It is unknown why transmission was achieved only from larvae hatched from females incubated at 28 ºC and not from those from mothers incubated at 18 ºC, yet the evidence from these and other studies where transmission has failed or achieved infection seem to point towards a phenomenon that may occur under the influence of many variables, including the tick strain, the rickettsial strain and very likely, the genetic makeup of the host and not only from the temperature at which the engorged ticks oviposit their eggs. This is the first study in which the presence of A. marginale DNA in larvae and infested naïve cattle was characterized as the same, indicating that transmission from unfed larvae to susceptible cattle occurred. The possibility of using a 73 β β β γ msp1α strain facilitated the follow up of the infection along the experiment. Our results confirmed that Tlapacoyan-2 was the same organism in the carrier, larvae and steers in these experiments. In light of previous evidence, these results provide additional support for the contention that Anaplasma marginale is transovarially transmitted through R. microplus ticks and that these larvae were capable of transmitting the rickettsia to the mammalian host. There are still many questions to answer; more studies will have to be carried to respond them. In the meantime, and based on these results it is important that transovarian transmission of Anaplasma marginale be considered within the A. marginale life cycle.

Acknowledgements The National Institute for Research on Agriculture, Forestry and Livestock (INIFAP) under agreement SIGI 1128119998 and the National Council for Science and Technology (CONACyT), agreement number 168167, funded this work. The funding sources provided financial support for the conduction of research and preparation of the manuscript. The contents of the manuscript however are the authors’ sole responsibility, solely to 127

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acknowledge this fact. We graciously acknowledge to Dr. Enrique Reynaud Garza from The Instituto de Biotecnología, National University of Mexico for the use of his acclimatized room.

Literature cited: 1. Brites-Neto J, Duarte KM, Martins TF. Tick-borne infections in human and animal population worldwide. Vet World 2015;8(3):301-15. 2. de la Fuente J, Estrada-Pena A, Venzal JM, Kocan KM, Sonenshine DE. Overview: Ticks as vectors of pathogens that cause disease in humans and animals. Front Biosci 2008;13:6938–6946. 3. Rodriǵ uez-Vivas RI, Grisi L, Pérez de León AA, Silva-Villela H, Torres-Acosta JF, Fragoso Sánchez H, et al. Potential economic impact assessment for cattle parasites in Mexico. Rev Mex Cienc Pecu 2017;8(1):61-74 4. Aguirre DH, Gaido AB, Vinabal AE, De Echaide ST, Guglielmone AA. Transmission of Anaplasma marginale with adult Boophilus microplus ticks fed as nymphs on calves with different levels of rickettsaemia. Parasite 1994;1(4):405-407. 5. Mahoney DF, Mirre GB. The selection of larvae of Boophilus microplus infected with Babesia bovis (syn B. argentina). Res Vet Sci 1977;23(1):126-127. 6. Rodríguez SD, García-Ortiz MA, Jiménez-Ocampo R, Vega-y-Murguía CA. Molecular epidemiology of bovine anaplasmosis with a particular focus in Mexico. Infect Genet Evol 2009;9:1092–1101. 7.

Aubry P, Geale DW. A review of bovine anaplasmosis. Transbound Emerg Dis 2011;58:1–30.

8. Kocan KM, de la Fuente J, Blouin EF, Coetzee JF, Ewing SA. The natural history of Anaplasma marginale. Vet Parasitol 2010;167(2-4):95-107. 9. Allen PC, Kuttler KL, Amerault TE. Clinical chemistry of anaplasmosis: blood chemical changes in infected mature cows. Am J Vet Res 1981;42(2):326-328. 10. Carreño AD, Alleman AR, Barbet AF, Palmer GH, Noh SM, Johnson CM. In vivo endothelial cell infection by Anaplasma marginale. Vet Pathol 2007;44(1):116-118. Erratum in: Vet Pathol 2007;44(3):427. 11. Magonigle RA, Newby TJ. Elimination of naturally acquired chronic Anaplasma marginale infections with a long-acting oxytetracycline injectable. Am J Vet Res 1982;43(12):2170-2172. 128

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12. Reinbold JB, Coetzee JF, Hollis LC, Nickell JS, Riegel C, Olson KC, et al. The efficacy of three chlortetracycline regimens in the treatment of persistent Anaplasma marginale infection. Vet Microbiol 2010;145:69-75. 13. Palmer GH, Brayton KA. Antigenic variation and transmission fitness as drivers of bacterial strain structure. Cell Microbiol 2013;15(12):1969-1975. 14. Reinbold JB, Coetzee JF, Hollis LC, Nickell JS, Riegel CM, Christopher JA, et al. Comparison of iatrogenic transmission of Anaplasma marginale in Holstein steers via needle and needle-free injection techniques. Am J Vet Res 2010;71:1178-1188. 15. Scoles GA, Broce AB, Lysyk TJ, Palmer GH. Relative efficiency of biological transmission of Anaplasma marginale (Rickettsiales: Anaplasmataceae) by Dermacentor andersoni (Acari: Ixodidae) compared with mechanical transmission by Stomoxys calcitrans (Diptera: Muscidae). J Med Entomol 2005;42(4):668-675. 16. Futse JE, Ueti MW, Knowles DP Jr, Palmer GH. Transmission of Anaplasma marginale by Boophilus microplus: retention of vector competence in the absence of vectorpathogen interaction. J Clin Microbiol 2003;41(8):3829-3834. 17. Kocan KM, Goff WL, Stiller D, Edwards W, Ewing SA, Claypool PL, et al. Development of Anaplasma marginale in salivary glands of male Dermacentor andersoni. Am J Vet Res 1993;54(1):107-112. 18. Ueti MW, Reagan JO Jr, Knowles DP Jr, Scoles GA, Shkap V, Palmer GH. Identification of midgut and salivary glands as specific and distinct barriers to efficient tick-borne transmission of Anaplasma marginale. Infect Immun 2007;75(6):2959-2964. 19. Scoles GA, Ueti MW, Noh SM, Knowles DP, Palmer GH. Conservation of transmission phenotype of Anaplasma marginale (Rickettsiales: Anaplasmataceae) strains among Dermacentor and Rhipicephalus ticks (Acari: Ixodidae). J Med Entomol 2007;44(3):484-491. 20. Dalgliesh RJ, Stewart NP. The use of tick transmission by Boophilus microplus to isolate pure strains of Babesia bovis, Babesia bigemina and Anaplasma marginale from cattle with mixed infections. Vet Parasitol 1983;13(4):317-323. 21. Mora C, Pérez M, García-Ortiz MA, Rojas-Ramírez EE, Preciado-de -la-Torre JF, Hernández R, et al. Evaluación de la transmisión de dos cepas mexicanas de Anaplasma marginale por la garrapata Boophilus microplus, in: XIII Congreso Lationamericano de Buiatría. 2007:241-245. 22. Mason CA, Norval RAI. The transfer of Boophilus microplus (Acarina: Ixodidae) from infested to uninfested cattle under field conditions. Vet Parasitol 1981;8:185-188. 129

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23. Connell M, Hall WT. Transmission of Anaplasma marginale by the cattle tick Boophilus microplus. Aust Vet J 1972;48(8):477. 24. Piercy PL. Transmission of anaplasmosis. Ann NY Acad Sci 1956;64:40-48. 25. Stich RW, Kocan KM, Palmer GH, Ewing SA, Hair JA, Barron SJ. Transstadial and attempted transovarial transmission of Anaplasma marginale by Dermacentor variabilis. Am J Vet Res 1989;50(8):1377-1380. 26. Shimada MK, Yamamura MH, Kawasaki PM, Tamekuni K, Igarashi M, Vidotto O, et al. Detection of Anaplasma marginale DNA in larvae of Boophilus microplus ticks by polymerase chain reaction. Ann N Y Acad Sci 2004;1026:95-102. 27. Jiménez-Ocampo R, Vega y Murguía CA, Oviedo N, Rojas-Ramírez EE, García-Ortiz MA, Preciado-de-la-Torre JF, et al. Genetic diversity of the msp1 gene variable region and msp4 gene of Anaplasma marginale strains from Mexico. Rev Mex Cienc Pecu 2012;3:373-387. 28. Gaxiola-Camacho S, García-Vázquez Z, Cruz-Vázquez C, Portillo-Loera J, VázquezPeláez C, Quintero-Martínez MT, et al. Comparison of efficiency and reproductive aptitude indexes between a reference and field strains of the cattle tick Rhipicephalus (Boophilus) microplus, in Sinaloa, Mexico. Rev Bras Parasitol Vet 2009;18(4):9-13. 29. Merino O, Antunes S, Mosqueda J, Moreno-Cid JA, Pérez de la Lastra JM, Rosario-Cruz R, et al. Vaccination with proteins involved in tick-pathogen interactions reduces vector infestations and pathogen infection. Vaccine 2013;31(49):5889-5896. 30. Torioni de Echaide S, Knowles DP, McGuire TC, Palmer GH, Suarez CE, McElwain TF. Detection of cattle naturally infected with Anaplasma marginale in a region of endemicity by nested PCR and a competitive enzyme-linked immunosorbent assay using recombinant major surface protein 5. J Clin Microbiol 1998;36(3):777-782. 31. Palmer GH, Knowles DP Jr, Rodriguez JL, Gnad DP, Hollis LC, Marston T, et al. Stochastic transmission of multiple genotypically distinct Anaplasma marginale strains in a herd with high prevalence of Anaplasma infection. J Clin Microbiol 2004;42(11):5381-5384. 32. Corrier DE, Kuttler KL, Terry MK. Observations on anaplasmosis following field exposure to heavy and light infestations with Boophilus microplus. Vet Parasitol 1983;13,187-190. 33. Rogers RJ, Shiels IA. Epidemiology and control of anaplasmosis in Australia. J S Afr Vet Assoc 1979;50(4):363-366.

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34. Uilenberg G [Note on babesisasis and anaplasmosis in cattle on Madagascar. I. Introduction. Transmission]. Rev Elev Med Vet Pays Trop 1968;21(4):467-474. 35. Leatch G. Preliminary studies on the transmission of Anaplasma marginale by Boophilus microplus. Aust Vet J 1973;49:16-19. 36. López-Valencia G, Vizcaíno-Gerdts O. Transmisión transovárica de Anaplasma marginale por la garrapata Boophilus microplus. Rev ICA Colombia 1992;27:437-443. 37. Esteves E, Pohl PC, Klafke GM, Reck J, Fogaça AC, Martins JR, et al. Low temperature affects cattle tick reproduction but does not lead to transovarial transmission of Anaplasma marginale. Vet Parasitol 2015;214(3-4):322-326.

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https://doi.org/10.22319/rmcp.v11i1.4981 Article

Inclusion of concentrate and growth promoters’ additives in sheep diets on intake, digestibility, degradability, ruminal variables and nitrogen balance

Marcelo Vedovatto a Camila da Silva Pereira a João Artêmio Marin Beltrame a Ibrahin Miranda Cortada Neto a Anderson Luiz de Lucca Bento a Gabriella de Oliveira Dalla Martha a Maria da Graça Morais a Gumercindo Loriano Franco a*

Universidade Federal de Mato Grosso do Sul, Faculdade de Medicina Veterinária e Zootecnia. Campo Grande/MS, Brazil.

* Corresponding author: gumercindo.franco@ufms.br

Abstract: This study evaluated the inclusion of concentrate and monensin, salinomycin and flavomycin in sheep diets on intake, digestibility, in situ degradability, ruminal variables and nitrogen balance. Five sheep in a latin square received the treatments: HAY (hay only), CONT (hay + concentrate), MON (hay + concentrate + monensin), SALI (hay + concentrate + salinomycin), and FLAV (hay + concentrate + flavomycin). Hay was offered ad libitum, concentrate, 20 g kg-1 of body weight (BW), and additives, 0.75 mg kg-1 of BW. The treatments with the concentrate (CONT, MON, SALI and FLAV) showed increased (P≤0.05) on intake, digestibility, total VFA, propionate and butyrate proportions, N-NH3, and nitrogen balance, and decreased (P≤0.05) DM and NDF degradability, acetate proportion, acetate:propionate ratio, and rumen pH compared to the HAY. The comparison between the outcome effects from additives with the CONT

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showed that the acetate proportion and acetate:propionate ratio was only reduced by MON (P≤0.05). MON and SALI increased (P≤0.05) the propionate proportion. The proportion of butyrate was increased with the inclusion of FLAV and reduced with MON 8and SALI. Only MON reduced the production of N-NH3 (P≤0.05). Other variables showed no effects from additives (P>0.05) in relation to the CONT. The inclusion of the concentrate in sheep diets caused alterations on intake, digestibility, ruminal variables (VFA, pH, and N-NH3) and nitrogen balance. However, the additives only altered the ruminal variables (VFA and N-NH3) and the greatest effects were observed with MON. Key words: Bambermycin, Flavomycin, Monensin, Ruminants, Salinomycin.

Received: 11/07/2018 Accepted: 06/02/2019

Introduction The evolution of the knowledge of the nutritional requirements of sheep, to obtain high productive performance, has led to the use of feedlot diets, that are formulated with high levels of concentrate, and small levels of roughage ingredients(1). The provision of concentrates affects ruminal fermentation(2) and, high levels of inclusion have been associated with the occurrence of nutritional disturbances, mainly acidosis(3). Growth promoters additives, have shown the potential to modulate ruminal fermentation, reflecting in high productive performance, in addition to reducing risks of nutritional disturbances. The class of ionophores is most commonly used as growth promoters, for animals of zootechnical interest. Although more than 120 antibiotics belong to this class, monensin is probably the most researched and used additive in ruminant diets(4). Similarly, salinomycin also belongs to the ionophore class, and is widely researched and used. According to Edwards et al(5) other non-ionophore antibiotics, such as flavomycin, have proved to be beneficial in altering ruminal fermentation and have been used as an additive. The beneficial alteration caused by ionophores in the rumen occurs because they act on Gram-positive bacteria, fungi and protozoa, and thus enable better conditions for Gramnegative bacteria to develop(6). These alterations in the rumen’s microbiology reflect in lower production of methane, ammonia, and acetic and butyric acids. Propionic acid production is increased, so there is an increase in energy efficiency and this reflects increasing the weight gain or feed efficiency of ruminants(7).

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Flavomycin has a mechanism of action different from ionophores, and its microorganism selectivity is different. It does not act on all species of Gram-positive bacteria, and has no effect on fungi and protozoa(5). This additive has been shown as efficient for increasing the weight gain or feed efficiency in ruminants(8,9), however, its effect on ruminal fermentation is not fully understood. Thus, this study evaluated the effects of the inclusion of concentrate, and compared the effects of the addition of monensin, salinomycin and flavomycin in sheep diets on intake, digestibility, in situ degradability, ruminal variables (pH, N-NH3 and VFA), and nitrogen balance.

Material and methods Experimental site and animal care

The experiment was conducted at Animal Metabolism Laboratory of Faculdade de Medicina Veterinária e Zootecnia, Universidade Federal de Mato Grosso do Sul (Campo Grande, Mato Grosso do Sul, Brazil). The experiment was conducted according to the institutional Ethics Committee on Animal Use under case no.: 577/2013.

Animals, management and treatments

Five male sheep (½ Suffolk + ½ Santa Ines) with a permanent cannula inserted in the rumen and, initial mean body weight (BW) of 46.50 ± 5.45 kg were used in the study. The sheep were housed in special cages for metabolism studies that are suitable for in vivo digestibility assays. These cages had a slatted wood floor and contained a feeder, drinking fountain, and a galvanized steel supplement for urine collection. The cages were housed in a covered shed with good ventilation. The animals were fed with chopped Coast-cross hay (Cynodon dactylon (L.) Pers.) and concentrate (Table 1). The concentrate formulation contained fine ground corn (700 g kg-1), soybean meal (260 g kg-1) and mineral premix (40 g kg-1). The experimental treatments included growth promoters additives in the concentrate as follows: HAY (hay only); CONT (hay + concentrate); MON (hay + concentrate + monensin), SALI (hay + concentrate + salinomycin), and FLAV (hay + concentrate + flavomycin). Hay was offered ad libitum, concentrate in the amount of 20 g kg-1 of BW, and additives 0.75 mg kg-1 of BW.

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Table 1: Chemical composition of the concentrate and Coast-Cross hay (Cynodon dactylon (L.) Pers.) DM (g kg-1)

Item 2

Concentrate Hay

870 875

Chemical composition (g kg-1 of DM)1 OM CP aNDFom EE NSC 904 188 214 24 479 936 69 732 15 119

Ashes 96 64

DM= dry matter; OM= organic matter; CP= crude protein; aNDFom= neutral detergent fiber with amylase and corrected for ashes; EE= ethereal extract; NSC= nonstructural carbohydrates (100- (Ashes + CP + aNDFom + EE; Sniffen et al(10)). 2 Formulation contained fine ground corn (700 g kg-1), soybean meal (260 g kg-1) and mineral premix (40 g kg-1).

The additives were weighed on an analytical balance and stored in microtubes until use. Hay and concentrate were provided in separate troughs. The hay and concentrate were provided in two meals a day, at 0007 and 0017 h. Hay intake was adjusted to provide orts of 150 g kg-1. Additives were provided only with the morning meal and mixed with the concentrate. The amount of hay and concentrate met the nutritional requirements of growing sheep with an average daily gain of 250 g d-1(1). The experimental design was a 5 x 5 latin square. Five experimental periods of 21 d each were performed as 10 d of adaptation to treatments and 11 d of data collection. At each new experimental period, the animals were weighed after 16-h solids fasting to adjust the amounts of concentrate and additive.

Intake control and collection of feces and urine

The control of daily intake of feed and water was performed between d 11 and 15 of each experimental period by weighing the amounts of feed offered and orts. Feces and urine were collected in the same period. Water intake was controlled by measuring the quantity supplied in the morning and afternoon. Orts water was measured in the drinking fountains only in the mornings. A control drinking fountain (without animal access) was also used to measure evaporation during the day in order to assess actual water intake in the experiments. A feces collecting bag was adapted to animals to allow total collection of feces. These bags were emptied daily in the morning and afternoon at the same times. Feces were weighed, homogenized, and samples equivalent to 100 g kg-1 were stored (-20 ºC) for further analysis. Based on this information, the following parameters were evaluated: intake (offered – orts), apparent digestibility coefficients (nutrient intake – excreted nutrient/nutrient intake) of DM, OM, CP, neutral detergent fiber corrected for ashes with the use of amylase (aNDFom), ethereal extract (EE), and NSC. The TDN were estimated by the formula proposed by Sniffen et al(10): TDN= digestible CP + digestible aNDFom + 2.25 * digestible EE + digestible NSC.

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In addition to the feces, urine was collected for the evaluation of nitrogen balance. Urine was collected in buckets containing 100 mL of sulfuric acid (100 mL L-1) placed in the lower part of urine collectors in the metabolic cages. These buckets were emptied daily in the morning and afternoon at the same time. Samples of 100 ml L-1were collected and stored (-20 °C). For nitrogen (N) balance analysis, absorbed N was calculated by the difference between N intake and excreted in the feces, while the N retained was obtained by the difference between N intake and excreted in feces and urine.

Measurement of in situ degradability

The ruminal degradability of DM and NDF was determined from d 16 to 19 of each period using 5 x 5 cm nylon bags with a porosity of 50 μm, sealed at the edges and properly identified. These bags were weighed empty, filled with 2.5 g of hay (ground and passed through a 2 mm pore sieve), and tied with a rubber band to a metal ring to keep them closed. These bags were first soaked in water for one hour and subsequently attached to a metal chain and anchor weighing approximately 100 g. These bags were subsequently infused into the rumen via cannula at 0007 h (before feeding) and removed after the incubation times (3, 8, 16, 24, 48, 72 and 96 h). These bags were immersed in ice water immediately after removal from the rumen and washed in a washing machine for five minutes for three cycles, changing the water in each cycle. They were subsequently placed in a forced air ventilation oven at 55 ºC for 72 h and weighed after this period. The DM soluble fraction from hay was determined with nylon bags with samples without incubation in the rumen. These bags were kept in water (38 °C) for one hour, washed in a washing machine, oven dried, and weighed. The difference between the initial and final weight was considered as the soluble fraction for each experimental period, which corresponds to the value at 0 h in the DM degradation curve. The soluble fraction “a”, insoluble fraction “b”, rate of degradation “c”, and effective degradability (ED) were calculated according to Ørskov and McDonald(11) with the equation ED = a + (bxc) / (c + k), where “k” is the estimated rumen solids passage rate calculated as 0.02, 0.05, and 0.08 h-1 in the present study.

Collection of ruminal liquid samples and pH

Ruminal liquid samples were collected for the determination of VFA, pH, and N-NH3 from d 20 to 21 in each experimental period. The samples were collected at the end of the experimental period after removal of the nylon bags. At the collection time, samples were taken at zero hours (before supplementation) and at 2, 4, 8, 10, 12, 14, 16, 18, 20, 22 and 24 h after feeding in the morning and always following the same sequence among 136

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animals. The ruminal fluid collection was performed with the help of a metal shell inserted in a cloth diaper. An aliquot of approximately 100 mL of ruminal fluid was collected. The pH was measured immediately after the collection of ruminal liquid using a digital potentiometer (B474; Micronal, São Paulo, SP, Brazil). The VFA analysis used four mL of ruminal fluid acidified with 1 mL of metaphosphoric acid (25 %) and stored at -20 °C. The N-NH3 analysis used 50 mL of ruminal liquid acidified with 1 mL of H2SO4 (50 %) and stored at -20 °C.

Chemical analysis

The analysis of the chemical composition of feeds, orts, and feces was conducted according to AOAC(12) as follows: DM - method 967,03; CP- method 981,10; Ashes method 942,05; and EE – method 920,29. The NDF content was analyzed in a Tecnal TE149® fiber analyzer (Tecnal, Piracicaba, SP, Brazil) using 5 X 5 cm non-woven fabric (NWF) bags with 100 μm porosity. To these were added 0.5 g of sample (feed or faeces) and followed for neutral detergent analysis according to the methodology of Van Soest et al(13) without sodium sulfite and using thermostable amylase (Termamyl 120 L Novozymes A/S, Bagsvaerd, Denmark). Subsequently, the NDF was corrected for ashes and the aNDFom content was calculated. The same procedure used for the NDF was used to analyze the material resulting from the in situ ruminal degradation but without the use of amylase and correction for ashes. The NSC content was calculated as proposed by Sniffen et al(10) with the equation: NSC= 100 - (CP + ashes + aNDFom + EE). The N-NH3 content analysis used the supernatant of ruminal liquid samples thawed at 4 ºC and distillation with 2N KOH according to Ribeiro et al(14). The concentration of VFAs was determined by gas chromatography (Shimadzu GC-2010, Kyoto, Japan) according to the methodology described by Erwin et al(15).

Statistical analyses

Statistical analyses were performed using the SAS statistical software (SAS Inst., Inc., Cary, NC). The data of intake, apparent digestibility and nitrogen balance were analyzed using ANOVA with a 5 x 5 latin square design. The statistical model used was: Yijk = μ + Ti + Pj + Ak + eijk

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Where: Yijk = observation of the effect of treatment i in period j, of animal k, where μ is the overall mean, Ti = effect of treatment i, where i = 1 (HAY), 2 (CONT), 3 (MON), 4 (SALI), and 5 (FLAV); Pj = effect of period j (j = 5 periods); Ak = effect of animal k (k = 5 animals), and eijk = random error associated with each observation. The model for the in situ degradation rate included the experimental treatment, incubation time, animal, period, and treatment × time. The experimental design was the latin square with subdivided plots for the ruminal variables data (VFA, pH, and N-NH3), where the plots were the treatments and subplots were ruminal liquid samples. The statistical model included treatment effects, sampling times, animal, period, and treatment × time. The statistical model used was: Yijk = μ+ Ti + Hj + Ak + Pj + (TH)ij + eijkl Where: Yijkl = observation of the effect of treatment i per hours of incubation (rate of degradation) or collection time (ruminal parameters) j in animal k; μ = overall mean; Ti = effect of treatment (i = 1 (Hay), 2 (CONT), 3 (MON), 4 (SALI), and 5 (FLAV); Hj = effect of incubation hours for degradability (j = 1,....., 7) or collection times for ruminal parameters (j = 1, ....., 13); Ak = animal effect (k= 1, ..., 5), Pj = the period effect (j= 1, ....., 5); THij = interaction between treatment i and time j; and eijkl= random error associated with each observation. When significant (P≤0.05) F-statistics were noted, means were separated using a multiple comparison test (Tukey’s method) and treatment differences were considered significant at P≤0.05.

Results The supply of concentrate with or without additives (CONT, MON, SALI, and FLAV) affected the intake (P≤0.05) of DM, OM, and nutrients in kg day-1 or g kg-1of BW when compared to the treatment HAY (Table 2). The animals of the HAY treatment showed higher (P≤0.05) DM and nutrients intake from hay, however, their total DM and total nutrient intake was lower (P≤0.05) than those receiving the treatments with the concentrate. The inclusion of concentrate did not show a significant difference (P>0.05) on total aNDFom and EE (g kg-1 of BW). No effects of the inclusion of MON, SALI, and FLAV in the diet was observed (P>0.05) on the intake of hay DM, total DM, and nutrients in kg d-1 or g kg-1of BW. The water intake increased (P≤0.05) with the addition of concentrate in the diets, however, no effect was observed from the use of additives. 138

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Table 2: Effect of the inclusion of concentrate and antimicrobial growth promoters’ additives in sheep diet on intake of DM, OM, CP, aNDFom, EE, NSC, and ashes of hay and total diet (hay + concentrate) Treatments2 Intake of1 SEM P-value HAY CONT MON SALI FLAV kg day-1 DM Hay 1.01a 0.68b 0.65b 0.73b 0.65b 0.050 0.0018 a b b b b DM Total 1.01 1.56 1.57 1.62 1.54 0.070 0.0004 a b b b b OM Hay 0.95 0.64 0.61 0.68 0.62 0.047 0.0021 a b b b b OM Total 0.95 1.43 1.44 1.49 1.42 0.065 0.0005 a b b b b CP Hay 0.08 0.05 0.05 0.05 0.05 0.004 0.0006 CP Total 0.08a 0.22b 0.22b 0.22b 0.22b 0.008 ≤0.0001 a b b b b aNDFom Hay 0.74 0.49 0.47 0.53 0.48 0.037 0.0023 aNDFom Total 0.74 0.68 0.67 0.72 0.67 0.042 0.7163 EE Hay 0.01 0.01 0.01 0.01 0.01 0.002 0.5565 b a a a a EE Total 0.01 0.03 0.03 0.03 0.03 0.002 ≤0.0001 a b b b b NSC Hay 0.12 0.08 0.08 0.09 0.08 0.006 0.0053 a b b b b NSC Total 0.12 0.50 0.52 0.51 0.51 0.019 ≤0.0001 a b b b b Ashes Hay 0.06 0.04 0.04 0.05 0.04 0.003 0.0002 a b b b b Ashes Total 0.06 0.13 0.13 0.13 0.13 0.005 ≤0.0001 -1 a b b b b Water (L day ) 2.44 3.74 4.03 4.06 3.86 0.192 0.0003 -1 g kg of BW DM Hay 19.23a 13.44b 12.45b 14.69b 12.93b 1.209 0.0150 a b b b b DM Total 19.23 30.80 29.83 32.10 30.33 1.223 ≤0.0001 a b b b b OM Hay 18.02 12.62 11.68 13.76 12.13 1.150 0.0168 a b b b b OM Total 18.02 28.30 27.38 29.49 27.85 1.155 0.0001 a b b b b CP Hay 1.42 1.07 0.93 1.10 0.99 0.073 0.0056 a b b b b CP Total 1.42 4.33 4.2 4.37 4.27 0.073 ≤0.0001 a b b b b aNDFom Hay 14.07 9.75 9.08 10.65 9.37 0.905 0.0161 aNDFom Total 14.07 13.46 12.79 14.37 13.05 0.915 0.7349 EE Hay 0.30 0.21 0.21 0.25 0.18 0.024 0.0533 a b b b b EE total 0.30 0.61 0.62 0.66 0.59 0.028 ≤0.0001 a b b b b NSC Hay 2.23 1.59 1.45 1.76 1.58 0.164 0.0450 a b b b b NSC Total 2.23 9.89 9.77 10.08 9.94 0.165 ≤0.0001 a b b b b Ashes Hay 1.22 0.83 0.78 0.94 0.80 0.063 0.0028 a b b b b Ashes Total 1.22 2.49 2.45 2.61 2.48 0.070 ≤0.0001 -1 Water (ml kg of BW) 45.35a 74.77b 76.11b 80.06b 76.37b 3.166 ≤0.001 1

DM= dry matter; OM= organic matter; CP= crude protein; aNDFom= neutral detergent fiber with amylase and corrected for ashes; EE= ethereal extract; NSC= nonstructural carbohydrates (100- (Ashes + CP + aNDFom + EE; Sniffen et al(10)). 2 Treatments: HAY (hay only), CONT (hay + concentrate), MON (hay + concentrate + monensin), SALI (hay + concentrate + salinomycin), FLAV (hay + concentrate + flavomycin). ab Means followed by different letters in the same row are significantly different (Tukey, P≤0.05).

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The treatments with concentrate showed higher (P≤0.05) DM, OM, CP, EE, and NSC digestibility when compared to the treatment HAY (Table 3). No difference (P>0.05) in aNDFom digestibility was observed resulting in an increase in total digestible nutrients (TDN). The inclusion of additives (MON, SALI, and FLAV) did not affect the digestibility of DM, OM, EE, aNDFom, NSC, EE, and TDN when compared to the CONT group (P>0.05). Table 3: Effect of the inclusion of concentrate and antimicrobial growth promoters’ additives in sheep diet on the apparent digestibility coefficients of DM, OM, CP, EE, aFDNom, and NSC 2 Treatments Digestibility of1 SEM P-value HAY CONT MON SALI FLAV DM (fraction 0–1) 0.54a 0.67b 0.67b 0.64b 0.66b 0.028 0.0305 -1 Digestible amount (g kg DM ) OM 563.69a 685.58b 700.04b 664.79b 700.15b 24.418 0.0142 CP 636.25a 819.29b 803.30b 756.69b 852.49b 29.610 0.0036 EE 498.05a 723.88b 782.96b 786.39b 674.80b 41.600 0.0027 aNDFom 530.03 420.43 416.17 438.04 427.30 49.845 0.2004 NSC 507.27a 883.04b 877.02b 871.69b 888.30b 23.749 ≤0.0001 TDN 519.70a 618.92b 616.82b 610.36b 628.44b 24.335 0.0197 1

DM= dry matter; OM= organic matter; C= crude protein; aNDFom= neutral detergent fiber with amylase and corrected for ashes; EE= ethereal extract; NSC= nonstructutal carbohydrates (100- (Ashes + CP + aNDFom + EE; Sniffen et al(10)). 2 Treatments: HAY (hay only), CONT (hay + concentrate), MON (hay + concentrate + monensin), SALI (hay + concentrate + salinomycin), FLAV (hay + concentrate + flavomycin). ab Means followed by different letters in the same row are significantly different (Tukey, P≤0.05).

The in situ disappearance rates of DM (Figure 1A) and NDF (Figure 1B) of hay were influenced by the experimental treatments and incubation times (P≤0.05). The in situ disappearance rates of DM and NDF at 3, 8, and 96 h of incubation did not show a significant difference between treatments. However, the treatment HAY only at 16, 24, 48, and 72 h of incubation showed disappearance rates higher than those in treatments with the concentrate. Comparing the influence of additives in relation to the CONT group, no difference was observed in the disappearance rate of DM and NDF (P>0.05). The HAY treatment presented potential DM and NDF degradation at 48 h of incubation. Conversely, this was observed in treatments with the concentrate at 72 h.

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Figure 1: Disappearance of dry matter (DM) (figure A) and neutral detergent fiber (NDF) (figure B) of hay (expressed as a fraction of 0-1) in the rumen of sheep

A a

Hours 16, 24, 48 and 72: HAYa, CONTb, MONb, SALIb, FLAVb (P ≤ 0.05). Potential deg. HAY: 48 h (P ≤ 0.05). Potential deg. CONT, MON, SALI and FLAV: 72 h (P ≤ 0.05).

2 3 HAY (hay only), CONT (hay + concentrate), MON (hay + concentrate + monensin), SALI (hay + concentrate + salinomycin), FLAV (hay + concentrate + flavomycin). Vertical bars represent the standard deviation; Potential deg: represents the incubation time of hay needed to achieve potential degradation.

For the ruminal variables of hay DM degradation, the inclusion of concentrate in the diet reduced (P≤0.05) the fraction "b" and the ED calculated at 0.02 and 0.05 h-1 and did not change (P>0.05) the "c" fraction and the ED calculated at 0.08 h-1 (Table 4). The inclusion of concentrate reduced (P≤0.05) fraction “c” and the calculated ED (at 0.02, 0.05, and

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0.08 h-1; P≤0.05) and did not change fraction “b” in the ruminal variables of Hay NDF degradation. The additives did not change these variables.

Table 4: Effect of the inclusion of concentrate and antimicrobial growth promoters’ additives in sheep diet on the estimation of the ruminal parameters of DM and NDF degradation of hay (values are expressed as the fraction of 0-1) Parameters1

Treatments2 HAY

SEM

P-value

CONT

MON

SALI

FLAV

0.482a 0.445ab

0.426b

0.452ab

0.454ab

0.009

0.0112

0.055

0.035

0.034

0.039

0.008

0.2723

ED (0.02 h-1)

0.709a 0.659ab

0.613b

0.625b

0.653ab

0.019

0.0146

ED (0.05 h-1)

0.565a 0.521ab

0.471b

0.477b

0.505ab

0.020

0.0456

ED (0.08 h-1)

0.486

0.450

0.402

0.406

0.430

0.020

0.0679

0.573

0.555

0.533

0.557

0.584

0.013

0.1810

0.048a 0.033ab

0.032ab 0.028b

0.032ab

0.004

0.0289

ED (0.02 h-1)

0.401a 0.347ab

0.324b

0.320b

0.363ab

0.017

0.0359

ED (0.05 h-1)

0.277a 0.223ab

0.205b

0.198b

0.231ab

0.015

0.0277

ED (0.08 h-1)

0.212a 0.164ab

0.150b

0.143b

0.169ab

0.013

0.0252

DM (a=0.210)

0.050

NDF

DM= dry matter; a= soluble fraction; b= insoluble fraction potentially degradable; c= degradation rate (/h); ED= effective degradation (considering a degradation rate of 0.02, 0.05, and 0.08 h-1), NDF= neutral detergent fiber. 2 Treatments: HAY (hay only), CONT (hay + concentrate), MON (hay + concentrate + monensin), SALI (hay + concentrate + salinomycin), FLAV (hay + concentrate + flavomycin). ab Means followed by different letters in the same row are significantly different (Tukey, P≤0.05).

Table 5 shows that the HAY treatment showed lower production (P≤0.05) in mmol L-1 of total acetate, propionate, butyrate, and total VFA and higher acetate:propionate ratio when compared to treatments with the concentrate (CONT, MON, SALI, and FLAV). When evaluated in mmol 100 mmol-1, the HAY treatment showed a higher (P≤0.05) proportion of acetate and lower (P≤0.05) of propionate and butyrate when compared to treatments with the concentrate.

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Table 5: Effect of the inclusion of concentrate and antimicrobial growth promoters’ additives in sheep diet on the production of short-chain fatty acids in the rumen P-value2 Treatments1 Item SEM Treat h Treat×h HAY CONT MON SALI FLAV Fatty acids (mmol L-1) Acetate Propionate Butyrate Total VFA

78.30b 90.15a 12.25 4.09

94.64

Acetate:propionate ratio 6.39 Fatty acids (mmol 100 mmol-1) Acetate Propionate

21.37

10.64

122.16 4.21

13.06

17.35

24.98 9.15 a

90.90a

24.14

9.49

89.93a

21.43

0.759

12.08

0.333

3.77

4.19

71.26c

73.15b

21.01

19.14

2.083

118.93 124.53 123.44 3.39

82.61a 73.94b d

84.80a

73.02bc 17.36

≤0.001 ≤0.001 0.4278 ≤0.001 0.0002 0.9995

2.776

≤0.001 0.0262 0.9840 ≤0.001 ≤0.001 0.6340

0.120

≤0.001 0.6263 0.9993

0.478

≤0.001 0.9540 0.9992 ≤0.001 0.6102 1.0000

0.422

Butyrate 4.32 8.7 7.73 7.71 9.62 0.264 ≤0.001 0.6895 0.9996 1 Treatments: HAY (hay only), CONT (hay + concentrate), MON (hay + concentrate + monensin), SALI (hay + concentrate + salinomycin), FLAV (hay + concentrate + flavomycin). 2 Treat= treatment. ab Means followed by different letters in the same row are significantly different (Tukey, P≤0.05). d

Analyzing the effects of the additives (MON, SALI and FLAV) in relation to the CONT in mmol L-1, the acetate production was not altered (P>0.05). MON and SALI increased (P≤0.05) the propionate production in relation to that in the CONT and FLAV did not differ from these. FLAV induced the highest (P≤0.05) production of butyrate, MON the lowest (P≤0.05), and SALI did not differ from the CONT and MON. The total VFA production of the additives did not differ from the CONT. The acetate:propionate ratio was the smallest (P≤0.05) in the MON treatment compared to the other treatments. When evaluated in mmol 100 mmol-1, the MON presented lower (P≤0.05) acetate production than CONT and SALI, but did not differ from FLAV. The CONT, SALI and FLAV groups did not differ. The highest (P≤0.05) proportion of propionate was produced in the MON treatment, followed by the SALI, FLAV, and CONT. The latter two did not differ. The highest (P≤0.05) proportion of butyrate was observed in the FLAV treatment followed by the CONT, MON and SALI. The latter two did not differ. The inclusion of concentrate in the diets reduced (P≤0.05) the ruminal pH in relation to the HAY treatment (Figure 2A) at all evaluated time points. No difference in pH was observed as the result of additives. The use of the concentrate caused a high pH variation throughout the day, with maximum values of 6.46 and minimum of 5.68. The lowest values were observed between 2 and 4 h after feeding. The inclusion of concentrate in the diet increased (P≤0.05) the production of N-NH3 in relation to the HAY treatment at all evaluated time points (Figure 2B). MON was the only additive showing some effect (P≤0.05) compared to the CONT treatment by reducing the N-NH3 concentration only at four hours after the morning feeding. No effect of the other additives was observed for this variable. 143

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Figure 2: Mean values of pH (Figure A) and ammoniacal nitrogen (NH3-N; Figure B) in the rumen of sheep at different collection times

All hours: HAYa, CONTb, MONb, SALIb, FLAVb (P ≤ 0.05).

Hours 0, 2, 6, 8, 10, 12, 14, 16, 18, 20, 22 and 24: HAYb, CONTa, MONa, SALIa, FLAVa (P ≤ 0.05). Hour 4: HAYc, CONTa, MONb, SALIa, FLAVa (P ≤ 0.05).

HAY (hay only), CONT (hay + concentrate), MON (hay + concentrate + monensin), SALI (hay + concentrate + salinomycin), FLAV (hay + concentrate + flavomycin). Vertical bars represent the standard deviation

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The use of the concentrate increased (P≤0.05) nitrogen intake (Table 6) despite the fecal and urine losses, the amount absorbed and retained was higher (P≤0.05) than that observed in the HAY treatment. No significant difference was observed in nitrogen intake with the use of additives.

Table 6: Effect of the inclusion of concentrate and antimicrobial growth promoters’ additives in sheep diet on nitrogen balance Treatments1 Intake of SEM P-value HAY CONT MON SALI FLAV g day-1 N intake - hay 12.18a 8.67b 7.72b 8.79b 7.98b 0.458 0.0001 N intake concentrate 0.00a 26.57b 27.76b 26.73b 27.32b 1.153 ≤0.0001 N intake - total 12.18a 35.24b 35.48b 35.51b 35.30b 1.193 ≤0.0001 N fecal 3.50a 6.34b 5.92b 7.01b 6.41b 0.550 0.0072 N absorbed 8.68a 28.91b 29.56b 28.50b 29.22b 0.838 ≤0.0001 N urinary 3.04a 11.11b 14.42b 12.13b 12.51b 1.181 ≤0.0001 N fecal + urinary 6.54a 17.45b 20.34b 19.15b 18.59b 1.459 0.0001 N retained 5.65a 17.80b 15.14b 16.37b 16.70b 1.444 ≤0.0001 g kg-1 of N intake 706.22 818.70 833.60 803.72 825.92 20.96 a b b b b N absorbed 7 0.0060 52.69 N retained 454.82 501.56 428.58 468.36 471.22 1 0.7101 -1 g kg of BW N intake - hay 0.23a 0.17b 0.15b 0.18b 0.16b 0.011 0.0200 N intake concentrate 0.00a 0.52b 0.52b 0.52b 0.52b 0.002 ≤0.0001 N intake - total 0.23a 0.69b 0.67b 0.70b 0.68b 0.011 ≤0.0001 N fecal 0.07a 0.13b 0.11b 0.14b 0.12b 0.009 0.0012 N absorbed 0.16a 0.57b 0.56b 0.56b 0.56b 0.010 ≤0.0001 N urinary 0.06a 0.22b 0.27b 0.23b 0.24b 0.016 ≤0.0001 N fecal + urinary 0.13a 0.35b 0.38b 0.37b 0.36b 0.019 ≤0.0001 N retained 0.10a 0.35b 0.29b 0.33b 0.32b 0.020 ≤0.0001 1

Treatments: HAY (hay only), CONT (hay + concentrate), MON (hay + concentrate + monensin), SALI (hay + concentrate + salinomycin), FLAV (hay + concentrate + flavomycin). ab Means followed by different letters in the same row are significantly different (Tukey, P≤0.05).

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Discussion Effect of concetrate

The inclusion of concentrate in the diet, increased the intake of MS and nutrients (Table 2). The lowest intake observed in the HAY treatment, could be the result of a ruminal physical limitation in sheep. The hay intake may have caused greater filling and ruminal distension that, according to Grovum(16), provoke inhibitory neural stimulus from the hunger center reducing feed intake. The addition of concentrate, is known to increase the passage rate, providing limiting nutrients, such as nitrogen and sulfur, to ruminal microorganisms and leading to a high rate of multiplication of microorganism(17) and consequently reflecting increased intake. The inclusion of concentrate in the diet, increased the digestibility of DM and other nutrients (with the exception of aNDFom). According to Hagos and Melaku(18), the lowest concentration of CP and highest of aNDFom in the HAY treatment may have reflected low microbial efficiency, leading to a low level of nutrientsâ&#x20AC;&#x2122; fermentation and consequently lower digestibility. The absence of improvement in the aNDFom digestibility as well as the reduction in the degradability of DM and NDF by the inclusion of concentrate may have occurred because the inclusion of rapidly fermentable carbohydrates, leads to a reduction in ruminal pH, and increased development of amylolytic, and decreased development of cellulolytic bacteria(19,20). These microbial alterations reduce the production of fibrolytic enzymes and consequently negatively affect fiber degradability and digestibility. The inclusion of concentrate in the diet increased the total production of VFA and proportions of propionate and butyrate, and a reduction in the acetate proportion and acetate:propionate ratio. The alteration in the VFA production with the inclusion of concentrate in the diet was probably the result of changes in the microbial population of the rumen, which is altered according to the type of substrate available. According to Wanapat and Khampa(20), the inclusion of concentrate in the diet, increases the number of protozoa and amylolytic and proteolytic bacteria, and reduces the number of fungi and cellulolytic bacteria. These alterations cause changes in the type and quantity of VFA produced. The lowest ruminal pH was observed in treatments containing concentrate. Rumen microorganisms ferment carbohydrates producing VFA and lactate, which have an acidogenic effect. Therefore, the inclusion of rapidly fermentable carbohydrates in the diet increases the fermentation rate and production of these compounds, reducing the pH(3,17). In addition, the inclusion of the concentrate is usually associated with less 146

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rumination and chewing with the consequent low production of saliva and diet buffer capacity(19,21). The treatment HAY, showed a low daily pH variation because the animals showed gradual intake throughout the day. Conversely, the treatments with the concentrate, presented a high pH variation during the day because the supplied concentrate was quickly consumed, reflecting subsequent drops in pH values, with the smallest values observed between 2 and 4 h after the feeding. The lowest pH values of 5.68 and 6.27 were observed in the treatments with the concentrate and hay, respectively. According to Hoover and Stokes(22), these values are within the range suitable for maximum microbial growth and maximal ruminal digestion of fibers (5.5 to 7.0) and the great pH range for fiber digestion is from 6.7 to 7.1. The highest concentration of ruminal N-NH3 was observed with the inclusion of concentrate. According to Van Soest(19), protein degradation in the rumen occurs through the action of enzymes secreted by ruminal microorganisms. These bacteria digest part of the protein, and others microorganisms on site use amino acids, peptides, and ammonia for cell multiplication. When the rate of ammonia production is greater than the rate of use, it is absorbed by the animal through the rumen wall passing into the blood stream and converting into urea in the liver. Urea can be recycled or lost through the urine. Excessive values are reached by a high inclusion of concentrate in the diets and are not desired. The treatment HAY presented a low daily variation of N-NH3 (Figure 2B) because the animals gradually consumed the feed throughout the day. On the other hand, as observed in the pH analysis, the treatments with concentrate showed a high variation due to the fast intake of concentrate causing peaks of ammonia production between 2 and 4 h after feeding. These increased levels occurred as the result of high amounts of CP from the concentrate (188 g kg-1), increasing its rumen degradation rate and producing N-NH3 peaks. There was an increase in the amount of absorbed and retained N (g d1 or g kg-1 of CP) with the inclusion of the concentrate in the diet. This happened probably due to the high N intake and high N digestibility contained in the concentrate compared to those in HAY. However, when the amount of N retained in g kg-1 of the N ingested was analyzed, the absence of increased efficiency in the use of ingested N with the inclusion of concentrate was probably resulting from the low flow rate displayed in the HAY treatment, which improved the efficiency of N use, producing results similar to those in the concentrate treatments. The inclusion of concentrate resulted in high losses of N, mainly through urine. This may have been due to a low efficiency of the urea cycle, which is a reflection of peaks of N-NH3 production and less saliva production with the inclusion of concentrate(19). Because the inclusion of concentrate reflects less chewing and rumination time(21), less saliva is produced, and less nitrogen is recycled in this way, which ends up being eliminated in the urine.

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Effect of additives

The inclusion of additives did not alter the DM and nutrients intake. However, ionophores are known to have an effect on DM ingestion leading to reduced intake when used in diets with a high proportion of concentrate(23,24). This effect may occur as a consequence of an increase in the concentration of ruminal propionic acid, which reflects an increase in energy efficiency, allowing nutritional requirements to be reached with a smaller amount of feed intake(7). This intake is also affected by pathophysiological aspects such as ruminal pH. Thus, a diet that induces rumen acidosis, with the addition of ionophores, may lead to a smaller pH drop, increasing intake(25). However, in this experiment, besides the high hay intake (approximately 430 g kg-1 of the diet), the diets were all cationic, which produces an alkalizing effect that may have caused the lack of effects of additives on the intake. The inclusion of additives did not alter the digestibility of the diet. However, ionophores can increase dietary digestibility by increasing the DM retention time in the rumen as the result of lower voluntary intake, stimulating rumination, improving the ruminal environment, and allowing increased digestibility(26). However, this effect was not observed in this study because the additives did not alter the intake. The additives did not influence the degradability of hay. Ionophores are known to alter the microbial population of the rumen and act on cellulolytic bacteria, which can lead to a reduction in fiber degradability(27). Nevertheless, it is probably easier to observe these effects in diets with higher proportions of roughage. Edward et al(5) report in an in vitro experiment that cellulolytic Gram-negative bacteria of the genus Fibrobacter are among the most sensitive to the action of flavomycin. According to these same authors, flavomycin normally does not decrease fiber degradation in in vitro and in vivo studies. Therefore, it is probable that the cellulolytic activities of bacteria of the genus Ruminococcus, fungi, and protozoa, which are not affected by this antibiotic and are in the microorganism's rumen population, compensate decreased numbers of Fibrobacter bacteria that could affect fiber degradation. The additives altered the production of VFA. Ionophores cause such alterations in the production of VFAs by modifying bacterial populations of the rumen. Gram-positive bacteria that produce acetate, butyrate, and H2 are inhibited by ionophores, and Gramnegative bacteria that produce propionate find better conditions to reproduce(28). The production of butyrate was increased in FLAV. (Thus, the response from the effect of flavomycin on the proportion of VFA differs from that from ionophores, which promotes an increase in the proportion of propionate. The action of flavomycin, not exactly on the same microorganisms, possibly reflects these alterations. The additives did not alter the ruminal pH. This happened probably due to the high proportion of hay in the diet (approximately 430 g kg-1 diet) inducing longer intake time, 148

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regurgitation, and saliva production resulting in a small drop in ruminal pH and not allowing the demonstration of these antibiotics’ effects. The reduction in the concentration of N-NH3 during the first peak of production (only 4 h after the morning feeding) was only detected in the diet with MON. This response is associated with the reduction in the number of bacteria that use amino acids and peptides as an energy source for their growth, and consequently, release ammonia in the ruminal environment. This reduction in the use of amino acids and peptides favors their passage into the small intestine and absorption, increasing the efficiency in the use of nitrogen(29). No effect was observed from additives on nitrogen balance. Nevertheless, the ionophores may promote an improved utilization of dietary nitrogen, as a result of reduced DM intake, consequent reduction of nitrogen intake, and reduced rumen deamination(30). In this study, the use of additives did not alter DM intake, and salinomycin and flavomycin did not alter the concentration of N-NH3. Therefore, the absence of an effect on the total nitrogen balance was expected. Although MON reduced the ammonia peak production after the morning feeding, this was not enough to alter the nitrogen balance.

Conclusions and implications The addition of concentrate to the sheep diet caused alterations in the intake, digestibility, ruminal variables (VFA, pH, and N-NH3), and nitrogen balance. MON, SALI, and FLAV altered the production of VFA, however, only MON reduced the production of N-NH3. Among the tested additives, monensina caused the most beneficial changes in the ruminal metabolism of sheep.

Acknowledgements The authors would like to thank the company Nutract Agrisolutions (Chapecó, SC, Brazil) for partially funding this research and also the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (Capes) for the scholarship provided to the first author.

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2. Ma T, Deng, KD, Tu Y, et al. Effect of dietary forage-to-concentrate ratios on urinary excretion of purine derivatives and microbial nitrogen yields in the rumen of Dorper crossbred sheep. Livestock Sci 2014;160:37-44. 3. Owens FN, Secrist DS, Hill WJ, Gill DR. Acidosis in cattle: a review. J Anim Sci 1998;76:275-86. 4. Nagaraja TG, Newbold CJ, Van Nevel CJ, Demeyer DI. Manipulation of ruminal fermentation. In: Hobson PN, editor. The Rumen Microbial Ecosystem. New York: Blackie; 1997:523–632. 5. Edwards JE, Mcewan NR, Mckain N, Walker N, Wallace RJ. Influence of flavomycin on ruminal fermentations and microbial populations in sheep. J Microbiol 2005;151:717-25. 6. Pressman BC. Biological applications of ionophores. Ann Rev Biochem 1976;45:501503. 7. Russel JB, Strobel HJ. Effect of ionophores on ruminal fermentation. J Appl Environ Microbiol 1989;55:1-6. 8. Murray PJ, Winslow SG, Rowe JB. Conditions under which flavomycin increases wool growth and liveweight gain in sheep. Aust J Agric Res 1992;43:367-87. 9. Bretschneider G, Elizalde JC, Pérez FA. The effect of feeding antibiotic growth promoters on the performance of beef cattle consuming forage-based diets: A review. Livestock Sci 2008;114:135-49. 10. Sniffen CJ, Connor JD, Van Soest P. A net carbohydrate and protein system for evalution cattle diets. II. Carboydrate and protein availability. J Anim Sci 1992;70:3562-77. 11. Ørskov ER, McDonald I. The estimation of protein degradability in the rumen from incubation measurements weighted according to rate of passage. J Agric Sci 1979;92:499-503. 12. Latimer GW; AOAC International. Association of Official Analytical Chemistry. Official methods of analysis. 15th ed. Arlington, VA: AOAC International; 1990. 13. Van Soest PJ, Robertson JB, Lewis BA. Methods for dietary fiber, neutral detergent fiber, and non starch polyssacarides in relation to animal nutrition. J Dairy Sci 1991;74:3583-97. 14. Ribeiro SS, Vasconcelos JT, Morais MG, Ítavo CBCF, Franco GL. Effects of ruminal infusion of a slow-release polymer-coated urea or conventional urea on apparent nutrient digestibility, in situ degradability, and rumen parameters in cattle fed lowquality hay. Anim Feed Sci Technol 2011;164:53-61.

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15. Erwin ES, Marco GJ, Emery EM. Volatile fatty acid analyses of blood and rumen fluid by gas chromatography. J Dairy Sci 1961;44:1768-71. 16. Grovum WL. Apetito, sapidez y control del consumo de alimentos. In: Church DC, editor. El rumiante. Fisiología digestiva y nutrición. ed. Acríbia, Zaragoza; 1988:225-242. 17. Dixon RM, Stockdale CR. Associative effects between forages and grains: consequences for feed utilization. Aust J Agric Res 1999;50:757-73. 18. Hagos T, Melaku S. Feed intake, digestibility, body weight and carcass parameters of Afar rams fed tef (Eragrostistef) straw supplemented with graded levels of concentrate mix. Trop Anim Health Prod 2009;41:599-606. 19. Van Soest PJ. Nutritional ecology of the ruminant, 2nd ed. Ithaca, NY, USA: Comstock Publishing Association; 1994. 20. Wanapat M, Khampa S. Effect of levels of supplementation of concentrate containing high levels of cassava chip on rumen ecology, microbial n supply and digestibility of nutrients in beef cattle. AJAS 2007;20:75-81. 21. Kleefisch MT, Zebeli Q, Humer E, Kröger I, Ertl P, Klevenhusen, F. Effects of the replacement of concentrate and fibre-rich hay by high-quality hay on chewing, rumination and nutrient digestibility in non-lactating Holstein cows. Arch Anim Nutr 2016;71:21-36 22. Hoover WH, Stokes SR. Balancing carbohydrates and proteins for optimum rumen microbial yield. J Dairy Sci 1991;74:3630-44. 23. Gastaldello Jr AL, Pires AV, Susin I, et al. Limestone with different particle size and sodium bicarbonate to feedlot lambs fed high grain diets with or without monensin. Small Ruminant Res 2013;114:80-5. 24. Mirzaei-Alamouti H, Moradi S, Shahalizadeh Z, et al. Both monensin and plant extract alter ruminal fermentation in sheep but only monensin affects the expression of genes involved in acid-base transport of the ruminal epithelium. Anim Feed Sci Technol 2016;219:132-43. 25. Rodrigues PHM, Mattos WRS, Melotti L, Rodrigues RR. Monensin and total tract digestibility in wethers fed different roughage/concentrate ratios. Sci Agric 2001;58:449-55. 26. Ellis WC, Horn GW, Delaney D, Pond KR. Effects of ionophores on grazed forage utilization and their economic value for cattle on wheat pasture. In: National wheat pasture symposium1983; Stillwater, USA. Stillwater: Agricultural Experimental Station; 1983.

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27. Bogaert C, Gomez L. Jouany JP. Effects of lasalocid and cationomycin on the digestion of plant cell walls in sheep. Can J Anim Sci 1991;71:379-88. 28. Bergen WG, Bates DB. Ionophores: Their effect on production efficiency and mode of action. J Anim Sci 1984;58:1465-83. 29. Yang CMJ, Russell JB. The effect of monensin supplementation on ruminal ammonia accumulation in vivo and the numbers of amino acid-fermenting bacteria. J Anim Sci 1993;71:3470-6. 30. Mcguffey RK, Richardson LF, Wilkinson JID. Ionophores for dairy cattle: current status and future outlook. J Dairy Sci 2001;84:194-203.

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https://doi.org/10.22319/rmcp.v11i1.4882 Article

Supplementation of broiler diets with propolis and oregano oil and its effect on production parameters, leukocytes, metabolites and breast meat antioxidant stability

José Inés Ibarra-Espain a Carlos Alfredo Carmona-Gasca a Francisco Escalera-Valente a Fidel Avila-Ramos b*

Universidad Autónoma de Nayarit. Unidad Académica de Medicina Veterinaria y Zootecnia. km 3.5 Carretera Chapalilla-Compostela. 63700, Compostela, Nayarit. México. b

Universidad de Guanajuato, Departamento de Veterinaria y Zootecnia. Irapuato, Guanajuato. México.

* Corresponding author: ledifar@hotmail.com

Abstract: Propolis and oregano oil are natural substances used in various food industry applications. An evaluation was done of the effects of oregano oil (A) and propolis (P) on production parameters, leukocytes, blood chemistry and meat antioxidant stability in broilers. Animals (n= 480) were randomly allocated to four treatments with four replicates of 30 animals each. Four additive levels (mg/k feed) were tested: C (control)= 0; P= 100 mg propolis; A= 100 mg oregano oil; and AP= 50 mg P + 50 mg A. At 42 d breast meat lipid oxidative stability was estimated based on malondialdehyde (MDA) content. The oregano oil contained 43.47% thymol and 29.16 % carvacrol, while the propolis contained 5.6 mg flavonoids, 840 µg phenols and 138 µg Trolox® equivalents (antioxidant stability) per gram. Feed intake, weight gain, feed conversion and mortality were unaffected by the dietary additives. At 3 wk, blood

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eosinophil levels increased in treatment AP (Pâ&#x2030;¤0.05), and at 6 wk triglycerides had increased in treatment A (Pâ&#x2030;¤0.05). Meat lipid oxidative stability decreased in the AP treatment (Pâ&#x2030;¤0.05). Neither oregano oil nor propolis improved production parameters, although they can stimulate immune response. When added to low-fat broiler diets they can increase blood triglycerides and in combination they compromise breast meat lipid oxidative stability. Key words: Essential oils, Natural additives, Broilers, Oxidative stability.

Received: 03/05/2018 Accepted: 13/12/2018

Introduction Restrictions on the use of synthetic substances in animal production systems, including of poultry species, has driven increasing interest in natural substances as growth stimulants(1,2). These can function by increasing production parameters, supporting immune response, improving health condition and decreasing oxidation of fats in chicken meat(3,4). Oregano oil is used as a preservative in the food industry because it prevents microorganism growth(5-7). Its main compounds are thymol and carvacrol, which can represent up to 80 % of its content and are responsible for its biological activity(8,9). Propolis is produced by bees from resins collected from trees, shrubs and plants. It has myriad functions in the beehive, including as an antiseptic to prevent the growth of microorganisms in the hive. Over 300 substances have been identified in propolis such as aromatic acids, diterpenes, phenols and flavonoids(10-13), all of which are bioactive compounds with anticancer, anti-inflammatory, bactericidal, viricidal, immunostimulatory and antioxidant capacity both in vivo and in vitro(14-16). Due to their price, ease of use and benefits oregano oil and propolis are currently in use as alternative compounds in the poultry industry, however results vary in response to their sources(17-19). Combining natural bioactive compounds can potentiate their biological effects, increasing organism response. The present study objective was to evaluate if oregano oil alone or in combination with propolis affects productive variables, blood leukocytes, lymphocytes and chemical element concentrations, and oxidative stability of broiler breast meat. 154

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Material and methods All animal protocols in the present study comply with animal welfare guidelines and were approved by the Animal Care and Use Committee of the University of Nayarit (Tepic, Mexico).

Oregano essential oil composition

Compounds in the oregano oil were identified with a gas chromatographer (GC; Hewlett Packard P-6890, California, USA) attached to a mass spectrophotometer (MS; Hewlett Packard 7953, California, USA), using a capillary column (30 m long, 0.25 mm internal diameter, 0.25 µm film thickness; Hewlett Packard 5ms®, California, USA). Injection port temperature was 240 °C. Initial temperature was 50 °C for 5 min, and was increased 10 °C per minute until reaching 260 °C. The carrier gas was helium. The MS was run in scan mode (m/z range: 30-550) with electronic ionization (70 eV) and a 1.0 ml/min flow rate.

Propolis flavonoids and phenols contents and antioxidant capacity

Flavonoids content was quantified following the aluminum chloride method, total phenols with the Folin-Ciocalteu method and antioxidant capacity with the 2,2-diphenyl-1picrylhydrazyl (DPPH) radical method(20).

Experiment location

The evaluation was done at the Veterinary Medicine and Zootechny Academic Unit poultry farm of the Universidad de Nayarit (Compostela Municipality, Nayarit, Mexico).

Animals and experimental diets

Experimental animals were 480, one-d-old Ross line broilers randomly distributed in four treatments (C= control, P= 100 mg propolis/kg feed, A = 100 mg oregano oil/kg feed, PA= 155

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50 mg propolis plus 50 mg oregano oil/kg feed) with four replicates of 30 chickens each per treatment. Starter and finishing diets were based on corn-soybean paste meal (Table 1) provided ad libitum for 42 d. The oregano oil and/or propolis were added during feed processing. Table 1: Experimental diet composition (%) Ingredients Corn Soy paste Raw soy oil Calcium bicarbonate (38%) Dicalcium phosphate (18/21) Salt Mineral and vitamin premix1 DL-Methionine HCL-Lysine Xanthophylls2 Coccidiostat

Nutrient composition: Mcal/kg Crude protein Calcium Lysine Methionine + Cysteine Methionine Available phosphorous Histidine Tryptophan Threonine Arginine Linoleic acid 1

Starter 65.41 29.22 1.00 1.64 1.49 0.30 0.30 0.30 0.29 0.00 0.05 100.00

Growth / Finishing 72.16 22.11 1.86 1.52 1.30 0.30 0.30 0.18 0.19 0.03 0.05 100.00

3.00 20.06 1.00 1.30 0.95 0.50 0.45 0.51 0.27 0.84 1.31 1.90

3.10 17.00 0.90 1.00 0.75 0.40 0.45 0.43 0.23 0.73 1.08 2.46

Vitamin premix (/kg feed): vitamin A, 10,000 UI; vitamin D3, 2,500 UI; vitamin K3, 2 mg; thiamin, 2 mg; riboflavin, 7 mg; pantothenic acid, 10 mg; pyridoxine, 4 mg; folic acid, 1 mg; vitamin B 12, 0.015 mg; and biotin, 0.010 mg (Vipresa®, Tepatitlán de Morelos, Mexico). Mineral premix (mg/kg feed): Se, 0.20; I, 0.30; Cu, 7; Fe, 65; Zn, 75; Mn, 65; and Co, 0.4 (Vipresa ®, Tepatitlán de Morelos, Mexico). 2 90 ppm Tagetes erecta (Florafil-93 Powder, Industrias Vepinsa S.A. de C.V., Los Mochis, Sinaloa, Mexico).

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Productive parameters and blood samples

Productive parameters were measured every seven days, and mortality as it occurred. At d 21 and 42, blood samples were taken from the brachial vein of two birds per replicate and 1.8 mg ethylenediaminetetraacetic acid (EDTA) per ml added. These samples were dyed with Wright dye for blood metabolite measurement (Easy-Vet, Desego).

Meat samples

Meat samples were taken from two birds per replicate. After a 6 h fast, the animals were killed by severing the jugular vein and carotid artery following an established protocol (Norma Oficial Mexicana NOM-033-SAG/ZOO-2014)(21). The carcass was drained of blood for 2 min, placed in water (60 °C) for 120 sec to allow for manual removal of the feathers, and cooled in ice water (0 °C) for one hour. The breast meat was removed from the carcass, the skin and any visible fat removed, and the meat stored in a vacuum and frozen (-20 °C) for approximately one month.

Meat oxidative stability

Oxidative stability was measured using a 30 g sample of meat and adding 30 ml distilled water with 0.2 mL 7% BHT (2,6-di-tert-butyl-4-methyl-phenol, Sigma-Aldrich, Toluca, Mexico) diluted in 96% methyl alcohol (CH3CH2OH). This mixture was liquified for 30 sec in a blender (Oster, M4655-813 / 465-42), filtered through a 0.84 mm plastic mesh and left to stand for 30 min at 25 °C in darkness. A 1 mL subsample was taken from the top layer and 2 ml 0.02 M thiobarbituric acid (Sigma-Aldrich, Toluca, Mexico) combined with 15% trichloroacetic acid (TCA) in distilled water added to it. The solution was stirred for 10 sec, placed in water at 80 °C for 10 min and finally at 0 °C for 10 min. Absorbance was measured at 532 nm (Biotek, Epoch, USA), and the resulting values multiplied by 7.8 to express mg malondialdehyde (MDA) per kilo of meat(22).

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Statistical analysis The results were analyzed with a completely random design using the Generalized Linear Method (GLM) of the SAS statistics program. The means were compared with a Tukey test at a P≤0.05 significance level. Mortality results were transformed with an arc sine function and expressed as a percentage. The statistical model was: Yij = µ + Ƭi + εij Where: Yij is feed intake, weight gain, feed conversion, mortality, leukocytes, chemical variables and MDA per kilogram of meat; µ is the general mean; Ƭi is the effect of the oregano oil, propolis and oregano oil plus propolis; Εij is the random error.

Results and discussion Oregano oil The most abundant compounds in the oregano oil were thymol (43.47 %), carvacrol (29.16 %), eucalyptol (6.96 %), caryophyllene (5.38 %) and tetramethyl (2.96 %). It is the thymol and carvacrol contents of oregano oil that slow bacterial growth. Their concentrations can vary due to place of origin, harvest time and plant maturity, but they remain the most abundant compounds in all phenological stages of the oregano plant. These two compounds can account for as much as 80% of oregano oil(23,24). In the present study they accounted for 72 %, more than twice that reported elsewhere(25,26).

Propolis Flavonoid content in the evaluated propolis was 5.6 mg quercetin equivalents/g propolis, phenols content was 840 µg caffeic acid equivalents/g propolis, and antioxidant capacity was 138 µg Trolox equivalents/g propolis. Biologically active compound contents can vary widely in propolis depending on source region; for example, flavonoid contents ranging from 8 to 188 mg/g propolis and phenols contents ranging from 42.9 to 329.0 mg/g propolis have been reported from China, India, Macedonia and Iran(10,24,25). Reported levels in propolis from Mexico are 379.2 mg flavonoids, 500.9 mg phenols and 54.4 mg Trolox equivalents per gram of propolis(20). Compared to the above values, the propolis analyzed here contained limited amounts of these active compounds. 158

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Productive parameters

Inclusion of the oregano oil and/or propolis in the feed had no effect on feed intake, weight gain, feed conversion and mortality (Table 2). Apparently, the animals exhibited no quantifiable response because the inclusion levels were not high enough. Previous reports of productive performance in broilers in response to addition of oregano oil or propolis in poultry diets are variable. In two studies inclusion levels of 25, 50, 300 and 600 ppm propolis per kilogram of feed had no effect on broilers(27,28). In another study, only addition of 15,000 and 20,000 ppm oregano oil to boiler diets increased productive yields(29). In the present study the doses of propolis and/or oregano oil did not provide enough active compounds to stimulate digestive enzyme secretion, and the birds consequently showed no changes in productive parameters. Only high doses or larger amounts of active compounds can stimulate digestive enzyme secretion, allowing the birds to better exploit ingested nutrients and thus increase yield(30). A serious challenge when comparing studies of production performance in response to natural compounds is that most do not report the amount of active compounds contained in evaluated propolis or essential oils, precluding any comparisons.

Table 2: Productive parameters (kg) of broilers at three and six weeks of age Feed Mortality Treatments Feed intake Weight gain conversion (%) Three weeks 1.58 4.20 0.68  0.03 0.43  0.02 C 1.59 7.50 A 0.66  0.01 0.42  0.02 1.58 10.00 0.67  0.01 0.43  0.01 P 1.59 9.20 AP 0.69  0.01 0.43  0.01 0.004 0.003 0.011 0.453 SME Six weeks 1.99 3.30 3.99  0.16 2.01  0.02 C 1.98 1.70 3.74  0.14 1.89  0.12 A 2.03 1.70 3.65  0.24 1.80  0.14 P 2.01 5.00 3.79  0.09 1.89  0.09 AP SME 0.049 0.030 0.017 0.181 C= control; A= oregano oil (100 mg kg-1 feed); P= propolis (100 mg kg-1 feed); AP= oregano oil (50 mg kg-1 feed) + propolis (50 mg kg-1 feed). SME= Standard mean error.

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Leukocytes

At three weeks, lymphocyte levels were lowest in the P treatment (P≤0.05), and eosinophils were highest in the AP treatment (P≤0.05). The C and A treatments were similar (Table 3). Lymphocytes support immune response when challenged by invading microorganisms. The present results coincide with previous studies in which lymphocyte levels in poultry decreased in response to addition of propolis to the diet because the active compounds in propolis inhibit development of T lymphocytes(31,32). In another study levels as low as 5 µg propolis per milliliter caused negative effects in vitro, due to the flavonoids content(33). Eosinophil levels were two-fold higher in the AP treatment than in the P treatment. Eosinophils are cells linked to the development of T lymphocytes, the populations of which decrease as bird age increases(34). However, when development of the digestive system improves, eosinophils increase; broilers offered feed with added oregano oil or propolis have exhibited improved intestinal flora and stimulation of cytosines which induced eosinophil proliferation(35).

Table 3: Blood leukocyte concentrations in broilers at three and six weeks of age Treatment Lymphocytes Heterophils Eosinophils Basophils Monocytes Three weeks C 68.8 ± 3.1 a 29.8 ± 2.4 0.0 ± 0.0 c 0.5 ± 0.5 0.3 ± 0.5 A 61.8 ± 2.9 ab 36.9 ± 13.3 0.0 ± 0.0 c 0.0 ± 0.0 0.0 ± 0.0 P 55.2 ± 3.3 b 43.2 ± 3.1 1.5 ± 1.4 b 0.3 ± 0.5 0.0 ± 0.0 AP 57.9 ± 8.9 ab 38.5 ± 10.1 3.6 ± 1.3 a 0.4 ± 0.5 0.0 ± 0.0 SME 1.65 1.67 0.313 0.083 0.043 Six weeks C 42.0 ± 10.2 19.6 ± 4.4 27.3 ± 8.0 2.8 ± 2.6 8.4 ± 7.7 A 38.4 ± 12.4 18.1 ± 7.8 31.0 ± 11.3 3.6 ± 2.9 12.0 ± 6.1 P 45.3 ± 10.1 14.8 ± 3.0 3.5 ± 2.3 3.5 ± 2.3 12.9 ± 3.9 AP 51.6 ± 9.4 17.5 ± 10.2 43.9 ± 63.0 2.4 ± 2.6 6.4 ± 4.6 SME 1.869 1.154 5.558 0.730 1.504 C= control; A= oregano oil (100 mg kg-1 feed); P= propolis (100 mg kg-1 feed); AP= oregano oil (50 mg kg-1 feed) + propolis (50 mg kg-1 feed). SME= Standard mean error. abc Different letter suffixes in the same column and age group indicate significant difference (P<0.05).

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Blood metabolites

In six-week-old birds, triglycerides levels were highest in treatment A (P≤0.05) and lowest in AP, while C and P had intermediate values and did not differ between themselves (Table 4). Blood metabolite levels are indicative of general animal health. Addition of propolis (300 ppm) in broiler diets has been reported to lower cholesterol and triglyceride levels(36), although this response is inconsistent(37). For example, broilers fed diets containing 6% fat levels and added propolis exhibited low cholesterol and triglyceride levels(38), whereas in trials with lower energy levels no hypocholesterolemic or hypolipidemic effect was observed with addition of propolis or oregano oil to the diet.

Table 4: Blood metabolites levels in broilers at three and six weeks of age Metabolite C A P AP SME Three weeks Glucose 137.8 ± 41.3 111.8 ± 58.4 106.3 ± 38.6 105.1 ± 49.5 8.00 Urea 6.2 ± 2.7 5.9 ± 1.5 4.8 ± 2.1 3.9 ± 0.9 0.00 Uric acid 5.6 ± 1.3 4.1 ± 1.4 5.6 ± 2.4 5.3 ± 2.2 0.00 Creatine 0.5 ± 0.2 0.3 ± 0.1 0.4 ± 0.1 0.4 ± 0.0 0.00 Cholesterol 234.6 ± 22.5 229.9 ± 41.6 237.3 ± 36.0 263.3 ± 35.6 6.00 Triglycerides 96.9 ±23.4 84.5 ± 21.0 84.3 ± 12.9 78.4 ± 9.4 3.00 Six weeks Glucose 284.8 ± 55.6 265.9 ± 58.8 313.8 ± 84.0 279.6 ± 27.4 10.478 Urea 3.1 ± 1.8 3.1 ± 3.1 2.9 ± 1.9 2.9 ± 1.4 0.356 Uric acid 7.4 ± 3.2 11.0 ± 7.3 7.7 ± 5.4 7.6 ± 2.2 1.000 Creatine 0.2 ± 0.1 0.3 ± 0.1 0.3 ± 0.0 0.3 ± 0.0 0.200 Cholesterol 170.4 ± 26.3 189.0 ± 51.4 186.5 ± 37.5 167.8 ± 30.6 0.516 Triglycerides 55.1 ± 10.0 ab 68.8 ± 22.9 a 50.3 ± 6.4 ab 45.0 ± 11.5 b 2.836 C= control; A= oregano oil (100 mg kg-1 feed); P= propolis (100 mg kg-1 feed); AP= oregano oil (50 mg kg-1 feed) + propolis (50 mg kg-1 feed). SME= Standard mean error. abc Different letter suffixes in the same row indicate significant difference (P<0.05).

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Chicken breast oxidative stability

Oxidation in the breast meat was highest in the AP treatment (P≤0.05), with no difference between the A, P and C treatments (Table 5). Propolis and oregano oil are known to have antioxidant capacity in vitro and in vivo(16,39), but their effects may vary when mixed with other ingredients in a diet. For example, oregano oil combined with acidified soybean oil has no antioxidant effect(39), whereas addition of 200 ppm propolis is reported to decrease MDA content in chicken meat(40). The latter may be due to accumulation of the bioactive compounds in propolis in cell membranes, which could protect them from oxidation(33,36). Apparently, combining oregano oil with propolis accelerates the oxidative process in meat, but when administered independently they have no effect on MDA levels.

Table 5: Oxidative stability in chicken breast meat (malondialdehyde per kilogram of meat) Treatment Mean ± standard deviation C 0.849 ± 0.34 b A 1.116 ± 0.41 b P 0.670 ± 0.39 b AP 1.864 ± 0.58 a SME 0.262 C= control; A= oregano oil (100 mg kg-1 feed); P= propolis (100 mg kg-1 feed); AP= oregano oil (50 mg kg-1 feed) + propolis (50 mg kg-1 feed). SME= Standard mean error. abc Different letter suffixes in the same column indicate significant difference (P<0.05).

Conclusions and implications The evaluated oregano oil contained 43.47 % thymol and 29.16 % carvacrol, and the propolis contained 840 µg phenols, 5.6 mg flavonoids and 138 µg Trolox equivalents. When added to broiler diets either alone or in combination they produced no increase in productive performance. At three weeks age, overall white blood cell counts decreased in the different treatments, although eosinophil counts increased. At six weeks, blood triglycerides increased in the oregano oil treatment. Combining oregano oil with propolis increased oxidation in breast meat. The present results do not indicate any clear benefit from including oregano oil and/or propolis in broiler diets at the evaluated concentrations. Further research is needed to 162

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identify at what concentrations these natural substances exercise a positive effect on productive performance, and if combining them could improve broiler productivity and health.

Acknowledgements The research reported here was financed by the Secretaria de Educación Pública through prject PRODEP (DSA/103.5/15/7007).

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the essential oils of commonly consumed medicinal herbs using an in vitro model. Molecules 2010;15(11):7532-7546. 10. Laskar RA, Ismail Sk, Nayan R, Naznin AB. Antioxidant activity of Indian propolis and its chemical constituents. Food Chem 2010;(122):2332-2237. 11. Huang S, Zhang, CP, Wang K, Li GQ, Hu FL. Recent advances in the chemical composition of propolis. Molecules 2014;19(12):19610-19632. 12. Choia YM, Nohb DO, Choc SY, Suhd HJ, Kimd KM, Kimd JM. Antioxidant and antimicrobial activities of propolis from several regions of Korea. LWT 2006;(29):756761. 13. Hashemi JM. Biological effect of bee propolis: a review. European J Appl Sci 2016;8(5):311-318. 14. Çetin E, Silici C, Çetin N, Güçlü B. K. Effects of diets containing different concentrations of propolis on hematological and immunological variables in laying hens. Poult Sci 2010;89(8):1703-1708. 15. Frozza CO, Garcia CS, Gambato G, de Souza MD, Salvador M, Moura S et al. Chemical characterization, antioxidant and cytotoxic activities of Brazilian red propolis. Food Chem Toxicol 2013;(52):137-142. 16. Kalogeropoulos N, Konteles SJ, Troullidou E, Mourtzinos L, Karathanos VT. Chemical composition, antioxidant activity and antimicrobial properties of propolis extracts from Greece and Cyprus. Food Chem 2009;116(2):452-461. 17. Toghyani M, Toghyani M, Gheisari A, Ghalamkari G, Eghbalsaied S. Evaluation of cinnamon and garlic as antibiotic growth promoter substitutions on performance, immune responses, serum biochemical and haematological parameters in broiler chicks. Livest Sci 2011;138(1-3):167-173. 18. Eyng C, Murakami AE, Santos TC, Silveira TGV, Pedroso RB, Lourenço DAL. Immune responses in broiler chicks fed propolis extraction residue-supplemented diets. AsianAustralas J Anim Sci 2015;28(1):135-142. 19. Zamora ZG, Durán MLA, Hume ME, Vázquez RS. Performance, blood parameters, and carcass yield of broiler chickens supplemented with Mexican oregano oil. R Bras Zootec 2017;46(6):515-520. 20. Hernández-Zarate MS, Abraham-Juárez MR, Cerón-García A, Ozuna-López C, Gutiérrez- Chávez JA, Segoviano-Garfias JJN, Avila-Ramos F. Flavonoids, phenolic content, and antioxidant activity of propolis from various areas of Guanajuato, Mexico. Food Sci Technol Campinas 2018;38(2):210-215. 164

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21. Secretariá de Agricultura, Ganadería, Desarrollo Rural, Pesca y Alimentación. 1995. Norma Oficial Mexicana NOM- 033-SAG/ZOO-2014. Sacrificio humanitario de los animales domésticos y silvestres. SAGARPA. 22. Tarladgis BG, Watts BM, Younathan MT, Dugan LJr. A distillation method for the quantitative determination of malonaldehyde in rancid foods. J Am Oil Chem Soc 1960;37(1):44-48. 23. Abu-Lafi S, Odeh I, Dewik H, Qabajah M, Hanus LO, Dembitsky VM. Thymol and carvacrol production from leaves of wild Palestinian Majorana syriaca. Bioresour Technol 2008;99(9):3914-3918. 24. Bouyahya A, Dakka N, Talbaoui A, Et-Touys A, El-Boury H, Abrini J, Bakri Y. Correlation between phenological changes, chemical composition and biological activities of the essential oil from Moroccan endemic Oregano (Origanum compactum Benth). Ind Crops Prod 2017;(108):729-737. 25. Ahn M, Kumazawa S, Usui Y, Nakamura J, Matsuka M, Zhu F, Nakayama T. Antioxidant activity and constituents of propolis collected in various areas of China. Food Chem 2007;101(4):1383-1392. 26. Mechergui K, Jaouadi W, Coelho JP, Khouja ML. Effect of harvest year on production, chemical composition and antioxidant activities of essential oil of oregano (Origanum vulgare subsp glandulosum (Desf.) Ietswaart) growing in North Africa. Ind Crops Prod 2016;(90):32-37. 27. Jang IS, Ko YH, Kang SY, Lee CY. Effect of a commercial essential oil on growth performance, digestive enzyme activity and intestinal microflora population in broiler chickens. Anim Feed Sci Technol 2007;134(3-4):304-315. 28. Kirkpinar F, Ünlü HB, Özdemir G. Effects of oregano and garlic essential oils on performance, carcase, organ and blood characteristics and intestinal microflora of broilers. Livest Sci 2011;137(1-3):219-225. 29. Abdel-Wareth AAA, Kehraus S, Hippenstiel F, Südekum KH. Effects of thyme and oregano on growth performance of broilers from 4 to 42 days of age and on microbial counts in crop, small intestine and caecum of 42-day-old broilers. Anim Feed Sci Technol 2012;178(3-4):198-202. 30. Lee KW, Everts H, Kappert HJ, Frehner M, Losa R, Beynen AC. Effects of dietary essential oil components on growth performance, digestive enzymes and lipid metabolism in female broiler chickens. Br Poult Sci 2003;44(3):450-457.

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31. Márquez N, Sancho R, Macho A, Calzado MA, Fiebich BL, Muñoz E. Caffeic acid phenethyl ester inhibits T-cell activation by targeting both nuclear factor of activated Tcells and NF-kappaB transcription factors. J Pharmacol Exp Ther 2004;308(3):9931001. 32. Dantas AP, Olivieri BP, Gomes FH, De Castro SL. Treatment of Trypanosoma cruziinfected mice with propolis promotes changes in the immune response. J Ethnopharmacology 2006;103(2):187-193. 33. Sá-Nunes A, Faccioli LH, Sforcin JM. Propolis: lymphocyte proliferation and IFNgamma production. J Ethnopharmacol 2003;87(1):93-97. 34. Huang H, Liu Y, Hou Y, Wen L, Ge H, Peng K, Liu H. Distribution patterns of stromal eosinophil cells in chick thymus during postnatal development. Vet Immunol Immunopathol 2016;153(1-2);123-127. 35. Buonomo EL, Cowardin CA, Wilson MG, Saleh MM, Pramoonjago P, Petri WA. Microbiota-regulated il-25 increases eosinophil number to provide protection during clostridium difficile infection. Cell Rep 2016;16(2):432-443. 36. Attia YA, Ibrahim Abd, AE, Ibrahim MS, Al-Harthi MS, Bovera F, Elnaggar ASh. Productive performance, biochemical and hematological traits of broiler chickens supplemented with propolis, bee pollen and, mannan oligosaccharides continuously or intermittently. Livest Sci 2014;(164):87-95. 37. Denli M, Cankaya S, Silici F, Okan A, Uloucak N. Effect of dietary addition of turkish propolis on the growth performance, carcass characteristics and serum variables of quail (Coturnix coturnix japonica). Asian-Australas J Anim Sci 2005;18(6):848-854. 38. Althnaian T. Influence of dietary supplementation of Garden cress (Lepidium sativum L.) on liver histopathology and serum biochemistry in rats fed high colesterol diet. J Adv Vet Anim Res 2014;1(4):216-223. 39. Avila-Ramos F, Pro-Martinez A, Sosa-Montes E, Cuca-Garcia JM, Becerril-Perez C, Figueroa-Velasco JL, Ruiz-Feria CA, Hernandez-Cazares AS, Narciso-Gaytan C. Dietary supplemented and meat-added antioxidants effect on the lipid oxidative stability of refrigerated and frozen cooked chicken meat. Poult Sci 2013;92(1):243-249. 40. Haščík P, Trembecká L, Bobko M, Kačániová M, Čuboň J, Kunová S, Bučko O. Effect of diet supplemented with propolis extract and probiotic additives on performance, carcass characteristics and meat composition of broiler chickens. Potravinarstvo 2016;10(1):223-231.

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https://doi.org/10.22319/rmcp.v11i1.4998 Article

Genetic relationships, biofilm formation, motility and virulence of Escherichia coli isolated from bovine mastitis

Alejandro Sergio Cruz-Soto a Valentín Toro-Castillo a Cristián Omar Munguía-Magdaleno a José Emmanuel Torres-Flores a Luis Enrique Flores-Pantoja a Pedro Damián Loeza-Lara a Rafael Jiménez-Mejía a*

Universidad de La Ciénega del Estado de Michoacán de Ocampo. Genómica Alimentaria. Avenida Universidad No. 3000. Col. Lomas de la Universidad, 59103, Sahuayo, Michoacán, México.

*Corresponding author: rjimenez@ucienegam.edu.mx

Abstract: Escherichia coli is an environmental bacterium frequently implicated in bovine mammary infections. Although specific virulence factors are unknown, biofilm-forming bacteria are associated with persistent infections, and motile bacteria exhibit increased virulence. An analysis was done of the genetic relationship, biofilm formation capacity and motility of bovine mastitis-associated E. coli, as well as the in vivo virulence of representative bacterial isolates. Of the 34 isolates, 67.7 % belonged to phylogenetic group A, 17.6 % to group B1 and 14.7 % to group D. Genetic relationship analysis done with (GTG)5-PCR indicated that the analyzed bacteria are diverse, with only two isolates exhibiting 100 % similarity, and the remaining 32 being grouped into seven main clusters with more than 70 % similarity. Biofilm formation capacity ranged from strong to moderate and weak in 76.5 % of the isolates. The 167

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csgA and fimA genes were detected in 52.9 % of the biofilm-forming isolates. Most (70.6 %) of the isolates were motile. In vivo infection assays using Galleria mellonella showed the biofilm-forming bacteria to be more pathogenic than the non-biofilm-forming ones. The studied bovine mastitis-associated E. coli were genetically diverse. Biofilm formation capacity and motility were variable among the isolates, but the biofilm-forming bacteria were more pathogenic than the non-biofilm-forming ones. Key words: E. coli, Bovine mastitis, Diversity, Biofilm, Virulence.

Received: 24/07/2018 Accepted: 16/01/2019

Introduction Bovine mastitis is the principal cause worldwide of economic losses in the dairy industry due to decreased milk production, treatment costs, and early disposal of cattle, among other factors(1). Escherichia coli is one of the main environmental pathogens associated with bovine mastitis, and its infections can range from moderate to severe(2,3). The specific virulence factors of bovine mastitis-associated E. coli have not been determined to date, but it may form part of a new pathotype known as Mammary Pathogenic E. coli (MPEC)(4). More recent studies at the genomic level have revealed the presence of groups of genes that code for the type VI secretion systems, lipopolysaccharide biosynthesis, biofilm formation and iron uptake systems characteristic of bovine mastitis-associated E. coli (BMAEC)(5-8). However, other studies suggest that evidence is still insufficient to assign BMAEC to a particular pathotype(9). Several phylogenetic analyses of E. coli have classified this bacterium into four main groups: A, B1, B2 and D. Non-pathogenic commensal bacteria belong mainly to groups A and B1, although these groups also include important pathogens. Group B2 and a smaller proportion of D contain strains associated with extra-intestinal infections(9,10). Bovine mastitisassociated E. coli (BMAEC) have been assigned mainly to groups A and B1(11,12,13). In addition, genetic and genomic analyses have revealed that BMAEC are quite diverse; indeed, the E. coli associated with both persistent and transient bovine mastitis exhibit both phenotypic and genotypic diversity(14). Genomic analysis of various E. coli isolates which cause bovine mastitis and commensals has shown that none can be classified into a particular

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phylogenetic group and that in both cases they apparently originated from different lineages(9). The ability to colonize and invade the bovine mammary epithelium helps bacteria evade the immune response and infect persistently. The E. coli behind persistent mastitis efficiently invades mammary epithelial cells, and, although the mechanisms it uses are not well known, the bacteria exhibiting greater motility also have greater virulence(15). The extracellular polymer matrix of biofilm-forming bacteria makes them more resistant to various chemical substances with antimicrobial activity produced by cells, as well as protecting them from the innate immune system(16,17). Bacterial virulence is generally studied using various animal models, although many of these can be expensive and present some ethical problems. A viable and increasingly popular model uses larvae of the greater wax moth Galleria mellonella to measure the virulence of Gram positive and negative pathogenic bacteria, as well as fungi(18,19). For example, G. mellonella is a suitable model for study of the pathogenic variants of both intestinal and extraintestinal E. coli(20,21,22). The present study objective was to analyze the genetic diversity, identify phylogenetic groups, and quantify biofilm formation capacity and motility of E. coli isolated from cases of subclinical bovine mastitis, and evaluate the in vivo virulence of representative isolates using a G. mellonella larvae model.

Material and methods DNA extract preparation and phylogenetic group identification

The studied E. coli were 34 antibiotic-resistant strains isolated from cases of subclinical bovine mastitis in western Michoacรกn state, Mexico(23). Total DNA extracts were prepared from these isolates(24). An established protocol was used to identify the phylogenetic groups of each strain(10). The primers used for fragment amplification were: ChuA.1 (5'-GACGAACCAACGGTCAGGAT-3'); ChuA.2 (5'-TGCCGCCAGTACCAAAGACA-3'); YjaA.1 (5'-TGAAGTGTCAGGAGACGCTG-3'); YjaA.2 (5'-ATGGAGAATGCGTTCCTCAAC-3'); TspE4C2.1 (5'-GAGTAATGTCGGGGCATTCA-3'); TspE4C2.2 (5'-CGCGCCAACAAAGTATTACG-3'). 169

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The PCR reactions were run using a 25 µl volume containing: 1X PCR Master mix (Promega, Madison, WI, USA), 1 µM of each primer and 2 µl bacterial DNA extract (50 ng). Fragment amplification was done in a C1000 thermocycler (Bio-Rad, Mexico City, Mexico) under the following conditions: initial denaturation at 94 °C for 5 min; 30 cycles as follows, denaturation at 94 °C for 30 s, alignment at 55 °C for 30 s and extension at 72 °C for 30 s; and final extension at 72 °C for 5 min. The amplified products were separated on 1.5% agarose gels and viewed with a Universal Hood II Gel Doc (Bio-Rad).

Biofilm production Biofilm production was grown according to an established protocol(25) with some modifications. Bacteria were seeded in Petri dishes with trypticase soy agar (TSA, BD, Mexico City, Mexico). These cultures were used to inoculate tubes with 2 ml trypticase soy broth (TSB) containing 0.25% glucose, which were incubated overnight at 37 °C under constant agitation. In each tube the cultures were diluted to the 0.5 MacFarland standard with TSB containing 0.25% glucose. From these bacterial dilutions 200 μl were deposited in triplicate in 96-well ELISA plates and incubated for 24 h at 37 °C without stirring. Noninoculated culture medium was used as a negative control, and the biofilm-forming bacterium Pseudomonas aeruginosa ATCC 27853 was used as a positive control. After incubation the culture medium was discarded, the wells washed three times with sterile saline, and the plate allowed to dry at 60 °C for 1 h to fix the cells. One percent (1%) violet crystal (200 µl) was added to the wells and the plate left at room temperature for 20 min. It was washed with running water until no color evolution was observed and allowed to dry at room temperature. The violet crystal was solubilized by adding 200 µl 96% ethanol to each well and stirring, and transferring the supernatant to a microcentrifuge tube. This process was repeated, tube content completed to 1 ml and optical density (OD) of the suspension read at 570 nm with a SmartSpec Plus spectrophotometer (Bio-Rad). This test was repeated four times in triplicate and average OD calculated from the results. The optical density cutoff (ODc) was calculated using the average OD of the negative control and increasing the value by three times its standard deviation, producing a value of 0.22. The biofilm-forming bacteria were classified into four groups: strong= OD> 4xODc; moderate= 2xODc<OD≤4xODc; weak= ODc<OD≤2xODc; and negative= OD≤ODc(25).

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Detection of genes associated to biofilm formation

The presence of two genes associated with biofilm formation, fimA (main subunit of type I fimbria) and csgA (main subunit of curli fimbria), was analyzed by PCR. A 119 bp fimA fragment was amplified with fimA-F (5'-CTCTGGCAATCGTTGTTCTGTCG-3') and fimA-R (5'-GCAAGCGGCGTTAACAACTTCC-3'), and a 178 bp csgA fragment was amplified with csgA-F (5'-GATCTGACCCAACGTGGCTTCG-3') and csgA-R (5'GATGAGCGGTCGCGTTGTTACC-3')(26). The reactions were run in a 25 µl volume containing 1X PCR Master mix (Promega), 1 µM of each primer, and 2 µl total DNA extract. Amplification conditions were: initial denaturation at 95 °C for 5 min; 30 cycles of 94 °C for 30 s, 55 °C for 30 s and 72 °C for 30 s; and a final extension cycle at 72 °C for 10 min. The amplified products were separated on 2% agarose gels and viewed as described above.

Determination of swarming type motility

Bacterial motility was measured following an established protocol(15). Briefly, swarming motility was determined by allowing the cultures to grow overnight in Lysogeny Broth (LB), and adding 5 µl swarming agar (LB + 0.5% agar) containing 0.5% glucose. After incubating the cultures for 12 h at 37 °C, bacteria displacement diameter was measured. Three measurements were taken and averaged.

Rep-PCR of bovine mastitis-causing E. coli

Genetic diversity was analyzed by purifying genomic DNA according to standard protocols(27). The purified DNA was amplified in 25 µl reaction mixture containing 12.5 µl 2X Master mix (Promega), 3 mM MgCl2, 5% DMSO, 0.16 µg/µl bovine serum albumin, 100 ng DNA and 2 µM of the primer (GTG)5 (5'-GTGGTGGTGGTGGTG-3'). Amplification was done in a C-1000 thermocycler (Bio-Rad) under the following sequence: initial denaturation 95 °C for 2 min; 30 cycles as follows, denaturation (94 °C/3 s and 92 °C/30 s), alignment (40 °C/1 min) and extension (65 °C/8 min); and final extension at 65 °C for 8 min(28). The amplified products were separated on 1.5% agarose gels and viewed with a Universal Hood II Gel Doc (Bio-Rad).

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Band patterns were analyzed with the GelJ ver. 2 software(29). Band size was standardized using a 1 kb DNA ladder (Promega) with fragments between 250 and 10,000 bp as a reference standard. The similarity coefficients were generated by the Dice method with a 2 % tolerance between rows, and the dendrogram built using the UPGMA method.

Virulence in Galleria mellonella

In vivo virulence was measured for representative bacteria exhibiting the highest biofilm formation rates, as well as non-biofilm-forming isolates. The G. mellonella larvae weighed 150 to 200 mg, were free of apparent damage, exhibited no melaninization (necrotic spots) (Petmmal, Cuautitlán Izcalli, Mexico), and were stored at 30 °C in darkness until use. The infection assays were done using bacterial cultures grown in LB broth until the mean exponential growth phase (OD 600 nm= 0.5). These were centrifuged at 12,000 rpm/min, washed twice with 1 ml 10 mM MgSO4, and resuspended in 1 ml 10 mM MgSO4. Serial dilutions were made of this cell suspension until attaining a bacterial concentration of approximately 1x105 CFU/ml, which was confirmed by CFU count on LB agar. Ten G. mellonella larvae were used for each bacterium to be studied. Using an insulin syringe with a 29G gauge needle, 10 μl bacterial suspension (1 x 105 CFU/ml) were injected into the final pro-leg of each larva. The negative control was ten larvae injected with 10 mM of bacteria-free MgSO4, and an additional ten without inoculation. The inoculated and noninoculated larvae were placed in sterile Petri dishes and incubated at 30 °C in darkness for 96 h. Survival percentages were measured at 24, 48, 72 and 96 h; larvae unresponsive to touch were recorded as dead(21). The virulence assay for each bacterium was run at least twice independently.

Results Phylogenetic groups and genetic relationship of bovine mastitisassociated E. coli

Amplification of the chuA (279 bp), yjaA (211 bp) and TspE4.C2 (152 bp) fragments (Figure 1) showed the 34 isolated BMAEC strains to belong to three phylogenetic groups. Most (67.7 %; 23 isolates) belonged to group A, followed by 17.6 % (6 isolates) in group B1 and the remaining 14.7 % (5 isolates) in group D (Figure 1B). 172

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Figure 1: Agarose gels showing PCR amplification results for A) chuA (279 bp), B) yjaA (211 bp) and C) TspE.C2 (152 bp)

The genetic relationship analysis by rep-PCR using the (GTG)5 oligonucleotide yielded 32 different patterns between 7 and 21 bands, with sizes ranging from 250 to 5,000 bp (Figure 2). The dendrogram based on the Dice similarity coefficient and generated by the UPGMA method indicated that the lowest similarity among the isolates was 58 % while the highest was 100 % (in 2 isolates) (Figure 3). Considering a 70 % genetic similarity level (dotted line), seven groups of bacteria were identified; the largest was group VII with 22 isolates (64.7 %), followed by group III with 4 isolates (11.8 %), group VI with 3 isolates (8.8 %), group I with 2 isolates (5.8 %), and groups II, IV and V with a single isolate each (2.9 %).

Figure 2: Agarose gel of products amplified by (GTG)5-PCR. The base pair size of some bands is indicated by the 1 kb marker (M)

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Figure 3: Grouping band patterns for 34 bovine mastitis-associated E. coli strains, based on the Dice similarity coefficient and generated by UPGMA

Motility, biofilm formation and associated genes Ten of the 34 E. coli isolates were not mobile (-) and the remaining 24 were mobile. Based on their displacement diameters, twelve of these were minimally mobile (+), six were moderately mobile (++), and six were highly mobile (+++) (Figure 4, Table 1). Figure 4: Representative examples of â&#x20AC;&#x153;swarmingâ&#x20AC;? type motility. A) Not mobile, B) Minimally mobile, C) Moderately mobile, D) Highly mobile

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Table 1: Motility, biofilm formation and frequency of biofilm formation-associated genes of the 34 E. coli isolates from subclinical bovine mastitis cases a

E. coli

Motility

Biofilm

MC75 MC80 MC81 MC83 MC13 MC14 MC72 MC19 MC40 MC41 MC59 MC73 MC66 MC2 MC6 MC35 MC36 MC84 MC24 MC56 MC67 MC74 MC77 MC55 MC60 MC54 MC18 MC23 MC57 MC53 MC20 MC70 MC61 MC63

+++ + + + +++ ++ +++ + + + ++ + + ++ ++ ++ + + +++ + +++ + +++ ++ -

W N W N S W M S W N W M W S S S S W W W N M N S W M W M M N N W N M

Genotype csgA/fimA +/+ +/+ +/+ +/+ -/+/+ +/+ -/+ +/+ +/+ -/-/+/+ -/-/-/+ -/+ -/+/+ +/+ +/+ -/-/-/-/+/+ +/+ -/+ -/+/+ +/+ +/+ +/+ -/-

(-) not mobile, (+) minimally mobile, (++) moderately mobile, (+++) highly mobile. b N, negative; W, weak; M, moderate; S, strong.

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Twenty-six (76.5 %) of the isolates formed biofilm to some degree (OD>0.22) while the remaining eight (23.5 %) did not form biofilm (ODâ&#x2030;¤0.22). Of the biofilm-forming isolates seven were classified as having a strong (OD>0.88) and moderate formation capacity (OD 0.45-0.88), and twelve as having a weak one (OD 0.23-0.44) (Table 1). Twenty-two (64.7 %) of the 34 isolates had either csgA or fimA, whereas of the 26 biofilm-forming isolates 15 had one or both of these genes. Both csgA and fimA were present in the seven non-biofilmforming isolates.

E. coli Virulence in G. mellonella

Differences in the pathogenesis of the BMAEC isolates were analyzed by infection trials using G. mellonella larvae. Seven representative isolates were tested: five strong biofilmforming isolates and two non-forming isolates. The biofilm-forming isolates killed 100 % of the larvae 24 h after infection (Figure 5). The two non-biofilm-forming isolates caused from 0 to 20 % mortality at 24 h, and from 10 to 50 % at 96 h. The control resulted in no mortality during the 96-h experiment.

Figure 5: Virulence in G. mellonella larvae of a control (C) and seven representative E. coli isolates: five biofilm-forming isolates (MC2, 6, 13, 19 and 35), and two non-biofilm forming isolates (MC41 and MC80) MC2 MC35

MC6 MC41

MC13 MC80

MC19 C

100

Survival (%)

80 60 40 20 0 0

48 72 Time post-infection (h) 176

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Discussion The severity of E. coli-caused bovine mastitis can range from mild to severe. No specific virulence factors have yet been associated with these disease-causing bacteria(11,30), and it has even been suggested that infection severity is determined by cattle characteristics rather than by the microorganisms(31). One line of evidence suggests that mammary gland infections can be caused by any E. coli strain(11), while another has shown that not all E. coli isolates are capable of producing mastitis in animal models(5). The E. coli strains known to cause bovine mastitis belong mainly to the A and B1 phylogenetic groups, and to a lesser extent to the D group(7). This coincides with the present results in which 67.7 % of the analyzed isolates belong to phylogenetic group A, 17.6 % to B1 and 14.7 % to D. This overall pattern has been reported previously, with 50 % of the E. coli strains associated with both persistent and transient mastitis belonging to the A phylogenetic group, 28.6 % to B1 and 7.1 % to groups B2 and D, respectively(14). In another study 44.88 % of mastitis-associated E. coli belonged to phylogenetic group A, 38.58 % to B1 and 16.53 % to D(32). Similar results have also been reported elsewhere(13,33). In addition, the E. coli isolated from bovine mastitis exhibit great diversity in terms of serotype, disease type (transient or persistent) and genotype, even when they belong to the same phylogenetic group(3,34). The 34 E. coli isolates analyzed here also exhibited broad genetic diversity, since only two had identical band patterns and the remaining 32 had similarity ranging from 92 to 58 %. The present results also indicated no clear separation between the different phylogenetic groups, which shows great heterogeneity among the bovine mastitis-causing E. coli strains in the study area; this also coincides with previous reports(3,30,34,35). The ability to form biofilms in pathogenic bacteria provides them protection against the host immune system and antibiotic resistance, as well as affecting virulence(26). The bacteria associated with bovine mastitis manifest a variable pattern of biofilm formation(36), although recurrent infections have been associated with biofilm-forming strains(16). In the present results 20.6 % of the isolates formed strong to moderate biofilms, while 35.3 % formed weak ones. Other studies have reported similar results with different BMAEC strains having variable biofilm forming capabilities. In one, 18.5 % of the strains had a strong capacity, while 40.7 % had a moderate to weak capacity(36), and in another study 40 % had strong capacity, 12 % had a moderate capacity and 4 % had a weak one(33). Among the 34 analyzed E. coli, the csgA and fimA genes were detected in 52.9 %, only fimA in 11.8 %, and neither gene in the remaining 35.3 %. At least one of the genes was detected in 15 of the 26 biofilm-forming isolates and the seven non-biofilm forming isolates. Both genes have been associated with biofilm formation, as have a variety of other genes and 177

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environmental conditions(37). Further research is clearly needed to generate a more detailed characterization of the factors affecting or promoting biofilm formation in the studied E. coli isolates. Biofilm formation can also vary in response to strain, culture medium, methodology and quantification method. Only one culture medium and one temperature were tested in the present study, raising the possibility that under different conditions the non-biofilm-forming bacteria that were csgA- and fimA-positive may be capable of forming biofilms(38). Bacterial motility is another important factor in the spread and production of persistent infections in cattle(15). In the present results 70.6 % of the studied E. coli were mobile, suggesting that there were both persistent and transient mastitis bacteria among the studied strains. The in vivo results indicated that the biofilm-forming isolates exhibited greater virulence against G. mellonella larvae than the non-biofilm-forming isolates. More study is required to establish the correlation between pathogenesis in vivo in G. mellonella with the severity of E. coli-caused mastitis, but the present results do suggest that this organism is an adequate model for analyzing the pathogenesis of mastitis-causing E. coli.

Conclusions and implications The bovine mastitis-associated E. coli analyzed here were genetically and physiologically diverse. The isolates strongly capable of forming biofilms were more pathogenic than the non-forming isolates. The observed genetic and phenotypic diversity indicates that there is no strain, genotype or specific virulence factor associated with mastitis. However, because biofilm-forming bacteria have been associated with recurrent and persistent mammary gland infections, better strategies for controlling infections need to be developed with the aim of reducing the economic losses associated with the consequent reductions in milk production and quality.

Acknowledgements The research reported here was financed by the PRODEP (IDCA-11106) and UCEMICH (UCEMICH-2016-006 and UCEMICH-2017-004). The authors thank Dr. IvĂĄn Medina and Dr. JosĂŠ Antonio Aguilar for their assistance with manuscript review.

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Literature cited: 1. Halasa T, Huijps K, Østerås O, Hogeveen H. Economic effects of bovine mastitis and mastitis management: A review. Vet Q 2007;29(1):18-31. 2. Wenz JR, Barrington GM, Garry FB, Ellis RP, Magnuson RJ. Escherichia coli isolates’ serotypes, genotypes, and virulence genes and clinical coliform mastitis severity. J Dairy Sci 2006;89(9):3408-3412. 3. Hagiwara S, Mori K, Okada H, Oikawa S, Nagahata H. Acute Escherichia coli mastitis in dairy cattle: diagnostic parameters associated with poor prognosis. J Vet Med Sci 2014;76(11):1431-1436. 4. Shpigel NY, Elazar S, Rosenshine I. Mammary pathogenic Escherichia coli. Curr Opin Microbiol 2008;11(1):60-65. 5. Blum SE, Heller ED, Sela S, Elad D, Edery N, Leitner G. Genomic and phenomic study of mammary pathogenic Escherichia coli. PLoS ONE 2015;10(9):e0136387. 6. Kempf F, Slugocki C, Blum SE, Leitner G, Germon P. Genomic comparative study of bovine mastitis Escherichia coli. PLoS ONE 2016;11(1):e0147954. 7. Goldstone RJ, Harris S, Smith DG. Genomic content typifying a prevalent clade of bovine mastitis-associated Escherichia coli. Sci Rep 2016;(6):30115. 8. Olson MA, Siebach TW, Griffitts JS, Wilson E, Erickson DL. Genome-wide identification of fitness factors in mastitis-associated Escherichia coli. Applied Environ Microbiol 2018;84(2):e02190-17. 9. Leimbach A, Poehlein A, Vollmers J, Görlich D, Daniel R, Dobrindt U. No evidence for a bovine mastitis Escherichia coli pathotype. BMC Genomics 2017:18(1):359. 10. Clermont O, Bonacorsi S, Bingen E. Rapid and simple determination of the Escherichia coli phylogenetic group. Appl Environ Microbiol 2000;66(10):4555-4558. 11. Suojala L, Pohjanvirta T, Simojoki H, Myllyniemi AL, Pitkälä A, Pelkonen S, Pyörälä S. Phylogeny, virulence factors and antimicrobial susceptibility of Escherichia coli isolated in clinical bovine mastitis. Vet Microbiol 2011;147(3-4):383-388. 12. Liu Y, Liu G, Liu W, Liu Y, Ali T, Chen W, Yin J, Han B. Phylogenetic group, virulence factors and antimicrobial resistance of Escherichia coli associated with bovine mastitis. Res Microbiol 2014;165(4):273-277. 13. Keane OM. Genetic diversity, the virulence gene profile and antimicrobial resistance of clinical mastitis-associated Escherichia coli. Res Microbiol 2016;167(8):678-684. 179

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14. Dogan B, Rishniw M, Bruant G, Harel J, Schukken YH, Simpson KW. Phylogroup and lpfA influence epithelial invasion by mastitis associated Escherichia coli. Vet Microbiol 2012;159(1-2):163-170. 15. Lippolis JD, Brunelle BW, Reinhardt TA, Sacco RE, Nonnecke BJ, Dogan B, Simpson K, Schukken YH. Proteomic analysis reveals protein expression differences in Escherichia coli strains associated with persistent versus transient mastitis. J Proteomics 2014;(108):373-381. 16. Melchior MB, Vaarkamp H, Fink-Gremmels J. Biofilms: a role in recurrent mastitis infections?. Vet J 2006;171(3):398-407. 17. Atulya M, Mathew AJ, Rao JV, Rao CM. Influence of milk components in establishing biofilm mediated bacterial mastitis infections in cattle: a fractional factorial approach. Res Vet Sci 2014;96(1):25-27. 18. Ramarao N, Nielsen-Leroux C, Lereclus D. The insect Galleria mellonella as a powerful infection model to investigate bacterial pathogenesis. J Vis Exp 2012;(70):e4392. 19. Nathan S. New to Galleria mellonella: modeling an ExPEC infection. Virulence 2014;5(3):371-374. 20. Alghoribi MF, Gibreel TM, Dodgson AR, Beatson SA Upton M. Galleria mellonella infection model demonstrates high lethality of ST69 and ST127 uropathogenic E. coli. PLoS ONE 2014;9(7):e101547. 21. Morgan JK, Ortiz JA, Riordan JT. The role for TolA in enterohemorrhagic Escherichia coli pathogenesis and virulence gene transcription. Microb Pathog 2014;(77):42-52. 22. Ciesielczuk H, Betts J, Phee L, Doumith M, Hope R, Woodford N, Wareham DW. Comparative virulence of urinary and bloodstream isolates of extra-intestinal pathogenic Escherichia coli in a Galleria mellonella model. Virulence 2015;6(2):145-151. 23. Jiménez-Mejía R, Gudiño-Sosa LF, Aguilar-López JA, Loeza-Lara PD. Caracterización molecular de Escherichia coli resistente a antibióticos aislada de mastitis bovina en Michoacán, México. Rev Mex Cienc Pecu 2017;8(4):387-396. 24. Madico G, Akopyants NS, Berg DE. Arbitrarily primed PCR DNA fingerprinting of Escherichia coli O157: H7 strains by using templates from boiled cultures. J Clin Microbiol 1995;33(6):1534-1536. 25. Stepanović S, Vuković D, Hola V, Bonaventura GD, Djukić S, Ćirković I, Ruzicka F. Quantification of biofilm in microtiter plates: overview of testing conditions and

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practical recommendations for assessment of biofilm production by staphylococci. APMIS 2007;115(8):891-899. 26. Silva VO, Soares LO, Júnior AS, Mantovani HC, ChangYF, Moreira MAS. Biofilm formation on biotic and abiotic surfaces in the presence of antimicrobials by Escherichia coli isolates from cases of bovine mastitis. Appl Environ Microbiol 2014;80(19):61366145. 27. Wilson K. Preparation of genomic DNA from bacteria. Curr Protoc Mol Biol 2001;56(1):241–245. 28. Mohapatra BR, Broersma K, Mazumder A. Comparison of five rep-PCR genomic fingerprinting methods for differentiation of fecal Escherichia coli from humans, poultry and wild birds. FEMS Microbiol Lett 2007;277(1):98-106. 29. Heras J, Domínguez C, Mata E, Pascual V, Lozano C, Torres C, Zarazaga M. GelJ–a tool for analyzing DNA fingerprint gel images. BMC Bioinformatics 2015;(16):270. 30. Blum SE, Leitner G. Genotyping and virulence factors assessment of bovine mastitis Escherichia coli. Vet Microbiol 2013;163(3-4):305-312. 31. Burvenich C, Van Merris V, Mehrzad J, Diez-Fraile A, Duchateau L. Severity of E. coli mastitis is mainly determined by cow factors. Vet Res 2003;34(5):521-564. 32. Ghanbarpour R, Oswald E. Phylogenetic distribution of virulence genes in Escherichia coli isolated from bovine mastitis in Iran. Res Vet Sci 2010;88(1):6-10. 33. Milanov D, Prunić B, Velhner M, Todorović D, Polaček V. Investigation of biofilm formation and phylogenetic typing of Escherichia coli strains isolated from milk of cows with mastitis. Acta Veterinaria 2015;65(2):202-216. 34. Dogan B, Klaessig S, Rishniw M, Almeida RA, Oliver SP, Simpson K, Schukken YH. Adherent and invasive Escherichia coli are associated with persistent bovine mastitis. Vet Microbiol 2006;116(4):270-282. 35. Moser A, Stephan R, Corti S, Lehner A. Resistance profiles and genetic diversity of Escherichia coli strains isolated from acute bovine mastitis. Schweiz Arch Tierheilkd 2013;155(6):351-357. 36. Fernandes JBC, Zanardo LG, Galvão NN, Carvalho IA, Nero LA, Moreira MAS. Escherichia coli from clinical mastitis: serotypes and virulence factors. J Vet Diagn Invest 2011;23(6):1146-1152.

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37. Flemming HC, Wingender J, Szewzyk U, Steinberg P, Rice SA, Kjelleberg S. Biofilms: an emergent form of bacterial life. Nat Rev Microbiol 2016;14(9):563-575. 38. Naves P, Del Prado G, Huelves L, Gracia M, Ruiz V, Blanco J, RodrĂguez-Cerrato V, Ponte MC, Soriano F. Measurement of biofilm formation by clinical isolates of Escherichia coli is methodâ&#x20AC;? dependent. J Appl Microbiol 2008;105(2): 585-590.

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https://doi.org/10.22319/rmcp.v11i1.4902 Article

Technical and environmental characterization of very small, small, medium and large cow-calf operations in Colombia Ricardo González–Quintero ab* María Solange Sánchez–Pinzón c Diana María Bolívar–Vergara d Ngonidzashe Chirinda a Jacobo Arango a Heiber Alexander Pantévez e Guillermo Correa–Londoño d Rolando Barahona–Rosales d Centro Internacional de Agricultura Tropical (CIAT), Km 17 recta Cali – Palmira, Valle del Cauca, Colombia, (0574) 4450000. a

Universidad de Antioquia, Medellín, Colombia.

Compañía Nacional de Chocolates, Rionegro, Antioquia, Colombia.

Universidad Nacional de Colombia. Facultad de Ciencias Agrarias– Sede Medellín.

Federación Colombiana de Ganaderos, Fedegán, Bogotá D.C, Colombia.

Corresponding author: ricardo.gonzalezq@udea.edu.co

Abstract: In Colombia, cow-calf operations account for 18.5% of the national livestock inventory and are a vital link in the national beef production chain. A lack of information has limited adequate technical and environmental planning of cow-calf systems. Based on technical and environmental parameters, a characterization of cow-calf operations was done for very small, small, medium and large producers in Colombia. Analyses were done using data from the Ganadería Colombiana Sostenible (GCS) and LivestockPlus (L+) projects, encompassing information for 2,618 farms classified by production emphasis. A total of 251 cow-calf operations were selected from this total

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and classified based on herd size into very small (1 to 30 head), small (31 to 50 head), medium (51 to 250 head), and large producers (≥251 head). Numerical and categorical variables were grouped within five components: (1) general information; (2) herd composition and management; (3) pasture management; (4) productive and reproductive information; and (5) environmental information. Each component was analyzed by Factorial Analysis for Mixed Data (FAMD), which showed that in the first four components variable distribution was spatially separated from the centroid in each producer category. Medium and large producers were associated with better infrastructure, machinery, equipment, reproductive and productive practices and parameters. No separation from the centroid was present for variables in the environmental information component highlighting a lack of difference in environmental practices among the producer categories. The present characterization can be used to design and implement public policy aimed at technological development and environmental management in Colombia’s livestock sector. Key words: FAMD, Colombian livestock, Environmental impacts, Public policy, Production systems.

Received: 17/05/2018 Accepted: 01/10/2018

Introduction Colombia ranks fourth in Latin America in terms of cattle population(1). In 2018 the country’s cattle population was 26,413,227 animals(2), 45.7 % of which was involved in beef production, 39.3 % in dual-purpose systems and 15.0 % in dairy(3). Nationwide, 514,794 farms were engaged in cattle production, of which 412,829 (80.2 %) had less than 50 heads and were mainly focused on dairy and meat production(2). In the five years from 2014 to 2018 national milk production averaged 6.816 million liters yr-1, while average meat production in carcass for the same period was 926,858 t yr-1(4). The beef production chain in Colombia consists of ranches focusing on cow-calf and growth, finishing and complete cycle. Cow-calf operations account for 18.5 % of the national livestock population and 40.5 % of the total beef production chain(3). Six departments account for the largest number of animals in beef production: Casanare, Meta, Antioquia, Santander, Córdoba and

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Tolima(3). Beef cattle production in Colombia is normally done using extensive systems, with low productivity levels and a largely static national population in recent years(2). Cow-calf operations are vital to meat production, highlighting the need to identify solutions to limitations in production. Industry characterizations help to identify production system strengths and weaknesses in technical, productive, reproductive and environmental aspects(5). Ideally, they help to promote establishment of good livestock production practices and develop technological strategies for increasing productivity and reducing negative environmental impacts. Greater understanding of production system characteristics can be applied to establish policies that promote and develop livestock production in Colombia. It can also guide implementation of the Nationally Appropriate Mitigation Action (NAMA) in Colombia. This in turn can support attainment of this sector’s mitigation goals as established in the “Intended Nationally Determined Contribution” (INDC) submitted to the United Nations Framework Commission on Climate Change in 2015(6). The very few cattle production system characterizations done to date in Colombia have focused on dual-purpose and dairy systems in just a few departments(7). In contrast, only one characterization of cow-calf production systems has been done, meaning there is still not enough data to plan this activity on a national level. The present study is a characterization of the technical and environmental parameters of cow-calf operations operated by very small, small, medium and large producers distributed in thirteen departments in Colombia.

Material and methods Sample population

Data for this characterization was obtained from the Sustainable Colombian Cattle Ranching (Ganadería Colombiana Sostenible - GCS) and LivestockPlus (L+) projects. The GCS project consists of 2,011 surveys administered on livestock farms with different production focuses: cowcalf, finishing, dual-purpose, specialized dairy and complete cycle. Selection of the surveyed areas prioritized livestock regions deemed important in terms of environmental attributes, the existence of ecosystems of global importance and proximity of protected areas and significant livestock production areas. The surveyed cattle farms were in twelve departments (number of municipalities in parentheses): Atlántico (13), Bolívar (4), Boyacá (12), Caldas (2), Cesar (10), La Guajira (5),

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Meta (10), Quindío (9), Risaralda (2), Santander (4), Tolima (6) and Valle del Cauca (7). Three criteria were used to select the farms included in the sample: 1) location in regions prioritized by the GCS project; 2) farm area greater than 2 ha; and 3) owned by Colombian citizen(s). A tencomponent questionnaire was applied at each farm: 1) general farm information; 2) livestock composition and management; 3) pasture management practices; 4) livestock productive and reproductive information; 5) animal health; 6) environmental information; 7) social information; 8) organizational information and relationship with external environment; 9) income from livestock; and 10) financial information. The L+ project involved surveys applied at livestock farms in six municipalities: Cumaral and Restrepo (Piedemonte region), and Puerto Gaitán and Puerto López (Altillanura region) in the department of Meta; and Patía and Mercaderes in the Patía Valley in the department of Cauca. Surveys were conducted at 607 livestock farms in the three regions: Meta Piedmont (150); Meta high plains (147); and dry valley of Patía (310). The questionnaire consisted of eight components: 1) general farm information; 2) farm administrative information; 3) farm land use; 4) technical assistance; 5) productive and reproductive characteristics; 6) association membership; 7) commercial and financial information; and 8) climatic events and environmental practices. From the total sample of 2,618 cattle farms surveyed between the two projects, 251 farms were identified. Of these, 165 (65.7 %) were cow-calf operations without dairy production and 86 (34.3 %) were cow-calf operations with dairy production. This sample (n= 251) was stratified based on herd size(8): very small (VSP: 1 to 30 head); small (SP: 31 to 50 head); medium (MP: 51 to 250 head); and large (LP: ≥251 head). The numerical and categorical variables used in the questionnaires from each project were classified into five groups (Table 1).

Table 1: Components and numerical and categorical variables used in characterizing cow-calf operations Component 1) General information

Numerical variables

Categorical variables

Animals per farm; stocking rate (large livestock unit – AU ha-1); areas (ha): total, livestock, agroforestry crops, perennial crops, transitory crops, monoculture forestry plantations, and improved pastures; topography (%): flat, undulating and hilly; non-bovid livestock inventory: horses, mules, pigs, goats, sheep and poultry.

Installations (stables, drive pen, chute, storage); machinery and equipment (tractor, chainsaw, mowing machine, motor pump, electric fence, electric pump, electronic scale); large species (horses, mules and buffalo); medium species (pigs, goats and sheep); small species (hens and chickens).

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2) Herd composition and management

Stratified inventory: producing cows, parous cows, dry cows, female calves (0-1 yr.), male calves (0-1 yr.), growing females, growing males, heifers, finishing males, young and mature bulls; supply rate (kg yr.-1 AU-1): mineral salts, supplements and concentrates.

Use of records (yes, no); use of (yes, no): mineral salts, white salt, supplements, concentrates.

3) Pasture management

Area (ha): improved pastures, fertilized area; application rate (kg ha-1 yr.-1): fertilizers and amendments.

Improved pastures (yes, no); pasture rotation (yes, no); pasture divisions (yes, no) barbed wire, electric fence, mixed); change in pasture area (yes, no); weeding method (manual, mechanical, chemical, mixed); fertilization (yes, no); amendments (agricultural lime, dolomite lime, other); pasture renovation (yes, no).

4) Production and reproduction information

Milk production (L animal-1 day-1); weight (kg): birth, weaning, final growth; age (months): weaning, final growth; daily weight gaina (kg day-1); preweaningb, finishingc; morality rate (%).

Type of milking (manual, mechanical; animal weighing (measuring tape, scale); weighed at birth (yes, no); weighed at weaning (yes, no); reproduction system (free natural mating, controlled natural mating, artificial insemination, embryo transfer); reproductive examination of cows and bulls (yes, no); weighing of heifers for first service (yes, no); inseminator (yes, no); artificial insemination equipment (yes, no); separation of dry lot (yes, no); birth pasture (yes, no); calculation of intercalving interval (yes, no).

5) Environmental information

aDaily

Forest (yes, no); water source (surface, underground, aqueduct); springs (yes, no); water available in summer for livestock (yes, no). irrigation system (yes, no); wastewater treatment system (yes, no); solid waste management (incineration, burying, third party).

weight gain (kg day-1): estimated based on initial and final weights during weaning and finishing phases and the length of each stage; bBirth to weaning; cWeaning to slaughter.

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Statistical analyses

Analysis each of the five components was done with the Factorial Analysis for Mixed Data multivariate technique (FAMD), using the FAMD function of the FactoMineR package for the R statistical package(9). The FAMD is a factorial method applied to analyze data sets in which a group of individuals is described with quantitative and qualitative variables. The term â&#x20AC;&#x153;mixedâ&#x20AC;? refers to the simultaneous presence of qualitative and quantitative variables as active elements in the sampling units. This method allows simultaneous exploration of these variables by combining principal component analysis (PCA) and multiple correspondence analysis (MCA)(10). The quantitative variables were centered and normalized to Z values, while the qualitative variables were disaggregated into a normalized disjunctive matrix. Starting from mixed samples, this method allows graphic evaluation of the similarities/dissimilarities between productive units (distances) and the correlations between continuous variables(10). Prior to the application of the FAMD, missing data was imputed using the algorithm implemented in the impute FAMD function, which is part of the missMDA package(11). The producer category and animal number variables were included in the FAMD as supplementary inputs to exclude their participation in model construction.

Results and discussion Overall, most (74.5 %) of the producers included in the study were VSP and SP, while just 25.4 % were MP and LP (Table 2). This coincides with previous reports of livestock farm type distributions in Colombia(2,8), in which 81 % of farms with cattle had fewer than 50 head and 18 % had from 51 to 500 head. Generally similar proportions have been reported for cattle farms in the Amazon region of Ecuador, with 64.5 % of farms having from 1 to 30 head of cattle(12). This highlights the need to create agricultural public policy for cattle productive and reproductive improvement aimed at this type of producer.

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Table 2: Farm and livestock characteristics and land use information for each cow-calf producer category (average ± standard deviation) Variable VSP SP MP LP Total number of producers Animals per farm, number Total farm area, ha Area for cattle, ha Large Livestock Units (AU) per farm Stocking rate, AU ha-1 Farms with agroforest crops, %

162 (64.5%) 13.4 ± 7.7 16.3 ± 26.3 16.2 ± 26.4 10.0 ± 5.9 1.2 ± 0.9 8.5

25 (10.0%) 39.4 ± 6.9 40.6 ± 39.6 40.4 ± 39.6 30.8 ± 7.3 1.5 ± 1.1 0

59 (23.5%) 108.8 ± 56.6 93.8 ± 76.9 93.4 ± 77.0 80.1 ± 43.2 1.3 ± 0.9 1.9

5 (2.0%) 329.2 ± 57.1 135.3 ± 43.3 134.9 ± 43.3 253.5 ± 32.6 2.1 ± 0.7 0

Farm area in agroforest crops, % total area*

13.3 ± 11.8

---

15.0

---

10.2

20.0

9.3

20.0

11.1 ± 15.0

2.3 ± 0.9

2.9 ± 4.9

0.6

7.0

10.0

5.6

20.0

12.9 ± 14.2

16.8 ± 0.2

10.2 ± 9.7

3.00

47.5

30.0

33.3

40.0

25.7 ± 34.0

21.4 ± 35.5

20.0 ± 30.7

24.8 ± 42.9

Farms with perrennial crops, % Farm area in perennial crops, % total area* Farms with transitory crops, % Farm area in transitory crops, % total area* Farms with improved pastures, % Farm area in improved pastures, % total area*

Flat area in farm, % total area 48.2 ± 38.3 50.5 ± 37.6 54.5 ± 39.5 62.0 ± 52.2 VSP= very small producers; SP= small producers; MP= medium producers; LP= large producers. *Average calculated based on farms with this type of crop.

Factorial Analysis for Mixed Data (FAMD) analyses were run for each of the five evaluated components and include: (a) the spatial relationship between qualitative variable centroids, with producer category as supplementary variable, and (b) the projection of the continuous variables on the plane of the first two factorial dimensions, with number of animals as a supplementary variable (Figures 1, 2, 3, 4 and 5). The first two dimensions captured 39.5% of the variability in the General Farm Information component (Figure 1), 24.8 % in the Herd Composition and Management component (Figure 2), 29.7 % in the Pasture Management component (Figure 3), 47.2 % in the Productive and Reproductive Information component (Figure 4) and 37.9 % in the Environmental Information component (Figure 5). The supplementary variables did not participate in model construction. The different producer categories (VSP, SP, MP and LP) were clearly separated from the centroid in the first four components. No separation from the centroid was present in the environmental component, suggesting that there were no marked differences in environmental practices associated with producer size.

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General farm information

The configuration of the categorical variables used to characterize the general farm information resulted in an orderly alignment of the producer categories in the first dimension of the FAMD graph (Figure 1 (a)). Close associations existed between the LP and MP categories and the machinery and equipment variables (electronic scale, tractor, chainsaw, motor pump, electric pump, drive pen, stable, chute and storehouse). In contrast variables related to non-use of these technologies were to the left of dimension 1, alongside the variables of agroforestry crops and monoculture forest plantations, both associated with the VSP and SP categories. In dimension 2, the presence of small, medium and large species on the farm, and use of a mower and electric fence grouped in the lower portion while the absence and/or non-use of these variables were located in the upper portion; no apparent relationship existed between these variables and producer category. Figure 1: Spatial projection of General Farm Information categorical (a) and numerical (b) variables

a) Spatial projection in first and second dimensions of General Farm Information categorical variable categories: LP = large farms; MP = medium farms; SP = small farms; VSP = very small farms; 1 = no stable; 2 = yes stable; 3 = no drive pen; 4 = yes drive pen; 5 = no chute; 6 = yes chute; 7 = no storage house; 8 = yes storage house; 9 = no electric fence; 10 = yes electric fence; 11 = no electric pump; 12 = yes electric pump; 13 = no electronic scale; 14 = yes electronic scale; 15 = no tractor; 16 = yes tractor; 17 = no chainsaw; 18 = yes chainsaw; 19 = no mower; 20 = yes mower; 21 = no motor pump; 22 = yes motor pump; 23 = no agroforestry crops; 24 = yes agroforestry crops; 25 = no perennial crops; 26 = yes perennial crops; 27 = no transitory crops; 28 = yes transitory crops; 29 = no monoculture forest plantations; 30 = yes monoculture forest plantations; 31 = no improved pastures; 32 = yes improved pastures; 33 = no large species; 34 = yes large species; 35 = no medium species; 36 = yes medium species; 37 = no small species; and 38 = yes small species. Spatial projection of numerical variable categories b): Farm Area = total area of farm; % Flat = flat area on farm; % Undulating = undulating area on farm; % Hilly: hilly area on farm; Agroforestry = area in

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agroforestry crops; Perennial = area in perennial crops; Transitory = area in transitory crops; Monoculture Forests = area in monoculture forest plantations; Improved pastures = area in improved pastures; Livestock Area = area for livestock; Buffalo = number of buffaloes; Horses = number of horses; Mules = number of mules; Pigs = number of pigs; Goats = number of goats; Sheep = number of sheep; Hens = number of hens; Chickens = number of chickens; Cattle = number of cattle.

Six numerical variables were positively related to the first dimension, representing farm size: total farm area; livestock area; improved pasture area; agroforestry crop area; monoculture forest plantation area; and transitory crop area (Figure 1b). These variables were also closely linked to the number of cattle; for instance, the number of buffaloes and undulating area on a farm were negatively associated to dimension 1, meaning that these conditions were more common at small farms. In dimension 2, positively linked variables included number of pigs and hilly area on farm, while the negatively linked variables were number of hens, goats and flat area on farm. The association of MP and LP with infrastructure (i.e. machinery, equipment and facilities) reflects their greater economic capacity. In addition, cattle producers with larger herds generate more income and profits than smaller producers, allowing them to build facilities and purchase more and better equipment and machinery, all of which are costly inputs in livestock production(7). Similar circumstances have been reported for Mexico in which larger farms have greater machinery and equipment availability and these were more apt for livestock production(13). Larger farms were negatively associated with the undulating area on farm variable but positively associated with the presence of mules and horses (large species). It is noteworthy that the presence and use of other animal species could favor food availability, stability, access and consumption; these are the four dimensions of food security and may benefit producer sustainability(14). Hilly slopes (>30 %) are not suitable for grazing(12). The percentage of hilly area (slope >60%) on farm was highest in the VSP (25.5 %), followed by the SP (22.0 %), MP (14.2 %) and LP (10.5 %). Grazing livestock on hilly slopes can cause land degradation due to increased erosion associated with livestock trampling(15). This leads to decreased soil filtration capacity and consequent greater surface runoff during rains(16), which translate to lower biomass production and livestock productivity. Also, as pastures degrade net annual GHG emissions tend to rise(17). It is therefore important to estimate GHG emissions on livestock farms to identify their contribution to global GHG emissions and propose appropriate mitigation actions. The number of the evaluated cow-calf operations that also engaged in agricultural activities or grew some crop was low in all four producer categories (Table 2). This contrasts with small producers in the state of Veracruz, Mexico, where 85% combined livestock activity with agriculture(18). It is to be expected that the overall crop area on the farms was low. Most cow-calf operations in Colombia are extensive systems(19), and the current results are therefore more comparable to those 191

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for extensive and semi-extensive livestock systems in Mexico(20), in which the area used to grow crops was reported as less than 20 %. Joint agricultural and livestock production helps to guarantee food security. It can also contribute to climate change adaptation and mitigation by, for example, incorporating short-cycle or transitory crops into grazing systems(21).

Technical component Herd composition and management The categorical variables related to supply of supplements, concentrates and mineralized salts concentrated to the left of dimension 1, whereas those related to their absence and the use of white salt were to the right (Figure 2 (a)). In dimension 2, the livestock records variable was located at the top of the graph while the lack of records was at the bottom. Overall, this suggests that the SP, MP and LP kept livestock records and provided larger quantities of feed complements, while the VSP were mainly characterized by supplying white salt, not keeping livestock records and not supplying feed concentrates or supplements. The numerical variables showed mineralized salt supply rate (kg yr.-1 AU-1) was positively related to dimension 1, while the concentrates and supplements supply rates (kg yr.-1 AU-1) were negatively related to it (Figure 2 (b)). This coincides with the higher concentrates and supplements supply rates in the MP and LP (Table 3). The variables cows per bull, percentage female calves, percentage male calves, percentage parous cows born and percentage milked cows were positively associated with dimension 2; these variables were also linked to the number of animalsâ&#x20AC;&#x2122; variable. The percentages of growing males, bulls and finishing steers were negatively associated with this dimension. Figure 2: Spatial projection of Herd Composition and Management categorical (a) and numerical (b) variables

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a) Spatial projection in first and second dimensions of Herd Composition and Management categorical variables: LP = large farms; MP = medium farms; SP = small farms; VSP = very small farms; 39 = no livestock records; 40 = yes livestock records; 41 = no mineralized salts; 42 = yes mineralized salts; 43 = no white salt; 44 = yes white salt; 45 = no supplements; 46 = yes supplements; 47 = no concentrate; and 48 = yes concentrate. Spatial projection of numerical variables b): Cows per bull = number of cows per bull; % Milked cows = % cows being milked; % Parous cows= % of cows that have given birth; % Dry cows = % dry cows; % Female calves = % female calves (0 to 1 yr.); % Male calves = % male calves (0 to 1 yr.); % Growing females = % growing females; % Growing males = % growing males; % Heifers = % heifers; % Finishing steers = % finishing steers; % Bulls = % bulls; Concentrate (kg/yr/AU) = feed concentrate supply rate; Supplements (kg/yr/AU) = supplement supply rate; Salt (kg/yr/AU) = salt supply rate; and Cattle = number of cattle.

Table 3: Herd composition, productive and reproductive parameters, and complementary feed supply rates by cow-calf producer size category (average ± standard deviation) Variables Herd composition Cows in production, AU Parous cows, AU Dry cows, AU Female calves (0-1 yr.), AU Male calves (0-1 yr.), AU Growing females (1-2 yrs.), AU Growing males (1-2 yrs.), AU Heifers (2-3 yrs.), AU Finishing steers (2-3 yrs.), AU Bulls, AU Complementary feed Concentrates, kg yr.-1 AU-1* Supplements, kg yr.-1 AU -1* Mineral salts, kg yr.-1 AU -1* Productive and reproductive parameters Birth weight, kg Weaning weight, kg Weaning age, months Preweaning DWG, kg day-1 Mortality, % Milk production, L animal-1 day-1

VSP

1.1 ± 2.3 2.5 ± 3.3 2.1 ± 2.7 0.5 ± 0.6 0.4 ± 0.4 1.0 ± 1.9 0.9 ± 1.9 1.2 ± 2.5 0.3 ± 1.3 0.5 ± 0.7

2.0 ± 4.0 8.9 ± 6.4 9.4 ± 10.1 1.3 ± 1.1 1.1 ± 0.9 2.3 ± 3.0 1.0 ± 1.8 4.4 ± 5.8 0.4 ± 1.2 1.0 ± 1.1

3.7 ± 9.8 25.5 ± 26.6 18.1 ± 19.8 4.5 ± 3.9 3.9 ± 3.3 6.2 ± 7.1 3.5 ± 6.9 7.7 ± 11.6 4.9 ± 12.7 3.7 ± 5.7

19.0 ± 42.5 58.4 ± 42.2 83.4 ± 33.6 11.6 ± 3.2 8.9 ± 4.7 20.5 ± 22.4 9.4 ± 18.3 13.0 ± 15.8 23.8 ± 53.3 5.5 ± 3.5

53.6 ± 25.3 16.5 ± 22.5 32.3 ± 5.7

55.8 ± 30.1 15.9 ± 15.5 30.7 ± 3.4

60.6 ± 45.5 33.8 ± 22.2 32.4 ± 3.2

85.4 ± 75.9 34.3 ± 30.6 31.6 ± 1.4

31.5 ± 4.4 32.3 ± 4.4 34.1 ± 4.0 34.3 ± 4.0 149.4 ± 34.8 175.0 ± 46.2 179.2 ± 42.3 176.7 ± 5.8 7.3 ± 1.1 7.8 ± 1.4 8.0 ± 0.9 8.0 ± 1.7 0.60 ± 0.22 0.59 ± 0.17 0.61 ± 0.18 0.63 ± 0.15 14.6 ± 10.9 6.1 ± 3.4 3.8 ± 3.0 3.0 ± 2.9 3.4 ± 1.4 3.5 ± 1.3 2.8 ± 1.7 2.9 ± 1.5

VSP= very small farms; SP= small farms; MP= medium farms; LP= large farms; DWG= Daily weight gain. *Average calculated based on farms using this technique.

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Most grasses cultivated in the tropics are mineral deficient. Cow-calf operations are largely extensive grazing systems using high percentages of natural pastures. Mineral supplementation is therefore necessary to minimize the negative effects of macro- and micronutrient deficiencies(22). Use of mineralized salts was associated with the MP and LP while use of white salt was associated with the VSP. The MP and LP apparently provide more complete mineral supplements, which may result in better reproductive and productive behavior than in the VSP, which do not provide mineralized salts supplementation, possibly due to the high cost or cultural aspects. Use of feed concentrates was associated most clearly with the LP, possibly because larger farms tend to have higher percentages of milked cows and higher supplementation rates (Table 3). In various characterization studies of extensive systems LPs are identified as generating the highest income. This allows them to purchase feed supplements, among the costliest inputs in cattle herds(12), and which can translate into higher productivity. Smaller producers often provided little or no supplements. For example, in combination cow-calf/dairy systems in the department of Cundinamarca, Colombia, small and medium producers did not provide supplements or concentrates and feeding consisted mainly of grazing natural grasslands(23). By basing feeding on natural and/or degraded pastures with some cases of improved concentrates and pastures, VSP, SP and MP may have lower yields. The minimal use of livestock records and productive and reproductive control associated with the VSP in the present characterization coincides with similar results for small-scale producers in Cundinamarca, Colombia(23). Promotion of livestock records and technical control could improve monitoring of productive and reproductive parameters at these farms, which is vital if producers are to make informed decisions aimed at increasing productivity.

Pasture management

The categorical variables in the pasture management component tended to group to the right side of dimension 1 (Figure 3 (a)), particularly the variables related to chemical fertilization, pasture renovation, pasture rotation and change, application of amendments and use of electric fencing. In contrast the variables related to non-implementation of these practices and/or activities grouped generally to the left side of dimension 1. In dimension 2, the variables of mixed pasture division (barbed wire and electric fence) and chemical and mixed-method weed control grouped at the top; the opposites of these variables grouped towards the bottom. These patterns suggest the MP, LP and SP tend to use better pasture improvement and conservation practices than the VSP.

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Pasture rotation and mixed-method division of pastures were associated with the MP and LP (Figure 3 (a)), which tend to use alternate and rotational grazing. An adequate pasture rotation system helps to increase biomass quantity and quality, and consequently livestock system productivity(24,25). Use of electric fences allows the changing of pasture area, facilitating proper pasture management and greater productivity. Farms with larger herds can therefore more easily rotate pastures and use electric fences to benefit productive performance.

Figure 3: Spatial projection of Pasture Management categorical (a) and numerical (b) variables

a) Spatial projection in first and second dimensions of Herd Composition and Management categorical variables: LP = large farms; MP = medium farms; SP = small farms; VSP = very small farms; 49 = no improved pastures; 50 = yes improved pastures; 51 = no pasture rotation; 52 = yes pasture rotation; 53 = no barbed wire pasture divisions; 54 = yes barbed wire pasture divisions; 55 = no electric fence pasture divisions; 56 = yes electric fence pasture divisions; 57 = no mixed-method (barbed wire, electric fence, etc.) pasture divisions; 58 = yes mixed-method (barbed wire, electric fence, etc.) pasture divisions; 59 = no change in pasture area; 60 = yes change in pasture area; 61 = no manual weed control; 62 = yes manual weed control; 63 = no mechanical weed control; 64 = yes mechanical weed control; 65 = no chemical weed control; 66 = yes chemical weed control; 67 = no mixed weed control; 68 = yes mixed weed control; 69 = no chemical fertilization; 70 = yes chemical fertilization; 71 = no agricultural lime; 72 = yes agricultural lime; 73 = no dolomite lime; 74 = yes dolomite lime; 75 = no other additive use; 76 = yes other additive use; 77 = no pasture renovation; and 78 = yes pasture renovation. b) Numerical variables: Improved pasture area = improved pasture area; Chemical fertilization (kg/ha/yr) = chemical fertilization rate; Fertilized area (ha) = farm area fertilized; Amendments (kg/ha/yr) = amendment application rate; Cattle = number of cattle on farm.

Sole use of manual weed control was associated with the VSP; it has the advantage of low environmental impact but is labor intensive. Use of mixed weeding methods was associated mainly with the MP and LP, suggesting these producers are concerned about weeds in pastures. These results agree with a report for cow-calf operations in Cundinamarca, Colombia, where many producers combined different weeding methods, including mechanical, manual and chemical(23).

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The numerical variables of improved pasture area, fertilized area, fertilization rate and number of animals were positively related to dimension 1 (Figure 3 (b)). Chemical fertilization was associated with farms with more animals, although less than 28 % of producers in all four categories used this technique. Rates as low as 14 % have been reported for cow-calf operations in Colombia(23). At most cattle farms chemical fertilization is done when a pasture is established, but no maintenance fertilization is done. In the present results fertilizer application rates ranged from 40 to 104 kg N ha-1 yr-1, the lowest rates being in the VSP and SP. Recommended rates for permanent pastures range from 100 to 200 kg N ha-1 year-1(26), suggesting that the levels applied in the studied farms were insufficient for pastures to attain optimum yields. However, in any given pasture the optimum fertilizer dose will depend on soil fertility and physical characteristics, environmental variables, and the crop to be established, among other factors.

Productive and reproductive information Among the categorical variables for productive and reproductive information (Figure 4 (a)), the productive and reproductive practices variables tended to group on the right side of dimension 1: weighing at birth and weaning, controlled mating, artificial insemination, embryo transfer, palpation of cows, reproductive examination of bulls, weighing of heifers for first service and separation of the dry cow lot, in addition to existence of a birth pasture, artificial insemination equipment and inseminator. Those variables quantifying the absence of these practices, activities, facilities and/or equipment grouped to the left side of dimension 1. Figure 4: Spatial projection of Productive and Reproductive Information categorical (a) and numerical (b) variables

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a) Spatial projection in first and second dimensions of Herd Composition and Management categorical variables: LP = large farms; MP = medium farms; SP = small farms; VSP = very small farms; 79 = no weighing with measuring tape; 80 = yes weighing with measuring tape; 81 = no weighing with scale; 82 = yes weighing with scale; 83 = no weighing at birth; 84 = yes weighing at birth; 85 = no weighing at weaning; 86 = yes weighing at weaning; 87 = no breeding male calves; 88 = yes breeding male calves; 89 = no finishing animals; 90 = yes finishing animals; 91 = no natural mating; 92 = yes natural mating; 93 = no controlled mating; 94 = yes controlled mating; 95 = no artificial insemination; 96 = yes artificial insemination; 97 = no embryo transfer; 98 = yes embryo transfer; 99 = no cow reproductive examination; 100 = yes cow reproductive examination; 101 = no bull reproductive examination; 102 = yes bull reproductive examination; 103= no weighing heifers for first service; 104 = yes weighing heifers for first service; 105 = no inseminator; 106 = yes inseminator; 107 = no insemination equipment; 108 = yes insemination equipment; 109 = no dry cow lot separation; 110 = yes dry cow lot separation; 111 = no birth pasture; 112 = yes birth pasture; 113 = no calculation intercalving interval; and 114 = yes calculation intercalving interval. b) Spatial projection of numerical variables: Stocking rate (AU/ha) = stocking rate; Milked cows = number of cows milked; Milk yield (L/Farm/day) = daily milk production per farm; Milk yield (L/cow/day) = daily milk production per cow; Birth weight = animal weight at birth; Weaning weight = animal weight at weaning; Weaning age: age at weaning; Final finishing age = animal final finishing age; Final finishing weight= animal final finishing weight; DWG weaning stage (kg/day) = animal daily weight gain during weaning stage; DWG finishing stage (kg/day) = animal daily weight gain during finishing stage; Number of births = number of births at farm; Mortality rate = mortality rate at farm; Cattle = number of cattle at farm.

In dimension 2, production practice variables such as weighing by measuring tape, breeding male calves and finishing animals grouped at the bottom. Variables representing the absence of these practices grouped in the upper portion, as well as calculation of intercalving interval and weighing with scales. These groupings suggest that the MP and LP implemented better productive and reproductive practices than did the VSP and SP. Use of better reproductive and productive practices by the MP and LP may translate into higher productivity. These results are similar to the reported absence at small producers of practices such as weighing heifers for first service, reproductive examinations, use of artificial insemination, availability of birth pastures, separation of the dry cow lot and calculation of the intercalving interval(23). These reproductive practices are more common in larger more specialized livestock systems with greater financial resources, and manifest in higher rates of productivity(7). Weighing cattle is important for assessing growth, planning feeding to maximize yields and take full advantage of available feed resources, properly managing technical and financial records, and implementing monitoring, medication, genetic improvement and reproductive management(27). More of the MP and LP producers weighed their animals than did the SP and VSP, a fact which may be linked to the greater availability of scales at larger farms. Barimetry facilitates estimation of approximate animal live weight through body metrics and formulas(27). These should therefore be promoted and applied at VSP and SP farms, where scales are rare, and thus provide them with greater control of yield rates and potentially increase their productivity.

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The variables of weaning age, number of milked cows, number of births and total milk production (L farm-1 day-1) were positively related to each other and to dimension 2 (Figure 4 (b)). One measure that could improve herd reproductive performance is early weaning, which reduces cow energy requirements, resulting in weight gain, improved body condition, increased pregnancy rates and better overall reproductive performance(28). However, this requires adequate nutritional management of weaned calves to ensure sufficient quantities of good quality energy and protein, which can incur additional costs for producers(29). In the present analysis the number of animals was negatively linked to mortality rates (Figure 4 (b)). The opposite was reported for livestock systems in Costa Rica where mortality rates tended to be lower at smaller farms (<30 head)(30). In small farms the death of one animal has a proportionally greater effect than it would at larger farms. No matter farm size, a lower mortality rate can result in greater profitability and competitiveness, and consequent higher income. Preweaning daily weight gain (DWG), and weights at birth and weaning were higher in the MP and LP. Higher birth weight offspring are reported to grow more rapidly and experience lower mortality, which would support the reported positive correlation between birth weight and weaning weight in beef cattle(31). However, some studies indicate that offspring with the highest birth weight do not necessarily reach the highest weaning weight(32,33). Nonetheless, a greater preweaning DWG does result in higher weight at weaning, which, through sale of heavier animals for finishing, can result in greater profitability(32).

Environmental information

In this component no separation from the centroid was observed (Figure 5), suggesting that the different producer categories did not differ in terms of environmental practices. Promoting broader implementation of good environmental practices on farms requires strategies that generate productive and economic benefits for producers in addition to environmental benefits such as climate change mitigation and adaptation. For example, the conservation of trees and shrubs in pastures and silvopastoral systems is a production strategy adopted in livestock systems in the Latin American tropics. It contributes to reducing extreme temperatures, conserving wildlife, controlling water quality in watersheds, capturing atmospheric carbon, mitigating climate change, as well as improving milk and meat production and livestock profitability(34).

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Figure 5: Spatial projection of Environmental Information categorical (a) and numerical (b) variables.

Spatial projection in first and second dimensions of Environmental Information categorical variables: LP = large farms; MP = medium farms; SP = small farms; VSP = very small farms; 115 = no forest; 116 = yes forest; 117 = no surface water use; 118 = yes surface water use; 119 = no underground water use; 120 = yes underground water use; 121 = no aqueduct water use; 122 = yes aqueduct water use; 123 = no springs; 124 = yes springs; 125 = no summer water available for livestock; 126 = yes summer water available for livestock; 127 = no irrigation system; 128 = yes irrigation system; 129 = no wastewater treatment system; 130 = yes wastewater treatment system; 131 = no solid waste incinerated; 132 = yes solid waste incinerated; 133 = no solid waste buried; 134 = yes solid waste buried; 135 = no third party waste management; and 136 = yes third party waste management.

The wastewater generated in livestock systems usually originates from any on-site dwellings and the stables. Few (<40%) of the farms included in the study employed wastewater treatment systems meaning any liquid waste was discharged directly into water sources and soils. Those farms with treatment systems largely used septic tanks and biodigesters, which are primary and secondary low nutrient removal processes. Therefore, direct discharges and effluents from treatment systems could generate eutrophication in water bodies in response to nitrogen (N) and phosphorus (P) from

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cattle excreta. Tertiary treatment systems that increase nutrient removal from discharge are vital to reduce eutrophication phenomena. Non-biodegradable solid waste is one of the main environmental impacts of the cattle production chain in Colombia, but a lack of quantitative studies prevents accurate estimation of its magnitude(35). Incineration and burial were the main forms of solid waste management and were used at more than 70% of the farms. Incineration generates GHG emissions that increases potential global warming, while burial without proper sanitary controls can contaminate aquifers. Characterization of cattle producer solid waste processing capacity is an important variable for quantitatively assessing the degree of potential negative impacts generated at farms and for establishing management strategies to minimize them.

Conclusions and implications In the four components of general farm information, herd composition and management, pasture management, and productive and reproductive information, the variables exhibited spatial separation from the centroid in each producer category. Generally, the medium and large producers were associated with variables indicating the presence of more sophisticated infrastructure, machinery and equipment, more advanced pasture management practices and better reproductive and productive parameters. All these variables in turn can be linked to greater production capacity and income. Only the environmental information variables lacked clear separation from the centroid in all four producer categories, suggesting that producer size had no effect on implementation of environmental practices. The most relevant environmental aspects of livestock systems need to be identified to include them in future characterization studies and increase understanding of the environmental impacts associated with livestock production. The principal characteristics identified for each producer category can serve as a basis for designing and implementing technological development policies and programs. Based on the number of small and very small producers and their characteristics these two categories would benefit from the mitigation actions established in the NDC for Colombia, including rational grazing, grassland rehabilitation and use of intensive silvopastoral systems.

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Acknowledgements This study is part of the LivestockPlus project funded by the Consultative Group on International Agricultural Research (CGIAR) Program (CRP) on Climate Change, Agriculture and Food Security. In addition, this work was also done as part of the Livestock CRP. We thank all donors that globally support the work of the CRP programs through their contributions to the CGIAR system. We are thankful to the Colombian Sustainable Cattle Ranching project implemented by the Federación Colombiana de Ganaderos, the Fundation Centro para la Investigación en Sistemas Sostenibles de Producción Agropecuaria, Fondo Acción, and The Nature Conservancy.

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https://doi.org/10.22319/rmcp.v11i1.4923 Review

Heat stress impacts in hair sheep production. Review

Ricardo Vicente Pérez a Ulises Macías Cruz b* Leonel Avendaño Reyes b Abelardo Correa-Calderón b María de los Ángeles López Baca c Ana L. Lara Rivera b

Universidad de Guadalajara, Centro Universitario de la Costa Sur, Departamento de Producción Agrícola, Autlán de Navarro, Jal., México. b

Universidad Autónoma de Baja California, Instituto de Ciencias Agrícolas, Valle de Mexicali, B.C., México. c

Centro de Investigación en Alimentación y Desarrollo A.C., Hermosillo, Sonora, México.

*Corresponding author: ulisesmacias1988@hotmail.com

Abstract: In view of the problem of global warming and climate change, small ruminants may be key to maintain animal protein production since they are more heat stress tolerant than most other domestic animals. Hair breed sheep are known for their ability to grow and reproduce under conditions of high temperatures and low nutrient availability. Their adaptation to heat stress involves a complex interaction between thermoregulation mechanisms and the presence of genetic factors. These confer physiological plasticity to these breeds, allowing them to tolerate hot climates without drastically affecting their productivity. In Mexico, hair sheep are distributed in different climates throughout the country. The lack of strict reproductive seasonality in these breeds has allowed the sheep industry to maintain constant mutton

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production year-round. Very limited research has addressed hair breedsâ&#x20AC;&#x2122; ability to produce under heat stress conditions. The present review describes the effects of heat stress on reproductive performance, lamb growth and thermoregulation in hair sheep breeds. Key words: Heat-adapted sheep, Hyperthermia, Homothermia, Sheep fertility, Hair breeds.

Received: 03/06/2018 Accepted: 10/12/2018

Introduction

Climate change derived from greenhouse gas emissions is the principal phenomenon threatening production of animal origin food and by consequently food security(1). The fenomenon is increasing environmental temperatures and changing circannual rainfall patterns in agroecological regions worldwide. Global warming creates climatic conditions of promote heat stress (HS) for domestic animals in regions where it has not occurred historically. In regions with naturally high temperatures HS has raised livestock mortality rates as temperatures exceed animalsâ&#x20AC;&#x2122; capacity to maintain normothermia(2).

Small ruminant systems predominate in arid, semi-arid and desert regions because, compared to cattle, they are more able to survive in low food availability conditions and have higher HS tolerance(1,3). High temperatures can negatively affect development and productivity in sheep since they reduce feed intake and increase energy demands due to activation of thermoregulation mechanisms. Heat stressed sheep exhibit low fertility and fetal development and growth, as well as unsuitble weight gain and feed efficiency during the fattening period(4,5,6). High temperatures can also negatively affect sheep carcass characteristics and meat quality(3,5). However, the degree to which HS affects productivity in sheep depends on how well a given breed is adapted to high temperatures, with hair breeds being generally less HS susceptible(7,8).

The hair sheep breeds used in Mexico were developed in hot climates, mostly in Africa, and therefore have the genetic capacity to more easily tolerate and adapt to hot climates(9). some studies done in dry, and arid regions from northwest Mexico during the hot summer months 206

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have found that in hair sheep breeds (Pelibuey, Katahdin, Dorper and crosses) productive and reproductive variables do not decline drastically(10,11). Activation of specific physiological, metabolic and endocrinological thermoregulatory mechanisms are partially responsible for their ability to avoid hyperthermia(11,12,13). They also have phenotypic and genotypic characteristics that allow them to be more HS tolerant(8). The present review addresses the effects of heat stress (HS) on reproductive behavior, lamb growth and thermoregulation in hair sheep.

Climate change and sheep production

The worldâ&#x20AC;&#x2122;s hot regions currently occupy about 50% of the surface, although projections suggest an increase due to global warming. Climate change is also generating unpredictable variations in the timing and amount of rainfall, as well as decreasing in vegetation cover and an increase in the amount of desert cover. All these effects have contributed to lowering the availability and quality of forage for livestock(1). Compared to other domestic species, small ruminants such as sheep are well adapted to extreme climate conditions, making them an option in arid and semi-arid regions with low forage resource availability(14).

Sheep have the ability to convert fibrous and poor-quality food into products for human consumption (e.g. meat, milk and wool) under precarious production conditions in which other domestic animals (except goats) can barely survive. It should be noted that sheep from native breeds to arid and semi-arid regions are better adapted to HS and surviving in precarious extensive conditions (3,14). Well-informed selection of appropriate breeds is therefore an effective strategy for maintaining meat production in the face of climate change(1).

In Mexico, hair sheep breeds adequately tolerate HS climatic conditions in hot agroecological regions. High temperatures in these regions are not a factor that substantially contributes to decrease reproductive capacity and growth in lambs(12,15,16). Hair sheep breeds adapted to hot climates exhibit physiological and metabolic plasticity which allows them to tolerate this environment type without compromising their productivity(13).

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Heat stress in hair sheep

Decreased feed intake and activation of the hypothalamic-pituitary-adrenal axis in response to HS results in low productive and reproductive behavior in sheep, which affects herd productivity(4,17). However, these alterations are not as marked in hair sheep as they can be in wool breeds(5,12).

Effects on reproduction

Fertility in hair sheep seems to be more affected by photoperiod and nutritional signals than by high environmental temperatures. Estrus and ovulation are reported to be unaffected by summer HS(12,15,16), although corpus luteum functionality (based on blood progesterone levels) decreases in response to acute(18) and chronic HS(12,15). This decrease in progesterone may be due to premature regression of the corpus luteum, as reported in Pelibuey sheep after being subjected to 37 Âą 2.5 Â°C in a environmental chamber, although early embryonic development was unaltered(18).

The mechanism by which hair sheep maintain reproductive activity and fertility in hyperthermia conditions remains unknown. Heat stress is known to reduce reproductive function due to activation of the hypothalamic-pituitary-adrenal axis (stress axis), which suppresses function of the hypothalamic-pituitary-gonadal axis (reproductive axis)(1). The stress axis promotes synthesis and release of cortisol in the adrenal glands, and this hormone inhibits production of gonadotropin-releasing hormone (GnRH) at the hypothalamus level(17). It is necessary to stimulate synthesis and release of follicle-stimulating hormone (FSH) and luteinizing hormone (LH) in the pituitary gland, and both pituitary hormones are needed to produce and release fertile ovules(19). Given that cortisol levels increase in hair sheep in response to HS(7), so two hypotheses could explain the lack of HS effect on their fertility: 1) lower reproductive axis sensitivity to increased cortisol levels, and 2) the increase in cortisol levels.

Moreover, HS apparently alters pre- and post-natal offspring development in sheep. gestational hyperthermia can reduce placental development and growth, promoting a decrease in the transfer of fetal-maternal nutrient(11). Fetal growth can consequently be delayed, leading to weak, low-birth weight lambs with a high possibility of perinatal death(20). 208

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Compared to winter thermoneutral conditions, summer HS during the last third of pregnancy did not affect lamb birth weight, but can reduce prolificacy and litter birth weight in hair sheep(6). Since progestogens and equine chorionic gonadotropin were used to synchronize and thus increase the percentage of twin lambing in this study, the lower prolificacy in summer may be due to fetal reabsorption in response to high temperatures. Clearly, when possible, it is best not to schedule births during the hottest months in warm regions.

Effects on lamb growth

Under Mexico conditions, there is few information available about the HS impact on growth and development of hair breed lambs. The enviromental temperature is a factor that partially controls the feed intake in animals; so, HS in lambs has been associated with lower dry matter intake, higher water intake and a increase in metabolizable energy requeriments to activate thermoregulation mechanisms(1,4). In other words, HS increases maintenance energy requirements in a body scenario in which energy intake via feed is reduced(1,14); under these circumstances growth in lambs slows or stops and nutritional efficiency is reduced. In extreme cases, mainly observed in non-adapted breeds, the energy balance becomes negative, making use of these breeds untenable in hot climates(2).

In a study using Dorper x Pelibuey lambs, HS was found to reduce growth rate by 28% and feed efficiency by 20%(5). Under Mexico conditions, there is few information available about the HS impact on growth and development of hair breed lambs. The environmental temperature is a factor that partially controls the feed intake in animals; so, HS in lambs has been associated with lower dry matter intake, higher water intake and an increase in metabolizable energy requirements to activate thermoregulation mechanisms(21,22). This negative effect on productive performance in fattening lambs was associated with increased energy expenditure in the thermoregulation process; indeed, hyperthermia in sheep can increase nutritional maintenance requirements by 10 to 20%(23).

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Thermoregulation in hair sheep

Activation of compensatory and adaptive mechanisms allow hair sheep to efficiently tolerate temperatures above the upper limit of their thermoneutral zone without drastically compromising their productivity. The thermoneutral zone for sheep is generally between 12 and 27 ºC(1,4), although in hair breeds the upper limit is considered to be 30 ºC(24), highlighting their natural tolerance for higher temperatures.

The type of HS to which sheep are exposed is generally evaluated based on the temperaturehumidity index (THI). Sheep in general can begin to experience HS at THI>72 (25), although one report for specific heat-tolerant breeds indicates it to begin at 82 units, with three HS levels: moderate (82 to <84), severe (≥84 to <86) and very severe (≥86)(4). This information needs to be taken with caution since other sources indicate that hair sheep begin to show signs of HS at THI values between 78 and 79 units(24). Since hair sheep tolerate higher temperatures than wool sheep, it is much more probable that HS in any sheep breed begins below 79 units and not at 82 units. More research is needed on the precise inflection point when sheep begin to manifest HS symptoms, as has been established in other domestic livestock species.

Hair sheep’s greater tolerance to HS conditions is the result of genetic and phenotypic adaptations, as well as the activation of physiological, metabolic and endocrinological mechanisms. These aid in maintaining an adequate body water balance and normothermic conditions (38.3 to 39.9 ºC) at a low energy cost(5,13). Several of the mechanisms activated by hair sheep in response to HS conditions are also activated by wool sheep but the latter still exhibit greater increases in body temperature as ambient temperature rises(26).

Genetic adaptations

Hair sheep breeds are genetically predisposed to be more tolerant of high ambient temperatures than most wool breeds(8). For example, Blackbelly sheep were found to have lower rectal temperature (RT) and respiratory rate (RR) than Dorset wool sheep under HS conditions(20). Pelibuey sheep were also reported to have greater thermoregulatory capacity 210

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than Suffolk sheep under acute HS (37 Âą 2.5 Â°C for 6 h/d)(18). This genetic variability is associated with the portability of thermo-tolerance genes, which have received little attention in hair sheep. One study found that hair sheep are more tolerant to HS because they activate thermo-tolerance genes associated with expression of heat shock proteins (HSP)(26). Under HS conditions, HSP confer protection to cells to prevent apoptosis, and are therefore partially responsible for the adaptation of hair sheep to HS(27).

In addition to having lower RT and RR than Suffolk sheep, Pelibuey sheep also had a higher concentration of HSP70 (2.86 vs 0.53 ng / mL) when exposed to HS in a climatic chamber(26). The reduced HSP70 expression in Suffolk sheep was associated with a decrease in the viability of in vitro-cultured blood mononuclear cells and consequently a lower adaptation to hot climates. The HSP70 genetic marker is the most widely expressed in sheep and goat breeds adapted to HS environmental conditions(26,27,28). In hair sheep, only genes linked to synthesis of HSP70 have been detected, but several genes have been identified that are associated with thermo-tolerance in HS-adapted small ruminants. Hair sheep may also be carriers of some of these genes, although further research is needed to confirm this possibility.

In native desert sheep, thermo-tolerance genes have been identified that are associated with skin color and pigmentation (FGF2, GNA13, PLCB1), energy and digestive metabolism (MYH, TRHDE, ALDH1A3 and GPR50), and immune response(9,28,29). Some mutations in the G1270A and C888T polymorphisms linked to the GPR50 gene, associated with better thermal tolerance, were recently found in HS-adapted sheep breeds in India(29). In another study, expression of genes linked to prolactin were found to affect maintenance of extracellular fluid volume, water intake, sweat gland regulation and seasonal growth of hair in sheep(30). This could explain why HS-adapted sheep breeds, including hair sheep, are able to efficiently use metabolizable energy and water, and maintain homeothermal conditions at a minimum energy cost in high temperature scenarios.

Based on the presence of thermo-tolerance genes in HS-adapted sheep, assisted genetic selection based on genetic markers could be an effective tool for identifying sheep with an outstanding capacity for heat tolerance and HS adaptation. Studies are already under way in some Mediterranean countries for selection of small ruminants by genetic markers linked to thermo-tolerance(31). Selection of thermo-tolerant hair sheep individuals can also be done effectively using biological markers such as physiological, endocrinological and biochemical thermoregulation mechanisms as well as phenotypic adaptations. Much more data is currently available on these aspects than on genetic markers associated with thermotolerance. 211

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Phenotype adaptations

Hair sheepâ&#x20AC;&#x2122;s phenotypic characteristics also provide them adaptability to HS(9). The fact that they have hair instead of wool is an advantage in terms of heat loss, both by non-evaporative and evaporative means(7,13). Being relatively thin and short, the hair facilitates air flow across the skin allowing transfer of heat accumulated on the body surface to the environment by radiation or convection(7), or, more efficiently, by evaporation of sweat(8). Wool, in contrast, is a very effective insulator that prevents air flow over the skin and maintains heat in the body. Consequently, non-evaporative body heat dissipation mechanisms and sweating are ineffective in regulating body temperature in wool breeds(32,33). In addition, the number of sweat glands and the area they occupy are greater in hair breeds than in wool breeds, meaning sweating is a more effective body heat dissipation mechanism in hair breeds(8). Skin thickness is another phenotypic factor that causes inter-breed differences in thermoregulatory capacity; hair sheep have thinner skin than wool sheep, which favors dissipation (radiation and sweating) of core body heat through the skin(33).

Skin color is known to affect the ability of shorn sheep to transfer excess body heat to the environment or vice versa(8,33). Light colored hair and skin in hair sheep is beneficial for animal comfort because it allows them to have a lower heart rate, RT and RR compared to dark-colored hair sheep(34). This occurs because light colors reflect solar radiation while dark colors absorb it; therefore, the darker the hair and skin color the greater the body heat accumulation in dark-haired animals(8,32,34). In terms of thermoregulation, hair sheep breeds benefit from having hair rather the wool, but even hair and skin color can improve their adaptation to hot climates.

Physiological mechanisms

Sheep require very little energy to maintain normothermia within the thermoneutral zone(35). However, temperatures above the upper limit of the thermoneutral zone can compromise this homeostatic balance(3). Under these conditions, the first response of sheep includes physiological adjustments to dissipate excess body heat load(35). If this is insufficient, endocrinological and metabolic thermoregulation mechanisms can also be activated.

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Therefore, higher RR and water intake, but lower feed intake, is commonly observed in heatstressed hair sheep.

Increased RR is the main mechanism implemented to avoid hyperthermia in sheep under HS(32,33); indeed, regardless of breed, sheep under HS dissipate at least 60% of body heat load via the respiratory tract(4). Under high temperatures RT in sheep increases in parallel with RR(3,13). These physiological responses to HS (i.e. increased RT, RR and other physiological constants) occur naturally in all sheep breeds(12,13,20,26), but increases in the average values of these physiological variables are lower in hair sheep than in wool sheep(20,26,33). This suggests that hair sheep breeds may implement other physiological adjustments, or adjustments of another nature (e.g. reduction of motor activity or metabolic activity), in conjunction with increased RR(20,32,35).

The lower RR observed in hair sheep may be related to continuous loss of body heat through the skin in HS environments(32,33). So, under HS, the need for heat dissipation produces vasodilation and redistribution of blood flow towards the peripheral tissues to increase skin sensitivity and promote heat loss via radiation, convection and sweating(4,36). Water evaporation through cutaneous sweating is low (~10%) in hair sheep, meaning that heat loss through the respiratory tract (60 to 90%) is the most important under hot conditions(36,37). Therefore in hair sheep increased RR and heat losses through the skin work synergistically to make thermoregulation more efficient(13).

In dry and arid climates, the circadian patterns for RT, RR and hair coat temperature from different body regions of hair sheep change in response to environmental temperature during spring (thermoneutral), but under summer HS, hair coat temperatures fluctuate with environmental temperature while RR changes as heat losses through the skin are insufficient(13). This circadian rhythm of RR under natural conditions of high temperature is probably a physiological adaptive mechanism developed by hair sheep to maintain homothermia without compromising organism hydration. A recent study done during the summer in the arid northwest of Mexico reported that hair sheep developed adaptive heterothermia during the hottest month (August)(38); a mechanism used by desert-adapted homeotherm animals (39). The adaptive heterothermia mechanism allows animals to tolerate a greater body heat load during daylight hours and then dissipate heat when solar radiation is minimal or non-existent, mainly through a drastic increase in RR(35,39). This adaptation prevents dehydration in desert homeothermic animals during the hottest seasons of the year(39).

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In response to higher RR and sweating, increased water intake also functions as a cooling mechanism and a way of compensating for the water deficit created by increases in water vapor loss through the respiratory tract(4,6,40) and sweating(8,36). A marked reduction in feed intake and digestion also occurs as a thermoregulation mechanism(4,6,7,40). This reduction in feed intake may be regulated at the endocrine level and be intended to reduce endogenous production of metabolic heat(4).

Endocrinological mechanisms

The physiological and behavioral responses triggered in heat-stressed animals are regulated at the neuro-endocrine level(17,41). Under HS conditions it is common to observe a reduction in blood levels of the thyroid hormones T3 (triiodothyronine) and T4 (thyroxine), both responsible for mediating animal metabolism, as a mechanism to decrease production of metabolic heat(39). Hair sheep are no exception: a study in which a climatic chamber was used to induce HS in pregnant Blackbelly and Dorset ewes, found that T3 and T4 concentrations decreased in both breeds at 33.8 Â°C, although these changes were minor(20). This suggests that hair sheep are able to effectively maintain their metabolism in balance when under thermal insult.

The effect of HS on thyroid hormone levels in hair sheep may be due to increased hypothalamic synthesis of the tyrosine inhibitor factor (TIF)(1). The HS stimulates peripheral thermal receptors which in turn suppress the hypothalamusâ&#x20AC;&#x2122;s appetite center, causing greater TIF synthesis and release. This in turn reduces release of thyroid stimulating hormone (TSH), negatively affecting hormonal production in the thyroid gland(3,41). Release of T4 is more sensitive to HS than release of T3(42), suggesting that T4 is more closely associated with reductions in feed intake and, thus, with endogenous reductions in metabolic heat.

Cortisol is another hormone vital to the process of adaptation to stressors(17,41). This glucocorticoid is a mediator of hepatic gluconeogenesis; an important function since availability of glucose in the organism is essential during a state of alarm or stress because it functions as an energy source with rapid cellular availability(41,42,43). Elevated serum cortisol has been found in response to HS in hair sheep breeds, as well as in other breeds not found in Mexico but adapted to HS (e.g. Malpura in India)(40,42). This is a response to the bodyâ&#x20AC;&#x2122;s need for energy to cope with the extra expenditure involved in activating evaporative type thermoregulation mechanisms. Higher cortisol levels are therefore linked to higher blood 214

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glucose levels from activation of hepatic cell metabolism(3), as well as to increased release of cholesterol, a blood metabolite that is converted to cortisol by enzymatic action in the adrenal gland(17,41).

Insulin is a metabolic hormone important in energy metabolism regulation under HS conditions in sheep(44). Levels of insulin increase in response to HS, producing hyperinsulinemia, which may be a strategy to protect correct pancreatic functioning and promote higher heat-shock protein (HSP) production(45). Thus, while HS reduces feed intake, hyperinsulinemia prevents lipolysis and increased concentrations of non-esterified fatty acids, excesses of which can cause apoptosis of pancreatic Î˛ cells(46). Heat stress-induced hyperinsulinemia also helps to maintain live weight, body condition and at least minimal weight gain, since even when feed intake is reduced, insulin prevents the use of body reserves(47). A study done using the heat-adapted Afshari sheep breed found reductions in body maintenance requirements under severe HS conditions since the sheep continued to gain weight even after a 17.5% reduction in feed intake(44). This positive effect of HS in adapted breeds may be related to alterations in post-absorptive metabolism generated by elevation of blood insulin concentrations(44,45). Notably, HS effects on insulin secretion in hair sheep has not been studied, but some studies suggest a similar metabolic adjustment may occur(5,12,15,38). This would partially explain why sheep breeds continue to grow under HS.

Epinephrine and norepinephrine act as hormones or neurotransmitters in thermoregulation in sheep, but no research has been done on their activity in heat-stressed hair sheep. In animals undergoing HS it is known that epinephrine and norepinephrine activate cardiovascular function to ensure sufficient blood supply to vital organs (43,48). Epinephrine is also related to hepatic gluconeogenesis and lipolysis, metabolic processes necessary for supplying energy to thermoregulation systems(49).

Biochemical mechanisms

In hair sheep, activation of physiological adjustments intended to maintain normothermia in hot climates is closely linked to changes in blood analyte levels, or perhaps, changes in some blood analytes may be directly caused by HS either as a reflection of the ability to adapt or the lack thereof(50). One study reported that serum concentrations of glucose, cholesterol and triglycerides in Dorper x Pelibuey lambs declined due to chronic HS during the summer in a desert region of northwestern Mexico(13). In this study RR increased by more than 100% 215

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compared to values observed in spring (thermoneutral period), suggesting that the decrease in metabolites responded to the high energy expenditure of the respiratory tract muscles during the increased RR. In addition, serum urea levels increased and potassium levels decreased without affecting sodium concentrations, indicating no net loss of body water content via urine, feces and sweat. This suggests that hair sheep have adaptive metabolic mechanisms that reduce the probability of becoming dehydrated. In another study done in the same desert region of Mexico(38), hair sheep were found to activate a post-absorptive energy metabolism under chronic and intense HS conditions, whereas under acute HS, glucose was the main source supplying the energy expenditure implied with increased RR. High blood glucose levels in response to acute HS can be explained by increased cortisol levels, a hormone that stimulates gluconeogenesis to provide glucose as energy for cells(44).

The HS effects on blood analyte concentrations vary widely across different studies, making it difficult to explain the metabolic adjustments made by hair sheep to survive and adapt to hot climates. Factors such as breed, age, HS type, nutrition, physiological status and others must therefore be considered when interpreting results. For example, in a recent study using heat-stressed Dorper x Pelibuey lambs, lack of shade in pens was found to promote an increase in metabolite concentrations related to energy and lipid metabolism, but not in protein metabolism(50). In the same study, increases in blood sodium and chlorine electrolytes were observed and were attributed to higher water intake. Another study using Dorper x Pelibuey ewes under natural HS conditions found that animal age and lactation status altered blood glucose, cholesterol and urea concentrations, but not blood concentrations of triglycerides, total protein and electrolytes(51). Additionally, weaned lambs and lactating ewes had lower glucose and cholesterol concentrations compared to nulliparous and non-lactating multiparous ewes. In the lambs this response was attributed to higher RR in lambs, whereas in the lactating ewes it was attributed to the effect of nutrient redistribution for synthesis of milk lactose and fat. Using sheep of a genotype similar to those used in these studies, it was reported that the uterine environment during the last third of gestation had no effects on variations in blood metabolite and electrolyte concentrations in heat-stressed lambs during the fattening period(52). Nutritional restriction has also been shown to have little effect on blood metabolite concentrations linked to energy metabolism in late pregnancy sheep in a hot climate(11).

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Conclusions and implications

Hair sheep breeds are characterized for being rustic and easily adaptable to different production conditions, including those in which the climate is most frequently extreme heat and forage quality is poor. Apparently, hair breeds have the ability to grow and reproduce under heat stress conditions because they have thermo-tolerance genes, and phenotypical advantages in terms of their skin and hair which allows them to dissipate body heat through evaporative or non-evaporative routes more efficiently than wool breeds. Circadian respiratory rate patterns, as well as skin characteristics and metabolic adjustments, allow hair sheep to effectively reduce body heat load, perhaps at a lower energy cost than in wool breeds. Given the pressing challenges of global warming and climate change, selection of heat-tolerant and nutrient-efficient breeds will become increasingly necessary to guarantee animal protein production.

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27. Singh KM, Singh S, Ganguly I, Nachiappan RK, Ganguly A, Venkataramanan R, et al. Association of heat stress protein 90 and 70 gene polymorphism with adaptability traits in Indian sheep (Ovis aries). Cell Stress Chaperon 2017;22(5):675-684. 28. Rout PK, Kaushik R, Ramachandran N. Differential expression pattern of heat shock protein 70 gene in tissues and heat stress phenotypes in goats during peak heat stress period. Cell Stress Chaperon 2016;21(4):645-651. 29. Saxena VK, Kumar D, Naqvi SMK. Molecular characterization of GPR50 gene and study of its comparative genetic variability in sheep breeds adapted to different thermocontrasting climatic regimens. Int J Biometeorol 2017;61(4):701-707. 30. Alamer M. The role of prolactin in thermoregulation and water balance during heat stress in domestic ruminants. Asian J Anim Vet Adv 2011;6(12):1153-1169. 31. Menéndez-Buxadera A, Molina A, Arrebola F, Clemente I, Serradilla JM. Genetic variation of adaptation to heat stress in two Spanish dairy goat breeds. J Anim Breed Genet 2012;129(4):306-315. 32. McManus C, Paludo GR, Louvandini H, Gugel R, Sasaki LCB, Paiva SR. Heat tolerance in Brazilian sheep: Physiological and blood parameters. Trop Anim Health Pro 2009;41(1):95-101. 33. Titto CG, Veríssimo CJ, Pereira AMF, Geraldo A de M, Katiki LM, Titto EAL. Thermoregulatory response in hair sheep and shorn wool sheep. Small Ruminant Res 2016;144:341-345. 34. Fadare AO, Peters SO, Yakubu A, et al. Physiological and haematological indices suggest superior heat tolerance of white-coloured West African Dwarf sheep in the hot humid tropics. Trop Anim Health Pro 2012;45(1):157-165. 35. Moberg GP. Biological response to stress: implications for animal welfare. In: Moberg, GP, Mench JA, editors. The biology of animal stress: Basic principles and implications for animal welfare. Wallingford: CABI; 2000:1-21. 36. da Silva WE, Leite JHGM, de Sousa JER, et al. Daily rhythmicity of the thermoregulatory responses of locally adapted Brazilian sheep in a semiarid environment. Int J Biometeorol 2017;61(7):1221-1231. 37. Fonseca VCF, Saraiva EP, Maia ASC, Nascimiento CCN, da Silva JA, Pereira WE, et al. Models to predict both sensible and latent heat transfer in the respiratory tract of Morada Nova sheep semiarid tropical environment. Int J Biometeorol 2017(5);61:777– 784. 220

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38. Macías Cruz U, Gastélum MA, Avendaño-Reyes L, Correa-Calderón A, Mellado M, Chay-Canul A, et al. Variaciones en las respuestas termoregulatorias de ovejas de pelo durante los meses de verano en un clima desértico. Rev Mex Cienc Pecu 2018;9(4):739753. 39. Cain III JW, Krausman PR., Rosenstock SR, Turner JC. Mechanisms of thermoregulation and water balance in desert ungulates. Wildlife Soc B 2006;34(3):570581. 40. Sejian V, Maurya VP, Naqvi SMK. Adaptability and growth of Malpura ewes subjected to thermal and nutritional stress. Trop Anim Health Prod 2010;42(8):1763-1770. 41. Matteri RL, Carroll JA, Dyer CJ. Neuroendocrine responses to stress. In: Moberg GP, Mench JA, editors. The biology of animal stress: Basic principles and implications for animal welfare. Wallingford: CABI; 2000:43-76. 42. Sejian V, Maurya VP, Kumar K, Naqvi SMK. Effect of multiple stresses on growth and adaptive capability of Malpura ewes under semi-arid tropical environment. Trop Anim Health Pro 2013;45(1):107-116. 43. Tsigos C, Chrousos GP. Hypothalamic–pituitary–adrenal axis, neuroendocrine factors and stress. J Psychosom Res 2002;53(4):865-871. 44. Mahjoubi E, Amanlou H, Mirzaei-Alamouti HR, et al. The effect of cyclical and mild heat stress on productivity and metabolism in Afshari lambs. J Anim Sci 2014;92(3):1007-1014. 45. Baumgard LH, Rhoads RP. Effects of heat stress on postabsorptive metabolism and energetics. Annu Rev Anim Biosci 2013;1(1):311-337. 46. Nelson EAS, Wong Y, Yu LM, Fok TF, Li K. Effects of hyperthermia and muramyl dipeptide on IL-1β, IL-6, and mortality in a neonatal rat model. Pediatr Res 2002;52(6):886-891. 47. Morigny P, Houssier M, Mouisel E, Langin D. Adipocyte lipolysis and insulin resistance. Biochimie 2016;125:259-266. 48. Afsal, A, Sejian, V, Bagath, M, Krishnan, G, Devaraj, C BR. Heat stress and livestock adaptation: Neuro-endocrine regulation. Int J Vet Anim Med 2018;1(2):1-8. 49. Binsiya TK, Sejian V, Bagath M, Krishnan G, Hyder I, Manimaran A, et al. Significance of hypothalamic-pituitary-adrenal axis to adapt to climate change in livestock. Int Res J Agric Food Sci 2017;2(1):1-20. 221

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50. Vicente-Pérez A, Avendaño-Reyes L, Barajas-Cruz R, Macías-Cruz U, Correa-Calderón A, Corrales-Navarro JL, et al. Parámetros bioquímicos y hematológicos en ovinos de pelo con y sin sombra bajo condiciones desérticas. Ecosist Rec Agropec 2018;5(14):259. 51. Macías-Cruz U, Correa-Calderón A, Mellado M, Meza-Herrera CA, Aréchiga CF, Avendaño-Reyes L. Thermoregulatory response to outdoor heat stress of hair sheep females at different physiological state. Int J Biometeorol 2018;62(12):2151-2160. 52. Macías-Cruz U, Stevens JC, Correa-Calderón A, Mellado M, Meza-Herrera CA, Avendaño-Reyes L. Effects of pre-lambing maternal energy supplementation on postweaning productive performance and thermoregulatory capacity of heat-stressed male lambs. J Therm Biol 2018;75:7-12.

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https://doi.org/10.22319/rmcp.v11i1.4951 Review

Azospirillum spp. in grasses and forages. Review

Camila Fernandes Domingues Duarte a* Ulysses Cecato a Thiago Trento Biserra a Divaney Mamédio a Sandra Galbeiro b

Universidade Estadual de Maringá, Programa de Pós-Graduação em Zootecnia, Departamento de Zootecnia, Av. Colombo, 5790 - Zona 7, Maringá, Paraná, Brasil. b

Universidade Estadual de Londrina, Centro de Ciências Agrárias, Londrina, Paraná, Brasil.

Corresponding author: camilafernandesd@hotmail.com

Abstract: The Azospirillum genus includes plant growth-promoting bacteria found in different soil regions worldwide. When associated with plant roots these bacteria help augment productivity by increasing both the aerial and root portions. These benefits derive from excretion of growth phytonutrients, especially auxins. Use of Azospirillum spp. can help to bridge the gap between productivity and sustainability since inoculants based on this microorganism can reduce use of nitrogen fertilizers without affecting productivity, and generate savings and greater profitability. Inoculation of Azospirillum spp. strains with forage grasses can result in greater forage mass gains and less need for nitrogen fertilizer, improving pasture production system sustainability. Co-inoculation with other strains such as Bradyrhizobium sp. apparently potentiates growth promotion. Proper application methods must be followed for these growth-promoting bacteria to be effective. Growth promotion in response to Azospirillum has been described in grasses such as sugarcane, maize and forages, but further research is needed under different conditions to support adoption by producers. Application of bacterial inoculates can increase competitiveness vis-à-vis conventional agriculture methods. Inoculation of grasses in livestock systems

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can raise forage mass production, mitigate degradation risks and improve productive indices. Key words: Bacteria, Agricultural microbiology, Rhizobacteria, Azospirillum.

Received: 16/06/2018 Accepted: 30/01/2019

Introduction

Perhaps the greatest challenge intrinsic to agriculture is balancing productivity with sustainability. Apparently at cross-purposes both goals have become pressing concerns due to population growth, climate change, and consumer behavior. New technologies and techniques are needed to shift the paradigm away from traditional techniques for increasing production of grains, meat, milk, etc. through greater use of chemical fertilizers and the opening of new areas.

Nitrogen (N) can increase productivity in plants and is an essential fertilizer in commercial agriculture, especially in tropical regions. However, fertilization with N raises production costs by approximately 40 %(1), and can pollute soils and water, with serious environmental consequences. Sustainable alternatives for plant nutrition are becoming increasingly important. For example, research into the potential of biological fixation of atmospheric nitrogen (BFN) is revealing it be essential for greater grassland productivity. This process is performed by diazotrophic bacteria, commonly known as plant growth-promoting bacteria (PGPB). It involves conversion of atmospheric nitrogen (N2) into other nitrogen substances which are then incorporated by plants through synthesis of protein and nucleic acids(2).

However, the benefits provided by PGPB extend beyond BFN(3). These bacteria also stimulate production of growth hormones such as auxins, cytokinins and gibberellins, and improve absorption of other nutrients such as phosphorus. Inoculation with PGPB is a promising technology for augmenting agricultural production while reducing the environmental impacts of inadequate use of fertilizers.

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Prominent among growth-promoting bacteria are those in the genus Azospirillum, the most studied of the PGPB(4). This genus gained worldwide relevance in the 1970s in response to research showing it increased absorption of water and nutrients, resulting in greater drought tolerance and productivity. These responses derive from higher production of growth-promoting substances which alter root system morphology by increasing the number and diameter of secondary, lateral and adventitious roots(5).

Inoculation of Azospirillum in corn (Zea mays) resulted in a 17 % increase in average ear length and productivity versus a control(5). Use of Azospirillum can also reduce the need for N fertilization(6), producing savings of 30 to 50 kg ha-1 N in corn at the beginning and end of the rainy season(7). Considering this possibility, substitution of 50 % of the N fertilizer used in Brazil would result in reductions of 52 kg ha-1 N in corn and 35 kg ha-1 N in wheat, and a consequent savings of approximately $1.2 billion a year(8). Sugarcane also requires heavy N fertilization, but interacts positively with PGPB(9). Inoculation with Azospirillum brasilense produced a 10% increase in productivity compared to a treatment receiving no N fertilizer, which is equivalent to the use of 120 kg ha-1 N(10).

The benefits observed with Azospirillum inoculation in corn, a forage grass, can also be expected in tropical forage grasses, possibly reversing or minimizing soil degradation risks while improving forage mass production. This is supported by a report of N2-fixing bacteria in the rhizosphere of forage grasses(9), suggesting a future of lower N fertilizer use in tropical forage grasses(9). Indeed, inoculation of the grass Brachiaria spp. with A. brasilense strains raised average forage mass production by 13 %(1).

Azospirillum Genus

The Azospirillum genus of bacteria was discovered by J. Dobereiner and became important in the 1970s for its ability to fix atmospheric nitrogen, hence the genus name Azospirillum(11). The genus has a broad geographical distribution, and can be found in temperate and tropical regions(1).

Azospirillum-genus bacteria are Gram-negative and free-living. They are cane-shaped, have active movement, measure 0.8 to 2 Îźm in diameter and 2 to 4 Îźm in length, and have intracellular polyhydroxybutyrate granules(12). Optimum development temperature range for these bacteria is 28 to 41 Â°C. These bacteria are strictly aerobic when in a N2-free environment and supplied with nitrogen or microaerophilic sources, which requires them to fix nitrogen(11). However, to promote a microaerophilic environment when in a semi225

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solid medium these bacteria produce a thin veil-like film containing the oxygen concentration essential for nitrogen fixation and growth initiation.

Azospirillum sp. have a flexible carbon and nitrogen metabolism which augments their ability to compete for rhizosphere colonization(12). When present in the rhizosphere they colonize both the mucigel layer around the roots (external colonization) and root intercellular spaces (internal colonization)(8). Colonization occurs mainly in the areas of elongation and root hairs(11). They are highly competitive when colonizing the rhizosphere, and to maintain metabolism make use of different nitrogen sources such as ammonia, nitrite, nitrate, molecular nitrogen and amino acids, as well as carbon sources such as organic acids (malate, pyruvate, succinate and fructose)(10).

Fifteen Azospirillum species have been identified to date: A. lipoferum, A. brasilense, A. amazonense, A. halopraeferens, A. irakense, A. largimobile, A. doebereinereae, A. oryzae, A. melinis, A. canadiana, A. zeae, A. rugosum, A. palatum, A. picis and A. thiophilum. Of these the most widely researched are A. lipoferum and A. brasilense, both of which are common in tropical grasses and forages(1). Not all Azospirillum species can be found colonizing plants in various regions; A. amazonense, for instance, has only been isolated in Brazil(12). Azospirillum brasilense, however, is widely distributed in tropical and subtropical soils, a characteristic that contributed to its ample study(13). Experiments have shown that A. brasilense promotes plant growth and consequently increases productivity(14). It exhibits satisfactory results when associated with Poaceae family plants such as corn, oats, wheat and rice(15).

Inoculum for plants

Widely known as biofertilizer, inoculants intended to promote plant growth contain live microorganisms that implement various mechanisms. Commercial production of biofertilizers in Latin America began in 1898(16), and Brazil is one of the largest current markets in the region(17). Inoculants can improve competitiveness in the agricultural sector and is a promising and sustainable technology capable of partially replacing nitrogen fertilization(18). Brazilâ&#x20AC;&#x2122;s Ministry of Agriculture, Livestock and Supply (MinistĂŠrio da Agricultura, PecuĂĄria e Abastecimento da Brasil - MAPAB)(19), requires that commercial inoculants contain at least 109 cells per gram or milliliter of product at their expiry date, that they must be prepared with a sterile vehicle and be free of unspecified microorganisms up to the 1x10-5 dilution factor. Traits decisive for inoculant efficacy in promoting plant growth 226

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include the strain, its competitiveness, and the number of necessary or viable cells for rapid colonization of the rhizosphere and plant tissue(20). They need to be produced using non-toxic vehicles, and be water-soluble and associated with competitive lines(21).

Inoculation success depends on selection of efficient, stress-resistant strains, since diazotrophic bacteria are found in various soil types and their persistence is determined by soil salinity, pH and moisture(22). Azospirillum genus bacteria promote plant growth through mechanisms such as greater tolerance to environmental stressors, phytohormone production and nitrogen fixation(23).

A major initiative to develop Azospirillum inoculates in Brazil began in 1996 when the Department of Biochemistry and Molecular Biology of the Federal University of Paranรก partnered with the Brazilian Agricultural Research Company (Empresa Brasileira de Pesquisa Agropecuรกria - Embrapa Soja) to do field research on Azospirillum efficiency. Years of research produced Azospirillum lines that survived longer in soils and produced more plant growth(16). A total of eighteen trials were run which were divided into two sets of nine trials each. The first set evaluated peat inoculants containing a single A. brasilense or A. lipoferum strain in corn using five trials with three harvests and in wheat using four trials with two harvests. The second set evaluated a mixture of two A. brasilense strains (Ab-V5 and Ab-V6) in peat or liquid inoculants in four corn trials and four wheat trials. This research contributed to the release of four A. brasilense strains (Ab-V4, Ab-V5, AbV6 and Ab-V7) for commercial inoculant production. Only Ab-V5 and Ab-V6 are widely used as inoculants because they provide the most satisfactory results in corn and wheat(16). Due to their ease of application liquid inoculants were chosen over peat inoculants for marketing. In 2010, a liquid inoculant containing Azospirillum strains and protective molecules for tropical conditions was developed in an association between Embrapa and the private sector.

Azospirillum strains are sold worldwide in countries including Argentina, Mexico, Italy, France, Australia, Pakistan, Germany, the United States, Africa, Belgium, India and Uruguay(24). The success of Azospirillum inoculants is the result of their beneficial effects in agricultural crops; for instance, they have a 60 to 70 % success rate and provide 5 to 30 % productivity gains in various cereal crops(25).

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Action mode of Azospirillum bacteria

Azospirillum spp. bacteria supply nitrogen to plants via different mechanisms (Table 1). Table 1: Action modes of Azospirillum bacteria Action modes Source (Authors) Plant growth regulator production (auxins, cytokinins and gibberellins) Assimilatory reduction of nitrate Biological fixation of N2 Resistence to hydric stress Growth of root system Greater water and nutrient absorption Biological control

Lambrecht et al.(27) Fages(23) Fernandes JĂşnior(24) Cohen et al.(34) Okon and Labandera-Gonzalez(25) Okon and Labandera-Gonzalez(25) Unno et al.(26)

Production of growth regulators is one of the main mechanisms by which these bacteria affect plant growth since they influence growth in plants, modify root morphology and maximize use of soil resources, which in turn augment BFN and reduction of the assimilable nitrate available in soils(24).

Azospirillum bacteria also reduce nitrate (NO3-) in the roots, promoting plant growth due to consequent lower energy expenditure required from the plant to reduce nitrate to ammonia; this energy is allocated to other vital processes. These bacteria can influence glutamine synthetase activity in the roots of corn plants(23). Glutamine synthetase is extremely important in the nitrogen incorporation process and essential for plants to express their full productive potential(26). Other indirect mechanisms through which Azospirillum bacteria can promote plant growth is by reducing the appearance of fungi or soil pathogens via production of siderophores, chitinases, glucanases and antibiosis.

Growth of the plant root system, which can occur in response to growth-promoting substances(25), can result in greater mineral and water absorption. Auxin, specifically indole-3-acetic acid (IAA), is the principal hormone promoting root growth(15). Azospirillum lineages produce IAA in addition to other indole compounds such as cytokinins and gibberillins(8). At least three biosynthetic pathways exist for IAA production in Azospirillum, two of which (indole-3-acetamide and indole-3-pyruvate) depend on tryptophan(27). Indole-3-acetic acid is the main indole secreted by Azospirillum(24), although indole-3-butyric acid (IBA) has also been reported(23). This indole is an important reserve source in the Azospirillum genus(28). 228

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Production of IAA by Azospirillum very probably affects root growth. For example, inoculation of tomato and red pepper seeds with A. brasilense, which is known to produce IAA, increased average root length from 7.21 (control) to 9.68 cm in tomatoes and from 6.20 (control) to 6.76 cm in red pepper(29). The aerial portion of the plants in this study also grew more in the treatments than in the controls, highlighting the growth promoting ability of A. brasilense. Phytohormone synthesis in A. brasilense can differ between strains. In one study the 42 M line produced higher IAA levels than the sp7, Cd, Az39, 40 and 42 strains(6).

In Azospirillum strains IAA may be a signal needed to maintain a symbiotic plantAzospirillum interaction(30), since this signaling function is shaped by coevolutionary processes between bacteria and their host plant(31). This phytohormone also affects photosynthesis, and biosynthesis of some metabolites and other phytohormones such as cytokinins and gibberellins(32). In plants cytokinins regulate cell division and new tissue formation both in the aerial part and roots(33). Gibberellins regulate plant growth, and promote division and elongation of primary roots(30).

Azospirillum strains can secrete abscisic acid (ABA) which forms part of the water stress defense mechanism in plants(34). This phytohormone induces plant responses to water, environmental and saline stress(35). For example, inoculation of A. lipoferum into corn plants resulted in high ABA levels and increased plant tolerance to drought probably related to ABA as well as prolines and polyamines(34). Polyamines (e.g. cadaverine, spermine and spermidine) are organic polymers associated with root growth and stress suppression in plants(33). In a study of rice seedlings inoculated with A. brasilense cadaverine production was associated with increased root growth and reduced osmotic stress(36). Corn plants inoculated with A. brasilense also are reported to exhibit greater drought resistance and higher biomass production(37), possibly due to the presence of cadaverine, among other phytohormones.

Growth-promoting bacteria such as Azospirillum can also act as biological control agents(35), which can occur through mechanisms such as parasitism, production of antibiotics, toxins and/or enzymes, interference in the plant-host recognition process and resistance induction(33). Facultative bacteria such as those in the genera Pseudomonas, Burkholderia, Azospirillum and Bacillus, produce and secrete secondary substances that can act as antibiotics, fungicides, antivirals and immunosuppressive agents(31). In plants endophytic bacteria of this type provide the best biological control of pathogens via natural colonization of the rhizosphere and invasion of internal tissues, both of which are essential means for successful treatment of diseases affecting subterranean plant tissues. The Azospirillum genus is not strictly considered to exercise biocontrol but Azospirillum strains do produce chemical compounds that modify plant metabolism and defense 229

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activity. For instance, A. brasilense has been shown to effectively control Agrobacterium tumefaciens and phytopathogenic fungi(25). Although the inhibition mode was not well defined, phenylacetic acid, from the auxin group, was identified and found to have antimicrobial activity. Phenylacetic acid is used in the defense mechanism and bacterial competition in the host(25). Biological defense in plants follows two metabolic pathways involving jasmonic acid and salicylic acid(17), while bacteria-induced systemic resistance is activated by the jasmonic acid and ethylene signaling pathway(15).

Co-inoculation with rhizobia

Co-inoculation with bacteria that may or may not be symbiotic is common in legume crops(38). Different microorganisms are used that produce a synergistic effect that surpasses production results obtained when strains are used separately(39). In vitro assays indicate that some bacteria mixtures provide a synergistic interaction that can improve nutrient supply, remove inhibiting products and/or stimulate physical or biochemical mechanisms(35). For example, when associated with rhizobia in legumes A. brasilense produces a beneficial effect caused by production of phytohormones that promote root system development, thus allowing more effective exploitation of available soil volume(38).

In future co-inoculation between Azospirillum and other microorganisms may become a major research focus(35). Co-inoculation produces higher success rates in plants since it results in increased productivity due to balanced nutrition and improved absorption of nitrogen, phosphorus and other minerals(5). It also stimulates root nodule function and increases nodule numbers and weight. Co-inoculation of Bradyrhizobium japonicum and A. brasilense in soybeans provided better yields, even under water and nutrient deficit conditions(39). In a study of B. japonicum/A. brasilense co-inoculation with and without water deficit, co-inoculation increased nodule weight under water deficit conditions and produced better yields and a greater dry matter accumulation under both conditions(40). Studies of root growth and nodulation in soybean co-inoculated with B. japonicum/A. brasilense found that addition of A. brasilense helped to stimulate root growth and improved nodule onset and development through excretion of metabolic products, especially IAA(36). The co-inoculated plants also exhibited a greater number of nodules and a higher percentage of nodulated plants.

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Azospirillum in forage grasses

Grassland degradation is a major problem in livestock systems. For example, an estimated 80 % of grasslands in Brazil exhibit some level of degradation(41). Of the factors that can lead to grassland degradation low nutrient supply for plants is the principal cause since it results in low grass quality and productivity(42). Among soil nutrients, N is the main limiting factor for grass growth and development in the tropics(43). Mineral fertilization is widely used to ensure proper grass growth, but this is expensive and environmentally damaging since around 50 % of applied N is lost due to volatilization or leaching(14).

This situation highlights the potential benefits of BFN in tropical grasses as a means to restoring forage productivity and quality. Diazotrophic bacteria (a.k.a. PGPB) are the main force behind BFN. The process itself involves conversion of N2 into other nitrogenous substances which are then assimilated by plants through synthesis of protein and nucleic acids(1). The nitrogen cycle in grassland ecosystems strongly depends on BFN and diazotrophic bacteria to supply N to plants. Inoculation of PGPB is therefore a promising technique for promoting growth and nutrition in forage plants. It is a viable alternative for totally or partially replacing N-fertilizer and thus contributing to natural resources conservation(44).

The benefits of PGPB in crops such as corn, wheat and rice are clear, but knowledge of the mechanisms involved requires extensive further research. Studies evaluating the effects of PGPB in establishing and maintaining pastures are fundamental to attaining cost-effective and sustainable grassland systems. Using BFN supports sustainability since it can totally or partially replace nitrogen fertilizers, which are produced from nonrenewable fossil fuels(45). Any lowering of N fertilizer use will also mitigate environmental pollution derived from its production and use, with the added dividend of reducing greenhouse gas emissions(8).

A metanalysis of 22 yr of data on in-field PGPB inoculation concluded that Azospirillum spp. promotes growth in several grass species under different environmental conditions(5). These gains went beyond BFN to include modification of root production and a consequent broadening of absorption area and the volume of exploited soil. Most of the research supporting this conclusion has involved inoculation of Azospirillum in forage grasses.

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Azospirillum brasilense was reported to increase dry matter production and foliar growth in pot-grown millet Setaria italica(46). In a study of forage grasses native to the Pantanal Matogrossense in South America, inoculation with diazotrophic bacteria had noticeable effects at 60 and 90 d of culture(47). Combined inoculation of an A. brasilense/A. lipoferum association in the same study resulted in greater dry matter production in the aerial portion and roots, as well as N accumulation. Higher dry matter production than in a control was also observed with inoculation of A. brasilense in the grasses in a natural pasture(48).

Inoculation is also reported to favor the simultaneous production of dry matter in the aerial portion and roots, and high levels of phosphorus (P) and N accumulation due to more efficient use of these nutrients(14). This higher dry matter accumulation rate may be related to an increase in photosynthetic enzyme activity and N assimilation(8). Similar increases in dry matter production have been observed with inoculation of MarandĂş grass, indicating this technique is a sustainable alternative for increasing forage production(49). Azospirillum inoculation has also increased productivity in other grasses(50), which may be due to excretion of plant hormones that enhance macro- and micronutrient absorption(35).

Use of PGPB is reported to raise nitrogen accumulation and overall yields. In a study using Pennisetum and Panicum species grasses inoculation with A. brasilense increased N content by approximately 40 kg ha-1 year-1 via BFN(25). In another study BFN was found to raise N accumulation 7 to 10 kg ha-1 mo-1 during the summer, which varied by grass genotype; this represents 39% of the N necessary for plant development and productivity(51). Dry matter accumulation rate in the same study was 15 kg ha-1 d-1 in the inoculated treatments, almost four-fold higher than the 4 kg ha-1 d-1 in a control without inoculation and fertilization.

Inoculation of A. brasilense in Brachiaria brizantha Staf cv. Marandu, produced better yield, greater tiller generation and a longer grazing period than uninoculated and unfertilized plants(49). In this same system root dry matter production increased with A. brasilense inoculation(33). Using the same grass cultivar, another study found that A. brasilense inoculation produced 9 % more leaves and 12 % more tillers than a control, although no differences in plant height were observed between inoculation and N fertilization treatments(52).

Application of A. brasilense in forage grass production contributes to increasing dry matter content, N content and plant height, making PGPB inoculation a viable alternative for partial replacement of N fertilizer. It can be a vital element in efforts to combine animal production with environmental conservation, which will become more feasible as soil biotechnology is broadly employed to promote soil conservation and fertility and improve plant nutrition. However, more research is needed on the mechanisms and effects 232

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of PGPB inoculation on dry matter content, N content, plant height, leaf area and crude protein content so recommendations can be made regarding its combination with N fertilizer(1). In addition, there is still no conclusive data indicating whether the effects of inoculation are due to BFN or hormonal action.

Azospirillum in corn

Yield in corn responds to a combination of genetic potential, environmental conditions and soil fertility. However, attaining maximum yields requires application of large amounts of fertilizers, particularly nitrogen. One option for reducing use of N fertilizers with corn is application of Azospirillum spp. strains, since it can reduce their use by 30 to 50 kg ha-1(7).

More specifically, inoculation with A. brasilense increases photosynthesis and dry matter accumulation rates(8). When associated with unimproved and cultured genotypes with low N availability, Azospirillum inoculation leads to greater dry matter production, grain yield and N accumulation in corn(5). It can also increase overall grain production by 9 %(53), and productivity by 30 %(8). Some authors report better results when inoculating Azospirillum in corn seeds, with average increases of 70 % in dry root mass and 43.5 % in aerial dry mass(54).

Inoculation process

Inoculation is a simple procedure in which seeds are mixed with an inoculant. It is preferably done in the shade in the morning to prevent direct sunlight and excessive heat from killing the bacteria. Mixing is done in a rotating drum, cement mixer, seed treatment machine or other machine. It is important to uniformly distribute the inoculant on the seeds and verify that each seed is covered by inoculant before sowing. For this technique to be effective seeds must be of good quality and the proper dose of inoculant/kg seed must be applied. After inoculant application the seeds are dried for about 30 min before sowing, all the while protected from sunlight and heat. For peat mixture inoculants a sugar solution or other adhesive substance (gum arabic, arrowroot flour, cassava flour, wheat flour and/or various types of cells and polymers) is recommended to moisten the seeds. In this case, a 10 % sugar solution (100 g sugar/L water) is prepared, the seeds mixed into 233

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it at a proportion of 250 to 300 ml sugar solution per 50 kg seeds, and finally the peat mixed in at the proportion indicated by the manufacturer(8). In either process, the seeds have a thin layer of inoculant on their surface when it is complete. It is extremely important to verify that all seeds have been covered with inoculant since this will ensure nitrogen fixation and expression of their full genetic potential.

Inoculated seeds should be sown the same day they are inoculated to ensure the highest number of viable microorganisms. If this is not feasible, the seeds can be stored in ventilated sheds by spreading them out on a smooth surface in layers less than 30 cm thick(12). The inoculant contains live microorganisms which are sensitive to hot environments(16), and seeds should therefore be sown a maximum of 24 h postinoculation. If this period is exceeded, the seeds must be re-inoculated to improve efficacy. During sowing, the seed container on sowing machines can become quite hot (35+ Â°C), which can kill the bacteria; should this occur sowing should be stopped and the container cooled. Direct inoculation in the seed container is not recommended because inoculant distribution is not uniform, which reduces inoculation efficiency(16).

Inoculation of small lots of seeds can be done with clean plastic bags, basins or buckets previously sterilized with 70% alcohol, as long as all seeds are covered with a thin layer of inoculant. Other aspects of the process follow the same criteria as when using a rotating drum or concrete mixer, namely that it be done in the shade, that inoculated seeds be allowed to dry for 30 min before sowing, and that doses be calculated following manufacturer instructions to ensure maximum efficiency(12).

For beans planted in small areas direct inoculation in the furrow is an alternative technique. Application can be done with a manual or motorized sprayer directly in the furrow. If using this technique, the inoculant must be mixed with water following manufacturer instructions and the sprayer to be used cannot have residues of agrochemicals such as pesticides or herbicides as these can decrease bacteria viability and lower efficiency. Even though the inoculant consists of soil bacteria, the operator must wear personal protection gear.

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Final considerations

Use of Azospirillum spp. in grasses can span the gap between productivity and sustainability. Inoculants based on these microorganisms can potentially reduce nitrogen fertilizer use without affecting productivity, resulting in savings and greater profitability. Grasses such as sugarcane, corn and forages are known to respond well to Azospirillum sp. inoculation, but further study is needed under different conditions to support its broader adoption among producers. This technique can increase competitiveness for some agricultural products vis-à-vis conventionally-grown crops. Grassland inoculation in livestock production can increase forage mass production, mitigate degradation risks and improve production rates.

Literature cited: 1. Hungria M, Nogueira MA, Araujo RS. Inoculation of Brachiaria spp. with the plant growth-promoting bacterium Azospirillum brasilense: An environment-friendly component in the reclamation of degraded pastures in the tropics. Agr Ecosyst Environ 2016;(221):125-131. 2. Nunes FS, Raimondi AC, Niedwieski AC. Fixação de nitrogênio: estrutura, função e modelagem bioinorgânica das nitrogenases. Químic Nov 2003;26(6):872-879. 3. Dobbelaere S, Vanderleyden J, Okon Y. Plant growth-promoting effects of diazotrophs in the rhizosphere. Plant Scienc 2003;(22):107-149. 4. Döbereiner J, Marriel IE, Nery M. Ecological distribution of Spirillum lipoferum Beijerinck. Can J Microbiol 1976;(22):1464-1473. 5. Okon Y, Vanderleyden J. Root-associated Azospirillum species can stimulate plants, Appl Environ Microbiol 1997;63(7):366-370. 6. Cheng NC, Novakowiski JH, Sandini I, Domingues L. Substituição da adubação nitrogenada de base pela inoculação com Azospirillum brasilense na cultura do milho. In.: Seminário Nacional de Milho Safrinha, 11. Anais... Lucas do Rio Verde: Fundação Rio Verde; 2011:377-382. 7. Fancelli AL. Boas práticas para o uso eficiente de fertilizantes na cultura do milho. Piracicaba: IPNI - International Plant Nutrition Institute Brazil, (IPNI. Informações Agronômicas, 131). 2010. 235

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8. Hungria M, Campo R, Souza E, Pedrosa F. Inoculation with selected strains of Azospirillum brasilense and A. lipoferum improves yields of maize and wheat in Brazil. Plant Soil 2010;(331):413–425. 9. Boddey RM, Xavier D, Alves BJR, Urquiaga S. Brazilian agriculture: the transition to sustainability. J Crop Produc 2003;(9):593-621. 10. Schultz N, Morais RF, Silva JA, et al. Avaliação agronômica de duas variedades de cana-de-açúcar inoculadas com bactérias diazotróficas e adubadas com nitrogênio. Pesq Agropec Bras 2012;(47):261-268. 11. Dobbelaere S, Croonenborghs A, Thys A, Ptacek D, Okon Y, Vanderleyden J. Effect of inoculation with wild type Azospirillum brasilense and A. irakense strains on development and nitrogen uptake of spring wheat and grain maize. Biol Fertil Soil 2002; (36):284–297. 12. Trentini DB. Identificação dos alvos celulares das proteínas de transdução de sinal PII do diazotrófico de vida livre Azospirillum amazonense [tesis maestria]. Brasil, RS: Universidade Federal do Rio Grande do Sul; 2010. 13. Zambrano ER, Jiménez Salgado T, Tapia Hernández A. Estudo de bacterias asociadas a orquídeas (Orchidaceae). Lankesteriana 2007;(71-2):322-325. 14. Reis VM, Baldini JI, Baldini VLD, Dobereiner J. Biological dinitrogen fixation in gramineae and palm Trees. Plant Sci 2000;(19):227-247. 15. Hartmann A, Baldani JI. The genus Azospirillum. In: Dworkin M editor. The Prokaryotes. 1rst ed. New York, New York: Springer; 2006:115-140. 16. Hungria M. Inoculação com Azospirillum brasilense: inovação em rendimento a baixo custo. Embrapa Soja – Documentos 325, 2011. 17. Silva MF, Reis VM. Produção, caracterização e aplicação de anticorpo policlonal contra Azospirillum amazonense estirpe AM 15. Rev Cien Agro 2009;68(1):1-11. 18. Chueire LMO. Classificação taxonômica das estirpes de rizóbio recomendadas para as culturas da soja e do feijoeiro baseada no sequenciamento do gene 16s rRNA. Rev Bras Cienc Solo 2003;27(5):833-840. 19. Silveira ÉL. Inoculações de bactérias promotoras de crescimento no cultivo de arroz em solução nutritiva [doctoral thesis]. Brasil, SP: Universidade Estadual Paulista, Jaboticabal; 2008. 236

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20. MAPA, Ministério da Agricultura, Pecuária e Abastecimento. Portaria nº36 de 3 de agosto de 2004- Anexo I. Diário oficial da União da República Federativa do Brasil, Brasília, nº 153 de 10 de agosto, 2004. Brasilia, DF, BRA: Ministério de Agriscultura, Pecuária e Abastecimento; 2004. 21. Deaker R, Roughley RJ, Kennedy IR. Legume seed inoculation technologyda review. Soil Biol Bioch 2004;(36):1275–1288. 22. Fernandes Júnior PI. Composições poliméricas a base de Carboximetilcelulose (CMC) e Amido como veículos de inoculação de Rizóbio em leguminosas [tesis maestria]. Brasil, RJ: Universidade Federal Rural do Rio de Janeiro; 2006. 23. Fages J. Azospirillum inoculants and field experiments. En: Okon Y, editor. Azospirillum/plant associations. Boca Raton: CRC. 1994:87-109. 24. Mehnaz S. Azospirillum: a biofertilizerfor every crop. In: Arora NK editor. Plant microbes symbiosis: Applied facets. 2015. 25. Okon Y, Labandera-Gonzalez CA. Agronomic applications of Azospirillum: an evaluation of 20 years worldwide field inoculation. Soil Biol Bioch 1996;(26):15911601. 26. Unno H. Atomic structure of plant glutamine synthetase. J Biol Chem 2006;281(39): 29287-29296. 27. Lambrecht M, Okon Y, Vande Broek A, Vandereleyden J. Indole-3-acetic acid: a reciprocal signalling molecule in bacteria-plant interactions. Trends Microbiol 2000;(8):298-300. 28. Duca S, Verderio E, Serafini-Fracassini D, et al. The plant extracellular transglutaminase: what mammal analogues tell. Amino Acids 2014;(46):777–792. 29. Madhaiyan M, Poonguzhali S, Kwon SW, et al. Bacillus methylotrophicus sp. nov., a methanol-utilizing, plantgrowth-promoting bacterium isolated from rice rhizosphere soil. Int J Syst Evol Microbiol 2010;(60):2490–2495. 30. Malhotra M, Srivastava S. Stress-responsive indole-3-acetic acid biosynthesis by Azospirillum brasilense SM and its ability to modulate plant growth. Eur J Soil Biol 2009;(45):73-80. 31. Walker TS, Bais HP, Grotewold E, et al. Root exudation and rhizosphere biology. Plant Physiol 2003;(132):44–51. 237

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32. Ilyas N, Bano A. Azospirillum strains isolated from roots and rhizosphere soil of wheat (Triticum aestivum L.) grown under different soil moisture conditions. Biol Fert Soils 2010;46(4):393–406. 33. Spaepen S, Vanderleyden J, Okon Y. Plant growth-promoting actions of rhizobacteria. Adv Bot Res 2009;(51):283–320. 34. Cohen AC, Bottini R, Pontin M, et al. Azospirillum brasilense ameliorates the response of Arabidopsis thaliana to drought mainly via enhancement of ABA levels. Physiol Plant 2015;(153):79–90. 35. Bashan Y, Holguin G, Bashan LE. Azospirillum-plant relationships: physiological, molecular, agricultural, and environmental advances (1997-2003). Canad J Microbiol 2004;(50):521-577. 36. Cassán F, Maiale S, Masciarelli O, et al. Cadaverine production by Azospirillum brasilense and its possible role in plant growth promotion and osmotic stress mitigation. Eur J Soil Biol 2009;(45):12–19. 37. Rodríguez-Salazar J, Suárez R, Caballero-Mellado J, Iturriaga G. Trehalose accumulation in Azospirillum brasilense improves drought tolerance and biomass in maize plants. Microbiol Lett 2009;(296):52–59. 38. Bárbaro IM. Técnica alternativa: co-inoculação de soja com Azospirillum e Bradyrhizobium visando incremento de produtividade. 2008. 39. Ferlini HA. Co-Inoculación en Soja (Glicyne max) con Bradyrhizobium japonicum y Azospirillum brasilense. 2006. 40. Benintende S, Uhrich W, Herrera M, et al. Comparación entre coinoculación con Bradyrhizobium japonicum y Azospirillum brasilense e inoculación simple con Bradyrhizobium japonicum en la nodulación, crecimiento y acumulación de N en el cultivo de soja. Agriscient 2009;(27):71-77. 41. Macedo MCM. Pastagens no ecossistema Cerrado: evolução das pesquisas para o desenvolvimento sustentável. Reunião anual da sociedade brasileira de zootecnia. Goiânia. 2005:56-84. 42. Batista K. Resposta do capim-marandu a combinações de doses de nitrogênio e enxofre [tesis maestria]. Brasil, SP: Universidade de São Paulo; 2002.

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43. Werner JC. Adubação de pastagens de Brachiaria spp. In: Anais do XI Simpósio Sobre Manejo de Pastagens. 1994. 44. Vogel GF, Martinkoski L, Ruzicki M. Efeitos da utilização de Azospirillum brasilense em poáceas forrageiras: Importâncias e resultados. Agropec Científic no Semi-Árido 2014;(10):01-06. 45. Bergamaschi C. Ocorrência de bactérias diazotróficas associadas às raízes e colmos de cultivares de sorgo [tesis maestria]. Brasil, RS: Universidade Federal do Rio Grande do Sul; 2006. 46. Fallik E, Okon Y. The response of maize (Zea mays) to Azospirillum inoculation in various types of soils in the field. World J Microb Biot 1996;(12):511-515. 47. Brasil MS, Baldani JI, Baldani BLD. Ocorrência e diversidade de bactérias diazotróficas associadas a gramíneas forrageiras do Pantanal Sul Matogrossense. R Bras Ciênc Solo 2005;(29):179-190. 48. Itzigsohn R, Burdman S, Okon Y, Zaady E, et al. Plant-growth promotion in natural pastures by inoculation with Azospirillum brasilense under suboptimal growth conditions. Arid Soil Res 2000;(13):151-158. 49. Oliveira PPA, Oliveira WS, Barioni WJ. Produção de forragem e qualidade de Brachiaria brizantha cv. Marandu com Azospirillum brasilense e fertilizada com nitrogênio. Embrapa pecuária sudeste, São Carlos, SP, 2007. 50. Fiori CCL, Bartchechen A, Watanabi SH, Guarido RC. Efeito da inoculação de Azospirillum brasiliense na produtividade da cultura do milho (Zea mays L). Campo Digit@l 2010;(5):56-59. 51. Guimarães SL, Bonfim-Silva EM Polizel AC, Campos TS. Produção de capim marandu inoculado com Azospirillum spp. Enciclopédia Biosfera 2011;(7):13-21. 52. Franche CK, Lindstrom C, Elmerich AB. Nitrogen fixing bacteria associated with leguminous and non-leguminous plants. Plant Soil 2009;(321):35-59. 53. Barros Neto CR. Efeito do nitrogênio e da inoculação de sementes com Azospirillum brasiliense no rendimento de grãos de milho. 2008. 29 p. Trabalho de Conclusão de Curso (Graduação em Agronomia) - Setor de Ciências Agrárias e de Tecnologia, Universidade Estadual de Ponta Grossa, Paraná.

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54. Braccini AL, Dan LGM, Piccinin GG, Albrecht LP, Barbosa MC, Ortiz AHT. Seed inoculation with Azospirillum brasilense, associated with theuse of bioregulators in maize. Revista Caatinga 2012;(25):17-23.

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https://doi.org/10.22319/rmcp.v11i1.5004 Technical note

Divaney Mamédio ac* Carlos Maurício Soares de Andrade b Aliedson Ferreira Sampaio b Daniele Rebouças Santana Loures c

Universidade Estadual de Maringá .Pós-Graduação em Zootecnia, Departamento de Zootecnia, Maringá, Paraná, Brasil. b

Embrapa Acre, Rio Branco, Acre, Brasil.

Universidade Federal do Recôncavo da Bahia .Centro de Ciências Agrárias, Ambientais e Biológicas, Cruz das Almas, Bahia, Brasil.

* Corresponding author: divaney.zootecnia@gmail.com

Abstract: The aim of this study was to assess the effect of soil management and planting spacing on establishment performance of mixed swards of purple stargrass (Cynodon nlemfuensis cv. BRS Lua) and forage peanut (Arachis pintoi cv. Belmonte). The treatments comprised two methods of soil management (conventional tillage, with desiccation followed by harrowing; and no-tillage, with sequential desiccation with glyphosate) and two planting spacing (50 and 100 cm between rows). The experimental design was in randomized blocks, arranged in split-plot. Both methods of soil management ensured rapid pasture establishment, with canopy cover greater than 94 % at 84 d after planting, with the notillage surpassing the conventional tillage, and at a cost of no-tillage 7 % lower. Reducing planting spacing from 100 cm to 50 cm accelerated canopy cover and reduced weed incidence. The initial contribution of forage peanut in the botanical composition was

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relatively small, declining by 3.8 % on average at 36 d after planting to less than 1.2 % at 84 d. No-tillage was as efficient in establishing mixed swards as conventional tillage. Key words: Arachis pintoi, Cynodon nlemfuensis, No-tillage, Stolon planting, Pasture renovation.

Received:28/07/2018 Accepted: 10/12/2018

The heterogeneity of climate, soil and livestock production systems in Brazil requires greater diversification of planted pastures to reduce the vulnerability of the livestock sector and promote a better genotype-environment adequacy(1). The clearest example of this vulnerability is the degradation of millions of hectares of planted pastures with Brachiaria brizantha cv. Marandu due to soil waterlogging in the Brazilian Amazon(2). Several cultivars of Cynodon grasses have been researched since the decade of 60(3) showing high productivity and persistence in different regions of Brazil. However, the adoption of these grasses has been low because most cultivars do not produce viable seeds and propagation is vegetative(4). Usually, pasture planting is made through the conventional planting methods and, mostly, though manual handling, which limits the efficiency of the process of pasture renovation due to the decrease in operational efficiency, raising the costs associated with pasture implementation through the planting of seedlings. Because of that, techniques with a higher degree of mechanization have been preferred, as a way to speed up the renovation process, reduce the workforce used in this activity and, with that, minimize the costs for the producer. The use of direct planting is an established method in agriculture, although it is absent in the livestock production systems, thus requiring the development of studies with different methods of soil management and more efficient techniques for establishment of pastures can increase the reliability of farmers and adoption rate in Brazil. In the state of Acre, purple stargrass (Cynodon nlemfuensis cv. Lua) has been the most planted Cynodon cultivar, because of its productivity, aggressiveness and high tolerance to soil waterlogging(5). This cultivar has formed productive, persistent and stable mixtures with forage peanut (Arachis pintoi cv. Belmonte), where beef cattle annual liveweight gains up to 850 kg ha-1 have been measured(6). Also, similar results were registered in Paranรก state with the mixture of Cynodon spp. cv. Coastcross-1 with Arachis pintoi cv. Amarillo(7,8).

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Thus, the objective of this study was to evaluate the technical and economic efficiency of vegetative propagation for establishment of mixed pastures of purple stargrass and forage peanut using two methods of soil management and two planting spacing. The experiment was carried out in an area of 1.6 ha of degraded pasture of Brachiaria brizantha cv. Marandu in Senador Guiomard, State of Acre, Brazil (09º52'35"S, 67º25'16"W), from November 2015 to March 2016. According to Köppen classification, the climate of the region is humid equatorial, with average annual rainfall of 1,958 mm, with the rainy period from October to April and a well-defined dry season from June to August. The annual average temperature is 25.3 ºC and the air relative humidity is approximately 85% (9). The soil is classified as Red Yellow Latosol (Oxisol), with the following characteristics: pH (H2O)= 5.38; P Mehlich-1=3.12 mg dm-3; K Mehlich-1=0,17 cmolc dm-3; Ca2+=2.57 cmolc dm-3; Mg2+=0.36 cmolc dm-3; H+Al=4.63 cmolc dm-3; CTC=7.72 cmolc dm-3; organic matter=10.35 g kg-1; base saturation=40.1 % and clay=146.4 g kg-1. The experimental design was in randomized blocks with four replications and treatments arranged in split-plot. The plots measured 40 x 50 m and subplots 20 x 50 m. Two soil management methods were tested in plots: conventional tillage (CT), which consisted in vegetation desiccation with the herbicide glyphosate [(Roundup Ultra - Bayer) (1.95 kg ha-1)], followed by two passes of disc harrow and one of leveling disc harrow on the planting eve; and no-tillage (NT), in which the vegetation was subjected to sequential desiccation with 1.95 and 0.65 kg ha-1 of glyphosate at 70 and 35 d before planting, respectively. Two planting spacing were tested in subplots: 50 and 100 cm between rows. Stolons of purple stargrass (Cynodon nlemfuensis cv. BRS Lua) and forage peanut (Arachis pintoi cv. Belmonte) were harvested and prepared for planting by cutting stolon pieces with approximately 30 cm in length. The planting operation was carried out with a 3-row stolon planter coupled to a tractor. Grass stolons were planted in external rows and legume stolons in the central row. At the time of no-tillage planting, surface residue of marandugrass presented water content of 460 g kg-1 and dry mass of 2,170 kg ha-1. Planting spacing of 100 cm was obtained with a single planting operation, expending 700 kg ha-1 of grass stolons and 300 kg ha-1 of legume stolons. To reduce planting spacing to 50 cm, a second planting operation was carried out interspersedly using consequently twice the amount of stolons. Pastures were fertilized immediately after planting with 200 kg ha-1 of NPK 8-28-16 and after 30 d with 100 kg ha-1 of urea. Weeds were controlled with a pre-emergent application of herbicide trifluralin [(Trifluralina Nortox - Nortox S.A.) (1.8 kg a.i. ha-1 in NT and 0.81 kg a.i. ha-1 in CT)] and a post-emergent application of herbicide bentazon [(Basagran® 600 - BASF S.A.) (1.5 kg a.i. ha-1)] 30 dalater.

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Shoot emergence of both forages was evaluated at 21 d after planting (DAP) by counting the number of sprouts inside a frame of 100 x 100 cm, in 15 sampling points per experimental unit. Pasture height, canopy cover and botanical composition were evaluated at 35, 56 and 84 DAP, in 12 sampling points per experimental unit using a frame of 100 x 100 cm. Within each sampling unit the following measurements were taken: pasture height (cm), measured from ground level to the curvature of the plant canopy, using a ruler; canopy cover (%), estimated visually; and botanical composition (%), visually estimating the percentage contribution of each component (purple stargrass, forage peanut, marandugrass and dicotyledonous and monocotyledonous weeds) to the total biomass(10). Herbage mass was evaluated at 84 DAP. Six samples were collected per experimental unit using a frame of 100 x 100 cm. The biomass was clipped to a 5-cm stubble height, with subsequent weighing and drying at 55 ºC for 72 h in a forced air circulation oven (model TE-394/7, brand Tecnal-Brazil). Relative levels of chlorophyll content in leaf blades of purple stargrass were measured at 70 DAP using a hand-held chlorophyll meter (model SPAD-502 Plus, brand Minolta Corporation, Japan). Readings were performed in the 15 first fully expanded leaf blades per experimental unit. Technical coefficients and costs of services and inputs were appraised over the experiment for each modality of pasture renovation. The costs of mechanized services were calculated based on the total operating cost per hour worked of the tractorimplement set, using an electronic spreadsheet(11). Input prices were collected in the market of Rio Branco, AC, in the first half of the year 2016. Data were tested for normality of error (Shapiro-Wilk test)(12) and homogeneity of variance (Bartlett's test)(13). Percentage data concerning botanical composition and canopy cover were previously submitted to arcsine transformation. Data were submitted to analysis of variance using the PROC GLM of SAS(14). Significant interactions (P<0.05) were unfolded by using the ‘SLICE’ statement. Treatment means were calculated using the ‘LSMEANS’ statement(14) and comparisons made using the F test (P<0.05). There was no effect (P>0.05) of the soil management methods on shoot emergence of purple stargrass and forage peanut (Figure 1). However, both forages presented higher shoot emergence (P<0.05) when planted with 50-cm spacing. Pasture established by NT presented higher canopy cover (P<0.05) at 84 DAP. Canopy cover over the experimental period was higher (P<0.05) when pasture was planted with 50-cm spacing, in particular at 35 DAP (Figure 2).

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Figure 1: Shoot emergence (number of sprouts m-2) of Cynodon nlemfuensis cv. BRS Lua and Arachis pintoi cv. Belmonte at 21 d after planting according with soil management methods and planting spacing

CT - conventional tillage; NT â&#x20AC;&#x201C; no-tillage. Means followed by the same letters, for each forage and study variable, are not different (P<0.05).

Figure 2: Evolution of canopy cover (%) over the establishment period of Cynodon nlemfuensis cv. BRS Lua and Arachis pintoi cv. Belmonte as affected by the soil management methods and planting spacing

Means followed by the same letters, for each date and study variable, are not different (P<0.05).

Pasture height was higher (P<0.05) in NT than in CT over the establishment period at 56 and 84 DAP and also was higher at 50-cm spacing at 56 DAP (Figure 3).

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Figure 3: Evolution of pasture height (cm) over the establishment period of Cynodon nlemfuensis cv. BRS Lua and Arachis pintoi cv. Belmonte as affected by the soil management methods and planting spacing

Means followed by the same letters, for each date and study variable, are not different (P<0.05).

Botanical composition was monitored at 35, 56 and 84 DAP, and there was a significant interaction (P<0.05; Table 1) between the soil management method and planting spacing only for the percentage of monocot-weeds at 56 DAP and purple stargrass at 84 DAP. Thus, such interactions will be unfolded in Table 2, after the presentation of the main effects in Table 1. No-tillage contributed to greater (P<0.05; Table 1) percentage of marandugrass at 35 DAP and also a higher (P<0.05) percentage of monocot-weeds over the establishment period, although at 56 DAP the effect was only significant when associated to 100-cm spacing (Table 2). When planted with CT, pastures presented higher percentage of purple stargrass at 56 DAP (Table 1). Percentage of purple stargrass was greater (P<0.05) over the establishment period when planting spacing was reduced from 100 to 50 cm (Table 1), although at 84 DAP this effect was significant only in NT (Table 2). Reducing planting spacing also increased (P<0.05) the percentage of forage peanut at 84 DAP (Table 1). In contrast, the wider spacing favored the recruitment of marandugrass at 84 DAP and monocot-weeds at 35 DAP (Table 1), also at 56 DAP, when associated to NT (Table 2).

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Table 1: Influence of soil management methods and planting spacing on pasture botanical composition Botanical components (%) Soil management Planting spacing SEM methods (cm) Component CT NT 100 50 35 days after planting Cynodon nlemfuensis 88.36 a 83.11 a 83.18 b 88.28 a 2.159 Arachis pintoi 3.54 a 4.09 a 3.59 a 4.04 a 0.586 Brachiaria brizantha 2.00 b 3.00 a 3.18 a 1.82 a 0.468 Dicot-weeds 3.14 a 3.39 a 4.12 a 2.41 a 0.705 Monocot-weeds 2.96 b 6.42 a 5.93 a 3.45 b 1.111 56 days after planting Cynodon nlemfuensis 85.02 a 75.66 b 77.08 b 83.60 a 1.803 Arachis pintoi 1.52 a 2.77 a 1.92 a 2.37 a 0.374 Brachiaria brizantha 3.28 a 5.10 a 4.83 a 3.55 a 0.514 Dicot-weeds 3.19 a 3.48 a 2.85 a 3.82 a 0.412 Monocot-weeds 84 days after planting Cynodon nlemfuensis Arachis pintoi 0.73 a 1.62 a 0.87 b 1.47 a 0.190 Brachiaria brizantha 4.77 a 7.19 a 8.31 a 3.65 b 1.142 Dicot-weeds 4.55 a 4.04 a 4.90 a 3.70 a 0.513 Monocot-weeds 4.59 b 8.42 a 8.69 a 4.33 a 1.075 ab

SEM - standard error of means; CT - conventional tillage; NT â&#x20AC;&#x201C; no-tillage. Means of each botanical component, followed by equal letters, are not different (P<0.05).

Table 2: Effect of the interaction between the soil management methods and planting spacing Monocot-weeds at 56 DAP (%) Planting spacing Soil management methods SEM 100 cm 50 cm Conventional tillage 8.6 Ba 5.3 Aa 1.2817 No-tillage 18.0 Aa 8.0 Ab Cynodon nlemfuensis cv. BRS Lua at 84 DAP (%) SEM Planting spacing Soil management methods 100 cm 50 cm Conventional tillage 82.7 Aa 88.0 Aa 2.1477 No-tillage 69.0 Bb 85.7 Aa SEM - standard error of means. Means followed by the same letters, uppercase in columns and lowercase in lines, are not different (P<0.05).

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There was no interaction (P>0.05) between the soil management method and planting spacing for herbage mass at 84 DAP, with significant effect (P<0.05) only for planting spacing (Table 3). Pasture productivity was 20 % higher when planted at 50-cm spacing. There was an interaction between soil management method and planting spacing on the relative levels of chlorophyll (SPAD values) in leaves of purple stargrass, as a lower SPAD value was measured on NT with100-cm spacing (Table 4).

Table 3: Effect of soil management method and planting spacing on HM - herbage mass (Cynodon nlemfuensis cv. BRS Lua and Arachis pintoi cv. Belmonte) at 84 d after planting Soil management methods Planting spacing (cm) SEM Variable CT NT 100 50 116.39 -1 HM (kg ha ) 4,960 a 5,259 a 4,634 b 5,585 a ab

SEM - standard error of means; CT - conventional tillage; NT â&#x20AC;&#x201C; no-tillage. Means followed by the same letters in lines, for each study variable, are not different (P<0.05).

Table 4: SPAD values on leaf blades of Cynodon nlemfuensis cv. BRS Lua at 70 d after planting Planting spacing (cm) Soil management methods SEM 100 50 Conventional tillage 29.7 Aa 29.7 Aa 0.2156 No-tillage 28.1 Bb 29.1 Aa SEM - standard error of means. Means followed by equal letters, uppercase in lines and lowercase in columns, are not different (P<0.05).

In practical terms, the method of soil management had relatively little influence on pasture establishment performance, which was adequate in both methods, as canopy cover exceeded 94 % at 84 DAP. However, NT positively influenced pasture height and canopy cover at the end of the establishment period. This effect seems to be related with a best sprouting of stolons after planting. In NT, the effect of residues on the soil surface can decreases temperature and water loss through evaporation, thereby reducing dehydration and increase plants survival after planting as demonstrated by Gasparim et al(15) and Furlani et al(16). Moreover, it was observed that in NT were opened shallower furrows and buried a lower proportion of stolons, due to a firmer soil structure. In a study with Tifton 85 bermudagrass (Cynodon spp.), partial burial of stolons improved sprouting percentage when compared to total burial(17). Reducing planting spacing from 100 cm to 50 cm, with use of twice the amount of stolons, more than doubled shoot emergence of purple stargrass and forage peanut and speed up canopy cover until 56 DAP. However, the difference in canopy cover disappeared at the end of establishment period. 248

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In degraded Brachiaria pastures, a big and active seed bank and the aggressiveness of its seedlings, hampers their replacement by other forages(18). The weed control protocol used in this study was effective in reducing the recruitment of marandugrass and. Previous desiccation with glyphosate in CT and sequential desiccation in NT, associated with the use of herbicide trifluralin, concurred to prevent the regrowth of marandugrass and the emergence of its seeds. As a result, botanical composition measured at 84 DAP showed only 4 to 8 % of marandugrass. Conventional tillage, which associated mechanical and chemical methods of weed control, was more effective in controlling marandugrass and monocot-weeds (mainly Cyperaceae), when compared to NT, where only chemical methods were used. Disc-harrowing contributes to bury weed seeds, reducing their infestation potential. In NT, the residues on the soil surface also contributes to reduce weed emergence. However, higher emergence of weeds was observed along the furrows where soil mobilization occurred and residue was buried. The herbicide trifluralin can be retained by residues, even when rain occur soon after application(19), reducing its efficacy. However, the formulation used in this study is registered for NT and CT, with higher dose for NT to compensate for retention by surface residues. Reducing planting spacing from 100 cm to 50 cm decreased marandugrass and monocotweeds incidence. Herbicide bentazon reduced the incidence of dicot-weeds in all treatments, and the main species found was Calopogonium mucunoides, a forage legume of spontaneous occurrence in the area(20). At the end of the establishment period, purple stargrass represented more than 80 % of the botanical composition in all treatments, except in NT with 100-cm spacing, which favored infestation by sedges. Forage peanut participation in botanical composition was small, decreasing from approximately 3.8 % on average at 35 DAP to 1.2 % at 84 DAP. This can be attributed to the highest planting rate of purple stargrass in relation to forage peanut (2:1), the lowest sprouting efficiency of forage peanut stolons, the faster establishment of purple stargrass and also the effect of nitrogen (N) fertilization at 30 DAP, which favors grass competition against the legume. At 21 DAP, the ratio of grass shoots to legume shoots was 7.5:1 in 50-cm spacing and 10:1 in 100-cm spacing. This indicates that the sprouting efficiency of purple stargrass was three to five times higher than that of forage peanut. Only mature stolons were used for both plants. Thus, this difference in sprouting efficiency can be inherent to these plants, but also related to the degree to which planting material is buried in the soil at planting. As previously mentioned, complete burial of stolons reduces sprouting efficiency. It was noted a greater proportion of forage peanut stolons completely buried than that of purple stargrass. Forage peanut was planted in the central row and, as the stolon planter has no independent lines, there may have been a further deepening of the central furrows. Stolon preparation may also have influenced, as

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forage peanut stolons were cut shorter than purple stargrass ones. These aspects deserve further investigations. This would also match the stolon planting rate (1:1). Even so, there should be initial predominance of grass because of its faster establishment. Slowing purple stargrass establishment to reduce its competition against forage peanut can have negative consequence on weed control(21). Thus, it could be preferable to accept a lower initial proportion of legume than a pasture infested by hard to control weeds. This mixture has shown high compatibility in Acre. Dominance of one species tends to be temporary, with proportion often stabilizing with time in one-third forage peanut and two-thirds purple stargrass(5). Start the first grazing when canopy cover reaches 80% instead of 100% as occurred in this study, could also decrease initial grass competitiveness without compromising weed control. In addition, top-dressing N-fertilization should only be used under NT, as N release from soil organic matter is higher under CT(22). The relative content of chlorophyll (SPAD value) on plant leaves has been used to infer the N status of plants(23). In this study, greater SPAD values in purple stargrass were expected in CT, due to the effect of soil tillage and incorporation of marandugrass residues, which could stimulate the decomposition of organic matter and N release in relation to NT. However, lower SPAD values were observed only when stargrass was planted in NT with 100-cm spacing . This may indicate increased competition for N with monocot-weeds in this treatment. N-fertilization (45 kg N ha-1) also contributed to reduce the differences among the treatments. Novel pasture establishment methods should be judged based on its technical and economic efficiency. No-tillage requires greater investment in inputs but saves on services, in particular those related to tillage operations in CT (Table 5). In general, NT saves the equivalent to 15 kilograms of beef cattle per hectare compared to CT. Reducing planting spacing from 100 cm to 50 cm increases the cost of pasture renovation in more than 30 %, due to increased expenses with harvesting, transporting, and planting stolons.

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Table 5: Cost estimate to establish a mixed pasture with Cynodon nlemfuensis cv. BRS Lua and Arachis pintoi cv. Belmonte, according to the method of soil management and planting spacing Conventional tillage Cost per ha

Planting spacing (cm) 100

Services, R$ Inputs, R$ Total, R$ Total, kg1

No-tillage Planting spacing (cm)

847.21 614.00 1,461.21

1,260.00 660.00 1,920.00

180.0

235.5

100

530.28 817.00 1,347.28

943.06 863.00 1,806.06

165.0

222.0

Total cost estimate in arroba (kg) of beef cattle, quoted in R$ 8.13 in March 2016 in Rio Branco, AC. Source: Andrade et al(2016).

The cheapest method (NT with 100-cm spacing) had the smallest technical efficiency, allowing greater recolonization of marandugrass and monocot-weeds. The total investment for pasture renovation planting a mixture of purple stargrass and forage peanut, converted into 15 kilograms of beef cattle, ranged from 165 to 240 kilograms per hectare. These methods are more expensive than establishing pastures using grass seeds in Acre, which historically have varied from 120 to 180 kilograms per hectare(24). Degraded Brachiaria brizantha pastures can be renovated by planting a mixture of purple stargrass and forage peanut with both CT and NT. In NT, planting 2,000 kg ha-1 of stolons in 50-cm spacing speed up pasture establishment and increases weed control effectiveness. Reducing row spacing from 100 cm to 50 cm increases the cost of pasture renovation in more than 30 %. The use of two parts of purple stargrass for one part of forage peanut do not assure the legume establishment, leading to an early predominance of the grass. Forage peanut is slower to establish than purple stargrass. Greater planting rates of forage peanut and anticipation of first grazing are techniques that should be tested to reduce initial grass dominance.

Acknowledgments Thanks to the CAPES and CNPq development agencies for granting the scholarship, and the owner of Iquiri Farm, Joaquim Pedro Ribeiro do Valle Filho. The authors declare they have no conflict of interest regarding the work presented in this report.

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Literature cited: 1. Valle CB, Simeão RM, Barrios SCL. Seleção e melhoramento de plantas forrageiras. In: Reis RA, Bernardes TF, Siqueira GR. Forragicultura: ciência, tecnologia e gestão dos recursos forrageiros. 1rst ed. Jaboticabal: M. de L. Brandel-ME; 2013:349-366. 2. Pedreira BC, Pitta RM, Andrade CMS, Dias-Filho MB. Degradação de pastagens de Braquiarão (Brachiaria brizantha cv. Marandu) no Estado de Mato Grosso. 1rst ed. Sinop (MT): Embrapa Agrossilvipastoril; 2014. 3. Aronovich S, Rocha GL. Gramíneas e leguminosas forrageiras de importância no Brasil Central Pecuário. Inf Agropec 1985;11(132):3-13. 4. Pedreira CGS. Gênero Cynodon. In: Fonseca DM, Martuscello JA. Plantas forrageiras. 1rst ed. Viçosa: UFV;2010:78-130. 5. Andrade CMS, Assis GML, Fazolin M, Gonçalves RC, Sales MFL, Valentim JF, Estrela JLV. Grama-estrela-roxa: gramínea forrageira para diversificação de pastagens no Acre. 1rst ed. Rio Branco (AC): Embrapa Acre; 2009. 6. Andrade CMS, Ferreira AS, Casagrande DR. Uso de leguminosas em pastagens: potencial para consórcio compatível com gramíneas tropicais e necessidades de manejo de pastejo [Anais]. Simpósio sobre Manejo de Pastagem. Piracicaba, SP. 2015:27. 7. Paris W, Cecato U, Branco AF, Barbero LM, Galbeiro S. Produção de novilhas de corte em pastagem de Coastcross-1 consorciada com Arachis pintoi com e sem adubação nitrogenada. Rev Bras Zootec 2009;38(1):122-129. 8. Barbero LM, Cecato U, Lugão SMB, Gomes JAN, Limão VA, Abrahão JJS, Roma CFC. Produção animal e valor nutritivo da forragem de pastagem de coastcross consorciada com amendoim forrageiro. Arq Bras Med Vet Zootec 2010;62(3):645653. 9. Duarte AF. Aspectos da climatologia do Acre, Brasil, com base no intervalo 19712000. Rev Bras Meteorol 2006;21(3b):308-317. 10. Whalley RDB, Hardy MB. Measuring botanical composition of grasslands. In: t’Mannetje L, Jones RM. Field and laboratory methods for grassland and animal production research. 1rst ed. Londres: CABI Publishing; 2000:67-102.

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11. CATI - Coordenadoria de Assistência Técnica Integral. Estimativa do custo operacional de tratores agrícolas. São Paulo: CATI. 2016. http://www.cati.sp.gov.br/portal/produtos-e-servicos/publicacoes/acervotecnico/acervo/administracao_rural/custo_operacional_maquinas.xlt. Access June 29, 2016. 12. Shapiro SS, Wilk MB. An analysis of variance test for normality (complete samples). Biometrika 1965;52(3/4):591-611. 13. Bartlett MS. Tests of significance in factor analysis. Br J Stat Psychol 1950;3(2):7785. 14. SAS - Statistical Analysis System, SAS Institute Inc., SAS User’s Guide, Cary, USA: SAS Institute Inc.; 2003. 15. Gasparim E, Ricieri RP, Silva SDL, Dallacort R, Gnoatto E. Temperatura no perfil do solo utilizando duas densidades de cobertura e solo nu. Acta Sci Agron 2005;27(1):107-115. 16. Furlani CEA, Gamero CA, Levien R, Silva RPD, Cortez JW. Temperatura do solo em função do preparo do solo e do manejo da cobertura de inverno. Rev Bras Ciênc Solo 2008;32(1):375-380. 17. Baseggio M, Newman YC, Sollenberger LE, Fraisse C, Obreza T. Stolon type and soil burial effects on ‘tifton 85’ bermudagrass establishment. Crop Sci 2014;54(5):2386-2393. 18. Rodrigues LRA, Rodrigues TJD. Estabelecimento dos capins do gênero Cynodon em áreas de Brachiaria spp [Anais]. Workshop sobre o Potencial Forrageiro do Gênero Cynodon. Juiz de Fora, MG. 1996:1. 19. Rodrigues BN, Lima J, Yada IFU, Fornarolli DA. Influência da cobertura morta no comportamento do herbicida trifluralin. Planta Daninha 1998;16(2):163-173. 20. Valentim JF, Carneiro JC. Pueraria phaseoloides e Calopogonium mucunoides [Anais]. Simpósio sobre Manejo de Pastagem. Piracicaba, SP. 2000:17. 21. Miranda EM, Saggin Jr OJ, Silva EMR. Amendoim forrageiro: importância, usos e manejo. 1rst ed. Seropédica (RJ): Embrapa Agrobiologia; 2008. 22. Borghi E, Crusciol CAC. Produtividade de milho, espaçamento e modalidade de consorciação com Brachiaria brizantha em sistema plantio direto. Pesq Agropec Bras 2007;42(2):163-171. 253

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23. Guimarães SL, Santos CSA, Silva EMB, Polizel AC, Batista ÉR. Nutritional characteristics of marandu grass (Brachiaria brizantha cv. marandu) subjected to inoculation with associative diazotrophic bacteria. Afr J Microbiol Res 2016;10(24):873-882. 24. Andrade CMS, Santos DM, Ferreira AS, Valentim JF. Técnicas de plantio mecanizado de forrageiras estoloníferas por mudas. 1rst ed. Rio Branco (AC): Embrapa Acre; 2016.

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https://doi.org/10.22319/rmcp.v11i1.4674 Technical note

Growth dynamics and nutrient extraction curves of Pennisetum sp. (Maralfalfa)

Oscar López-Astilleros a Julio Cesar Vinay Vadillo b Yuri Villegas-Aparicio a Isaías López Guerrero b Salvador Lozano-Trejo a*

Instituto Tecnológico del Valle de Oaxaca, División de Estudios de Posgrado e Investigación. Programa de Maestría en Ciencias, Oaxaca México. CIR Golfo Centro/INIFAP/SAGARPA. Campo experimental “La Posta”, Carretera La Tinaja-Paso del Toro, 94270 Medellín, Veracruz-Llave, México. b

Corresponding author: lozanos2004@gmail.com

Abstract: Mathematical models are useful in calculating forage nutrient concentration, nutrient extraction and growth curves. An analysis was done of growth and nutrient content in Pennisetum sp. (maralfalfa) applying Gompertz and Logistic models. Dilution curves for nitrogen, phosphorous and potassium (NPK) were generated using a negative potential model and maximum extraction values were calculated with a second order polynomial equation. Nutrient unitary extraction and nutrient recovery efficiency of NPK were also calculated. The goodness-of-fit models were compared using a completely randomized design with a 2 x 2 factorial arrangement, in which factor A was the two models and factor B was the real-world assay (fertilized treatment vs. control). Nutrient concentration curves were optimized with the Levenberg-Marquart algorithm. Both models’ goodness-of-fit were similar among the study plots, although the Gompertz model better represented biological reality. Maximum

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growth rate was reached at 21 d after sowing in the control plots and at 56 d in the fertilized plots. The inflection point was reached at 30 ds in the control plots and at 31 d in the fertilized plots. Nutrient concentration decreased over time in both the treatment and control, and dry matter production was highest in the fertilized treatment. Aside from calcium and magnesium, nutrient unitary extraction did not differ between the treatment and control. Nutrient recovery efficiency was 48 % for nitrogen, 39% for phosphorous and 104 % for potassium, suggesting excess nutrient levels. Key words: Gompertz, Logistics, Growth rate, Nutrient dilution.

Received: 23/10/2017 Accepted:14/12/2018

Continuous forage production is the greatest challenge in meeting feeding needs in beef and dairy cattle production systems(1). Small and medium livestock producers in the tropics face chronic forage shortages caused by droughts and inadequate management practices(2,3). Harvested forages cultivated on lands with productive potential are fundamental to reducing the production costs of feeding cattle(4). Moreover, they require less area for forage production and therefore have a relatively lower impact on ecosystems transformed by increasingly intense livestock development(3). Sustainable livestock production can be difficult, and continuous production forages are vital to its success. If a forage species is known to be productive further data is needed on its growth rate and basic reference parameters to facilitate effective management decisions and increase harvest efficiency(5,6), as well as to guarantee expression of its maximum productive potential. Due to their rapid growth and high production volume the forage grasses Pennisetum spp. can be used in intensive harvest systems(7,8). Maximizing Pennisetum spp. production can benefit from mathematical models that estimate a specific speciesâ&#x20AC;&#x2122; moment of maximum biological production and nutrient extraction (primarily NPK). This information assists in planning optimum time of harvest and fertilizer application, and minimizing environmental impacts. Improving forage yields has been associated with soil nutrient contribution, which increases crop nutritional value and crop production(9), as well as sufficient accumulation of heat units and adequate water supply to take full advantage of a forage speciesâ&#x20AC;&#x2122; productive potential(10). The present study had two objectives. The first was to describe growth in Pennisetum sp. (ecotype maralfalfa) during the rainy season in a control (unfertilized) and fertilized treatment, and using the Gompertz and Logistic models. The second was to model the nutrient extraction and dilution curves, and calculate unitary extraction (UE) and nutrient 256

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recovery efficiency (NRE) for nitrogen (N), phosphorus (P) and potassium (K) to determine proper fertilizer load for the next production cycle. A Pennisetum sp. (maralfalfa) pasture was established under seasonal conditions in July 2010 to January 2011 at the La Posta Experimental Field, in Paso del Toro, in the state of Veracruz, Mexico (19Âş00'49" N; 96Âş08'19" W). Located at 10 m asl(11), regional climate is sub-humid tropical (Aw2 in KĂśppen climate classification)(12). Accumulated rainfall during the sixmonth study period was 1,461 mm, average relative humidity was 77.4%, and average temperature was 25 Â°C (maximum = 35 Â°C; minimum = 15 Â°C). Soils at the experimental field are predominantly deep Vertisol type soils with acidic pH (5.4), a clay-sandy friable texture and 2.6% organic matter content(13). Experimental unit area was 4.0 x 12.0 m (48 m2). It was planted in furrows 0.80 m apart with 0.80 m between plants, following a completely random block design with 16 replicates. In the fertilization treatment a 141-43-20 (N-P-K) dose was applied using 200 kg urea, 50 kg of 18-46-00 mixture and 200 kg of 20-10-10 mixture. This was applied in two applications: the first (8 days post standardizing cut) included 100 kg urea, 100 kg 20-10-10 mixture and 25 kg 18-46-00 mixture; the second (60 days later) included all the remaining N, P and K(14).

The grass was harvested every 21 d at 25 cm above ground level, with a total of eight cuts and a study period of 168 days. In each sampling, fresh matter (FM) production per plot was recorded. A 300 g subsample was collected from the FM, dried in a forced air oven at 55 Â°C to constant weight, and dry matter (DM) content estimated with a correction at 105 Â°C(15). The samples were milled (Thomas Wiley, model 3383L40) to a 1 mm particle size for NPK and chemical analyzes. Using the accumulated DM weights, the curve and growth rate were calculated with equation 1.

đ??şđ?&#x2018;&#x2026; =

đ??ˇđ?&#x2018;&#x20AC;đ?&#x2018;&#x192;đ?&#x2018;Ą2 â&#x2C6;&#x2019;đ??ˇđ?&#x2018;&#x20AC;đ?&#x2018;&#x192;đ?&#x2018;Ą1 đ?&#x2018;&#x2021;2â&#x2C6;&#x2019;đ?&#x2018;&#x2021;1

(1)

Where: GR= growth rate kg DM ha-1 d-1; DMPt2= dry matter production at time 2, kg DM ha-1; DMPt= dry matter production at time 1, kg DM ha-1; T2= final time, T1= initial time.

The growth curves were created with the Gompertz(16) and Logistic(17) models, using the Micromath Scientist software (Micromath Research, 2006), and applying the Powell algorithm as the minimization method. The Gompertz function used was:

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Y  Aexp  exp    xB  (2) Where Y= yield, A= maximum production, -B= inflection point, µ= growth rate, and x= time in days. The Logistic function used was:

P  A /(1  B * exp( c *T )) (3) Where P= production, A= maximum production, B= inflection point, c= growth rate(18). Forage N content was calculated with the Kjeldhal method (VELP Scientifica, Series D-K6, USA), using 0.5 g samples in triplicate per whole plant. Phosphorous was quantified with ammonium vanadate in a UV-visible spectrophotometer (UV/VIS Lambda 2, Perkin Elmer, USA). Potassium, calcium and magnesium were measured by atomic absorption, while sulpher was measured with the turbidimetric method using barium sulfate in a UV/VIS spectrophotometer(19). Comparison of nutritional NPK content in the forage samples at the different harvests was done with equation 4(20).

y  ax B …. (4) Where a= critical concentration of nutrient in plant, x= DM production, –B= decrease (dilution) rate of nutrient in plant, calculated using the Levenberg-Marquart logarithm for minimizing variance. Each nutrient’s unitary extraction (UE) was estimated based on the nutritional composition of each nutrient (N, P, K) in the grass species. It was calculated with equation 5(21).

UE= FY/NAF (5) Where: UE= unitary extraction or efficiency of nutrient in the fertilizer, FY= forage yield (kg ha-1), and NAF= nutrient applied via fertilizer (kg ha-1).

Calculation of NPK nutrient recovery efficiency (NRE) was done with equation 6(22):

NRE = [(NT – Ncontrol)/Dose in trat] x 100 (6)

Where: NRE= nutrient recovery efficient, NT= plant nutrient content (N, P or K) in treatment; Ncontrol = plant nutrient content (N, P or K) in control, and Dose in trat = nutrient dose applied in fertilizer (NPK). The NT and Ncontrol were calculated from the derivative of each fitted polynomial, for maximum NPK extraction. The goodness-of-fit indicators in the Gompertz and Logistic models were R2, adjusted R2, r(23), and the model selection criterium (MSC)(24). For the coefficients A, B, C and µ, an 258

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analysis of variance (ANOVA) was applied to NRE using the GLM procedure (SAS ver. 9.01), and a comparison of means was done with the Duncan method (α=0.05)(25). The Gompertz model better represented the biological reality at the inflection point (B) for the treatment and the control plots. Maximum DM yield was 10,414 kg DM ha-1 in the treatment plots at 161 d, and 5,952 kg DM ha-1 in the control plots at 168 days (Table 1). Growth rate rose continually in the fertilized plots up to 56 d, with an inflection point at 31 d (Figure 1a). In the control plots, maximum growth rate occurred at 21 d and then descended thereafter, with an inflection point at 30 d (Figure 1b). This growth behavior for maralfalfa grass is similar to other tropical grass species(26), with a sigmoid curve until reaching maximum expression followed by an asymptotic decrease. This behavior indicates a reasonable fit of the Gompertz model data to the biological reality represented in the curve; the resulting parameters provide trustworthy information on growth(18).

Table 1: Goodness-of-fit indicators and Gompertz model coefficients for maralfalfa ecotype grass fertilization treatment (a), and control (b) during rainy season Indicators/coefficients Treatment Control R2 R2adj r MSC

-1

A Maximum yield (kg ha ) B Inflection point (days) µ Growth rate (kg DM ha-1day-1)

0.98 ± 0.004 a 0.87 ± 0.028 a 0.93 ± 0.015 a 1.54 ± 0.262 a

0.98 ± 0.004 a 0.84 ± 0.046 a 0.92 ± 0.025 a 1.44 ± 0.378 a

10,414 ± 2,254.57 a 31.12 ± 7.094 a 43 ± 0.68 a

5,952± 2,684.75 b 29.62 ± 15.946 a 31 ± 0.54 b

ab Different letter suffixes in the same row indicate significant difference (Duncan= 0.05). ± standard error R2= determination coefficient, R2adj= adjusted R2, r= coefficient of correlation, MSC= model selection criterium.

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Figure 1. Fitted growth curve and rate (Gompertz), maralfalfa ecotype grass fertilization treatment (a), and control (b) during rainy season

100

150

200

Growth rate

7000

6000

5000

4000

3000

2000

1000

Time (Days) (a)

kg DM ha-1 d-1

120 100 80 60 40 20 0

kg DM ha-1

12000 10000 8000 6000 4000 2000 0 0

Growth curve

Growth rate

kg DM ha-1 d-1

kg DM ha-1

Growth curve

0 0

100 150 Time (Days) (b)

200

The low forage yields in the control treatment are related to the low availability of nutrients in the soil(27). At 56 d, fertilized Pennisetum OM-22 varieties have reported yields of 7 t DM ha-1(23), higher than the 6.1 t ha-1 produced at 56 d harvest in the present study. This is the maximum expressed potential yield based on the physiological processes of photosynthesis, heat unit accumulation, water absorption, nutrient availability and growth(10). At this yield a forage is optimally utilized, avoiding losses in total biomass due to senescence and decomposition(9). Average nutrient concentrations in the fertilization treatment were 1.06 % for N, 0.20 % for P and 2.35 % for K, whereas in the control they were 0.79 % for N, 0.21% for P and 2.30 % for K (P>0.05). Of note is that the greater availability of nutrients in the soil due to fertilization continued for a longer time which resulted in higher accumulated DM. The growth rate (Îź in Equation 2) was also higher in the fertilization treatment, translating into higher yields per units of time and space, a phenomenon reported in other crops and forages with higher protein levels than Pennisetum sp.(5,28,29). However, maximum production did not coincide with the highest forage nutritional values. Rectifying this mismatch requires monitoring on the part of maralfalfa producers to determine at what point between 30 and 56 d to harvest the grass to attain both the best possible quality grass and maximum production. This is vital to producing the most nutritious possible livestock feed since N content decreases in maralfalfa even over 30 d(29,30). Phosphorus and potassium levels behave in the same way, and these gradual decreases in chemical composition slowly reduce nutritional quality(29,30).

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Maximum nutrient extraction levels in the control were 30 kg ha-1 at 107 d for N, 10 kg ha-1 at 110 d for P, and 110 kg ha-1 at 120 d (Fig. 2a). Levels were substantially higher in the fertilization treatment with 68 kg ha-1 at 98 d for N, 17 kg ha-1 at 115 d P, and 208 kg ha-1 at 116 d K (Figure 2b). Unitary extraction (UE) did not differ between the treatment and the control. In the control (5,952 t DM ha-1) average total UE was 27.49 kg N, 10.05 kg P, and 116.0 kg K over 168 d. In the fertilization treatment estimated UE per ton DM was 4.72 kg N, 1.29 kg P, and 15.90 kg K. Average total extraction for the treatment (10,414 t DM ha-1) was 49.15 kg N, 13.43 kg P and 165.58 kg K over 161 d. Nutrient recovery efficiency (NRE) values were 48 % for N, 39 % for P and 104% for K. These indicate the amount of each nutrient required by the maralfalfa grass during the study period. Using the cumulative production of 58,205 t ha-1 at 161 d for the treatment, and applying the approach of Volke et al(31) for fertilized forage crops, the calculations for the recommended fertilization levels for the next cycle would be 45-09-48 kg ha-1 (NPK).

Figure 2: NPK extraction curves (quadratic model) for maralfalfa ecotype grass (Pennisetum sp.) during rainy season for fertilization treatment (a) and control (b) Nitrogen Nitrogen Phosphorous Potassium 250

Phosphorous Potassium

100

200

150

kg ha-1

y = -0.0055x2 + 1.3199x + 30.683 R² = 0.959

120

y = -0.013x2 + 3.0282x + 32.615 R² = 0.9769

y = -0.0047x2 + 0.9192x + 22.554 R² = 0.9352

100

60 y = -0.0009x2 + 0.1928x + 19.46 R² = 0.897

50 y = -0.0011x2 + 0.2527x + 2.7894 R² = 0.9615

0 0

100 150 Time (Days) (a)

y = -0.0005x2 + 0.1103x + 3.5176 R² = 0.9419

200

100 Time (Days) (b)

150

200

Excess soil N and K contents caused by fertilization is known to decrease the NRE of these nutrients(32,33). This may lead to loss of N, consequent soil contamination, and excess K uptake(33), a common situation faced by forage producers. Fertilization dose therefore needs to be adjusted based on a nutritional balance between crop nutrient demand, soil nutrient supply and nutrient recovery efficiency(31). In the present study fertilization directly affected

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DM production and forage NPK content, although NRE was lower for N and P, suggesting that the fertilization dose utilized exceeded the required supply of these nutrients. Under the studied local climatic conditions (rainy season) the maralfalfa ecotype took advantage of the nutrient supply provided by fertilization, doubling its growth rate in the first 60 d. Considering this behavior and with the goal of attaining the best quality forage, the first harvest would best be done before 56 d, when maralfalfa grass reaches its maximum growth rate. If a higher NPK concentration is desired in the harvested forage the harvest should be done at between 30- and 35-days’ regrowth in successive harvests. The observed forage NPK levels suggest that fertilizer dose should be adjusted downwards in the following production cycle. Understanding the productive behavior of maralfalfa grass in terms of nutrient extraction would facilitate more accurate fertilizer management, increase crop nutrient recovery efficiency and determine the most opportune moment for fertilization; all these measures could help to reduce potentially polluting nutrient surpluses, particularly of N.

Literature cited: 1. Ramírez JL, Herrera RS, Leonard I, Cisneros M, Vardecia D, Álvarez Y. Relación entre factores climáticos, rendimiento y calidad de Pennisetum purpureum vc. Cuba CT 169 en el Valle del Cauto, Cuba. Rev Cubana Cien Agríc 2011;45(3):293-297. 2. Ortiz EE, Rodríguez JC, Russo RO. Efecto de fertilización y frecuencia de corte en rendimiento de biomasa de dos variedades del pasto king grass (Pennisetum purpureum). Tierra Tropical 2010;(6):43-53. 3. Steinfeld H, Gerber P, Wassenaar T, Castel V, Rosales M, De-Haan C (2009). La larga sombra del ganado: problemas ambientales y opciones. FAO. Roma.http://www.fao.org/3/a-a0701s.pdf. Consultado 7 Sep, 2017. 4. Márquez F, Sánchez J, Urbano D, Dávila C. Evaluación de la frecuencia de corte y tipos de fertilización sobre tres genotipos de pasto elefante (Pennisetum purpureum). 1. Rendimiento y contenido de proteína. Zootec Trop 2007;25(4): 253-259. 5. Rodríguez L, Larduet R, Martínez RO, Torres V, Herrera M, Medina Y, Noda AC. Modelación de la dinámica de acumulación de biomasa en Pennisetum purpureum vc. king grass en el occidente de Cuba. Rev Cubana Cien Agríc 2013;47(2):119-124. 6. Valenciaga D, Chongo B, Herrera RS, Torres V, Oramas A, Cairo JG, Herrera M. Efecto de la edad de rebrote en la composición química de Pennisetum purpureum vc. Cuba CT-115. Rev Cubana Cienc Agríc 2009;43(1)73-79. 262

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7. Calzada-Marín JM, Enríquez-Quiroz JF, Hernández-Garay A, Ortega-Jiménez E, Mendoza-Pedroza SI. Análisis de crecimiento del pasto Maralfalfa (Pennisetum sp.) en clima cálido subhúmedo. Rev Mex Cienc Pecu 2014;5(2):247-260. 8. Wagner B, Colón R. Comportamiento forrajero de tres Pennisetum purpureum Schumach. Revista APF 2014;3(1): 61-66. 9. De Caram GA, Angeloni P, Prause J. Determinación de la curva de dilución de nitrógeno en diferentes fases fenológicas del girasol. Agric Téc (Chile) 2007;67(2):189-195. 10. Colabelli MR, Agnusdei MG, Durand JL. Grupos funcionales de plantas, producción de forraje y eficiencia de uso de radiación de pastizales naturales en condiciones potenciales y limitadas de agua y nitrógeno. RIA (Argentina) 2011;(37):62-74. 11. INEGI (Instituto Nacional de Estadística y Geografía). Catálogo de claves de entidades federativas, municipios y localidades. 2009. http://mapserver. inegi. org. mx/mgn2k/?s=geo&c=1223. Consultado 23 Jun, 2016. 12. Vidal ZR. Las Regiones Climáticas de México. Colección: Temas Selectos de Geografía de México. UNAM. México. 2005. 13.

CIR Golfo Centro/INIFAP/SAGARPA. Campo experimental “La Posta”. Caracterización y resultados de análisis de suelo en el Laboratorio de Suelos. Paso del Toro, Veracruz. 2011.

14. Ramos-Trejo OS, Victoria-Graniel CA, Sandoval-Gío JJ. Temporada, fertilización y rendimiento de variedades de Pennisetum purpureum. Agrociencia 2014;49(8):837-844. 15. AOAC. Official methods of analysis. Association of Official Analytical Chemists. 15th. ed, Washington DC, USA. 1980. 16. Raji AO, Alade NK, Duwa H. Estimation of model parameters of the japanese quail growth curve using Gompertz model. Arch Zootec 2014;63(243):429-435. 17. García- Cardozo CR, Martínez RO, Tuero R, Cruz AM, Estanquero L, Noda, AC, et al. Evaluación de Panicum maximum vc, Mombaza y modelación de indicadores agronómicos durante tres años en un suelo ferralítico rojo típico de la provincia la Habana. Rev Cubana Cien Agríc 2009;43(3):297-306. 18. Casas AG, Rodríguez D, Afanador TG. Propiedades matemáticas del modelo Gompertz y su aplicación al crecimiento de los cerdos. Rev Colomb Cienc Pecu 2010;(23):349358.

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19. Rodríguez-Fuentes H, Rodriguez-Absi J. Métodos de análisis de suelo y plantas. México: Editorial Trillas SA de CV; 2011. 20. Juárez-Hernández J, Bolaños-Aguilar ED. Las curvas de dilución de la proteína como alternativa para la evaluación de pastos tropicales. Uciencia 2007;23(1):81-90. 21. Castro-Luna I, Gavi-Reyes F, Peña-Cabriales JJ, Núñez-Escobar R, Etchevers-Barra JD. Eficiencia de recuperación de N y K de tres fertilizantes de lenta liberación. Terra Latinoamericana 2006;24(2): 77-282. 22. Mora-Ravelo SG, Gavi-Reyes F, Tijerina-Chávez L, Pérez-Moreno J, Peña-Cabriales JJ. Evaluación de la recuperación del nitrógeno y fósforo de diferentes fuentes de fertilizantes por el cultivo de trigo irrigado con aguas residuales y de pozo. Acta Agronómica 2014;63(1):25-30. 23. Martínez RO, Tuero R, Torres V, Herrera RS. Modelos de acumulación de biomasa y calidad en las variedades de hierba elefante, Cuba CT-169, OM-22 y King Grass durante la estación lluviosa en el occidente de Cuba. Rev Cubana Cien Agríc 2010;44(2):189194. 24. Phaechamud T, Thongpin C, Choncheewa C. Shellac Wax-Lutrol F127 as Matrix Base for Hot Melt Extrusion. Res J Pharm Biol Chem Sci 2012;3(4):687-694. https://www.rjpbcs.com/pdf/2012_3(4)/[74].pdf 25. Steel RGD, Torrie JH. Bioestadística: principios y procedimientos. 2ª ed en español. Editorial McGraw-Hill México ;1996. 26. Rodríguez L, Torres V, Martínez RO, Jay O, Noda AC, Herrera M. Modelos para estimar la dinámica de crecimiento de Pennisetum purpureum vc. Cuba CT-169. Rev Cubana Cien Agríc 2011;45(4):349-354. 27. Escudero A, Mediavilla S. Dinámica interna de los nutrientes. Ecosistemas 2003;(1):1-8. 28. Crespo G, Álvarez J. Comparación de la producción de biomasa de clones de Pennisetum purpureum fertilizados con nitrógeno. Rev Cubana Cien Agríc 2014;(3):287-291. 29. Cerdas-Ramírez R. Comportamiento productivo del pasto Maralfalfa (Pennisetum sp.) con varias dosis de fertilización nitrogenada. InterSedes 2015;16(33):124-145. 30. Uvidia H, Ramírez J, Vargas J, Leonard I, Sucoshañay J. Rendimiento y calidad del Pennisetum purpureum vc Maralfalfa en la Amazonía ecuatoriana. Red Vet 2015;16(6)1-11.

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31. Volke HV, Etchevers BJD, San Juan RA, Silva PT. Modelo de balance nutrimental para la generación de recomendaciones de fertilización para cultivos. Terra Latinoamericana 1998;16(1):79-91. 32. Cabalceta G, Saldias M, Alvarado A. Absorción de nutrimentos en el cultivar de papa MNF-80. Agronomía Costarricense 2005;29(3):107-123 33. Puentes-Páramo Y, Menjivar-Flores J, Aranzazu-Hernández F. Eficiencias en el uso de nitrógeno, fósforo y potasio en clones de cacao (Theobroma cacao L.). Bioagro 2014;26(2):99-106.

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https://doi.org/10.22319/rmcp.v11i1.4829 Technical note

In vitro ruminal degradation of carbohydrate fractions in tropical grasses fertilized with nitrogen

Erika Andrea Hernández a Francisco Indalecio Juárez Lagunes a* Alice N. Pell b Maribel Montero Lagunes c Juan Manuel Pinos Rodríguez a Robert W. Blake b

Universidad Veracruzana. Facultad de Medicina Veterinaria y Zootecnia. 91710 Veracruz, Ver. México. b

Cornell University. Department of Animal Science. Ithaca, NY. USA.

INIFAP. Campo Experimental La Posta. 94277. Medellín, Ver. México.

*Corresponding author: juarezf@hotmail.com

Abstract: The goal was to determine the digestion rates of carbohydrate fractions A (sugars, oligosaccharides and organic acids), B1 (starch and soluble fiber), NSC (non-structural carbohydrates) and B2 (available NDF) in four tropical grasses using the gas production technique. Samples of whole forage (WF), residue insoluble in 90% ethanol (EIR) and isolated NDF (iNDF) were fermented in vitro and gas production measured. Gas volumes were determined from the following fractions, A = WF minus EIR; B1 = EIR - ND; NSC = WF iNDF; and B2 = iNDF. Grasses were Andropogon gayanus, Urochloa brizantha, Cynodon plectostachyus, and Megathyrsus maximus each grown in Veracruz, Mexico on four plots (5×5 m), fertilized (relationship equivalent to 0 and 100 kg N/ha) and clipped 35 d after the N 266

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fertilization. A complete randomized block design with factorial arrangement 4Ă&#x2014;2 and two replicates per treatment was used. Factors were grass species and N fertilization. Data were fit using a single-pool exponential model with lag. The volume (mL gas/100 mg OM), rate (%/h) and lag (h) were: WF (22.8; 5.3; 2.1); A (3.2; 15.7; 0.5); B1 (1.5; 15.7; 0.2); and B2 (18.3; 6.6; 5.2). Andropogon and Urochloa had higher NSC content compared to Megathyrsus and Cynodon but lower gas yield per unit of NSC. Rates of digestion for the B2 fraction ranged from 4 to 8 %/h; and NSC digestion rate averaged 15.7 %/h. Nitrogen fertilization reduced carbohydrate pool sizes but did not affect rates of digestion. It is concluded that the rates of digestion of the carbohydrate fractions differs by grass specie. Key words: C4 grasses, Carbohydrate fractions, Digestion rates, Gas production, CNCPS model.

Received: 29/03/2018 Accepted: 13/11/2018

The energy content of forages that is available to the animal cannot be determined using standard analytical techniques. Therefore, other means are needed to estimate it. Past use of empirical prediction equations based on chemical composition, aided by detergent system analysis of fiber(1) has been in the foundation for a comprehensive system of forage evaluation(2). However, the underlying relationship between energy content and chemical composition is inconsistent in tropical forages with high contents of lignin, silica, tannins and other secondary compounds, which may interfere with digestion.

An alternative approach uses the In vitro ruminal digestion method(3). This technique is commonly used to predict the digestibility of a feedstuff. However, measuring the extent of digestion by substrate disappearance has limitations: The soluble components are assumed to be completely digested and with similar energy values regardless of their carbohydrate or organic acid profiles(1). The Cornell Net Carbohydrate and Protein System model (CNCPS) v.5 http://blogs.cornell.edu/cncps/ fractionates carbohydrates into three major fractions: fraction A (sugars, oligosaccharides and organic acids), fraction B1 (starch and soluble fiber), and fraction B2 (digestible structural carbohydrates)(4,5). The CNCPS further partitions carbohydrates into eight digestible fractions(6): A1 (volatile fatty acids); A2 (lactic acid); A3 (other organic acids); A4 (sugars); B1 (starch); B2 (soluble fiber); B3 (available NDF); C (unavailable NDF). However, the CNCPS v6.5.5(7) http://blogs.cornell.edu/cncps/ model considers information only about the digestion rates of four fractions, A4, B1, B2 and B3. In this model (version 6.5.5), the rate of digestion assigned to the A4 fraction (40 to 60 %/h) was 267

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obtained from data based on mixed ruminal microbes(8,9) using the gas production technique(10). This technique has been automated and used to estimate the digestion of the NDF(11) and non-structural carbohydrates (NSC)(12). Accordingly, fractions B1 and B2 have rates of 20 to 40 %/h and the B3 fraction rate varies between 1 and 18 %/h.

The feed library of the Nutrient Requirements of Beef Cattle(13) (https://www.nap.edu/download/19014) does not include tropical grasses. However, the Large Ruminant Nutrition System (LRNS) v1.033(14) (http://nutritionmodels.com/lrns.html) includes rates of digestion of carbohydrate fractions A, B1 and B2 for tropical grasses. In this library grasses from Mexico(15) are differentiated from Brazil, Honduras and Florida. The updated tropical library of the CNCPS v.6.5.5(7) validates the database from Mexico and correct the rates from Brazil, Honduras and Florida by assigning fixed values (%/h) of 40 for the A4; 30 for B1; 30 for B2; and 3.0 for B3 carbohydrate fractions. These last values are in agreement with previous reports(16-19). However, more research is needed to update these rates.

Therefore, the objective of the present study was to chemically quantifying the carbohydrate fractions, A, B1, B2 and C, and to measure the digestion kinetics of each of these fractions by measuring gas production in four tropical grasses fertilized with nitrogen.

The study was conducted at La Posta Experimental Station of Mexico’s Instituto Nacional de Investigaciones Forestales Agrícolas y Pecuarias (INIFAP). This research station is located on the southeastern coast of Mexico in the State of Veracruz at 19° 02' N and 96° 08' W, with an altitude of 12 m asl, a tropical subhumid Aw climate, with average annual rainfall of 1,728 mm, 25° C of average temperature and 81 % relative humidity. The soil is classified as Oxisol, a predominantly sandy loam with >15 % clay and 1.7 % organic matter, the pH was 5.35. The soil chemical analysis report showed the follow mineral content (ppm): P2O5, 12; K, 108; Mg, 115; Ca, 545; NO3, 9.5; S, 16; Mn, 13; Fe, 53; Cu, 0.45; and B, 0.6.

The selected grasses Andropogon gayanus, Urochloa brizantha, Cynodon plectostachyus, and Megathyrsus maximum Var. Guinea, are commonly used species. At the onset of the rainy season, each grass was grown in four plots (5×5 m). Two plots were none fertilized, and the others were fertilized with N from urea (relationship equivalent to 100 kg N/ha). This dose is representative of that local livestock producers use. All plots were previously cut to a height of 5 cm. There were two sampling periods (June 20 and July 25). After 35 d of regrowth, one sample of 2 m2 from the center of each plot was clipped at a height of 10 cm. Samples were taken between 0700 to 0900 h. A sub-sample of 500 g of green material was immediately frozen at -15 °C, and another was placed in a forced air oven at 100 °C for 24 h to determine DM content and discarded. At the end of the sampling period (July 25), four frozen samples 268

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from each grass were lyophilized, placed in 30×25 cm heavy-duty freezer bags, and sent to Cornell University (USA) for chemical analysis.

All samples were ground through a 1-mm screen in a Wiley mill (Model 4, Arthur H. Thomas Co. Philadelphia, PA). Dry matter for correction was determined by direct oven-drying of samples at 100° C overnight. Crude protein (N×6.25) was determined by a Macrokjeldahl procedure(20), modified using Boric acid at 4% concentration during distillation. Neutral detergent fiber (NDF) (without sodium sulfite), acid detergent fiber (ADF), nonstructural carbohydrates (NSC), neutral detergent insoluble protein (NDIP), and acid detergent insoluble protein (ADIP) were determined(21). Permanganate lignin, cellulose and acid insoluble ash were also determined(22). Hemicellulose was calculated as the difference of NDF minus ADF with appropriate correction for contents of ash and crude protein. Sugar content was determined by ethanol extraction (EIR)(23).

Total carbohydrates and its fractions (NSC, A, B1, B2, and C) were estimated as follows: Total carbohydrates= 100 - CP - ash - fat. C fraction= lignin/NDF * 2.4. B2 fraction= (NDF/OM) - NDIP - C fraction. A fraction= (DM - CP - ash) - (ethanol insoluble residue – CP in ethanol insoluble residue – ash in ethanol insoluble residue). NSC = 100 - CP - (NDF - NDIP) - ash - fat. B1 fraction = NDS - A.

The digestion kinetics of carbohydrate fractions were estimated from gas production measurements(11) using the curve subtraction procedure(12). To achieve this, the whole forage, ethanol insoluble residue (EIR) and the isolated NDF were fermented separately. For EIR(23) five hundred milligrams of sample in 100 mL of 90% vol/vol ethanol were stirred for 4 h. The sample was filtered through a 37-µ nylon mesh (Tetko®, Briarcliff Manor, NY) and thrice rinsed with 90% ethanol without vacuum and once with acetone under vacuum. The sample then was dried at 50 °C overnight to remove residual acetone.

For the isolated NDF(11) five hundred milligrams of sample and 100 mL of ND solution in 150-mL serum bottles were autoclaved for 1 h at 105 °C. This NDF isolate was rinsed with hot water and 100 mL of ethanol, and filtered through a 37-µ nylon mesh. Residual detergent was removed by soaking the isolate overnight at 39 °C in a solution of 1 M (NH4)2SO4 (1 g NDF to 269

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100 mL 1 M (NH4)2SO4). The isolate was again rinsed with hot water followed by 100 mL each of ethanol and acetone and air dried.

For the in vitro digestion(22) the medium was boiled to remove dissolved gases and cooled, cysteine added, and pH adjusted to 6.8 as necessary. Sodium sulfide was replaced by an equal weight of cysteine hydrochloride to protect the pressure sensors used to monitor gas volume from traces of hydrogen sulfide. Ruminal fluid was collected approximately 4 h after feeding from two out of four mature, non-lactating, Holstein cows housed in the LARTU (Large Animal Research and Teaching Unit at Cornell University) and maintained on Timothy (Phleum pratense) hay Full Bloom (CP, 8%; FDN, 65%) similar quality than grasses of this study, in accordance with the Institutional Animal Care and Use Committee (IACUC) protocol.

At the outset of a fermentation, each 120 mL serum bottle contained 8 mL medium, 2 mL ruminal fluid, and 100 mg of either whole forage, EIR, or isolated NDF. Gas production was measured every 20 min during a 48 h fermentation using a computerized monitoring system(11,12). The disappearance of NDF was determined at the end of each fermentation(11). All gas volumes were corrected to standard atmospheric pressure (760 mm Hg).

The estimation of digestion rates for the A, B1, B2, and NSC fractions by curve subtraction requires that the gas volume produced by the separate preparations (EIR and NDF) be adjusted to a common basis proportional to the content of each fraction within the whole forage(8). Therefore, the gas volume produced was adjusted proportionally to the OM content of the whole forage.

Gas production during fermentation was recorded every 20 min for 48 h. On a point by point basis, data from the curve were subtracted from the gas produced by the larger fraction (8,24). The gas from the A fraction was estimated by the difference between the gas yields from the whole forage sample and its EIR preparation. The B1 fraction was estimated by the difference between the EIR preparation and the isolated NDF. The B2 fraction is the gas produced from the fermentation of isolated NDF, and the NSC is the difference between the whole forage and its isolated NDF.

Kinetic analyses of cumulative gas production were obtained using a single pool exponential model with lag(25), Y=a*(1-exp(-b*(x-c))), where Y=volume of gas mL/100 mg OM at time x; a=maximum volume of gas, mL; b=rate constant of gas production, %/h; c=lag term, h. The gas curves obtained by subtraction for the A, B1, and NSC fractions reached their asymptotes 270

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between 12 and 24 h, indicating that these fractions had been depleted(12). Afterwards changes in gas volume are related to microbial turnover, and potential non-additivity of the curve subtraction approach(26,27). For this reason, the gas curves for the A, B1 and NDS fractions were truncated for curve fitting after they plateaued(8). All curves were fitted using the Table Curve (version 4.0, Jandel Scientific, San Rafael, CA).

A complete randomized block design with factorial arrangement and two replicates per treatment was used, where the factors were grass species and N fertilization. A laboratory standard of Guinea grass (M. maximum) was used to control for ruminal fluid variation among in vitro analyses. A 4Ă&#x2014;2 factorial arrangement of forage species (A. gayanus, U. brizantha, C. plectostachyus, or M. maximum Var. guinea) and N fertilization (0 and 100 Kg/ha) as factors was used. Planned comparisons among the forages were evaluated using Tukey's W procedure. Results were deemed significant at Pâ&#x2030;¤0.05 for the effects of grass species and fertilization. The ANOVA analyses were performed using the MINITAB, Version 10 (Minitab Inc., State College, PA)(28). Because there were no interactions (grass*N fertilization) of the 4Ă&#x2014;2 factorial arrangement of treatments, only means of mean factors (grass or N fertilization) are shown in Tables 2 and 3.

Chemical composition by grass species and amount of N fertilization are presented in Table 1. Under the same conditions of management and environmental growing conditions, the chemical composition of the grasses differed by species. Urochloa contained less NDF, neutral detergent insoluble protein (NDIP) and lignin than the other grasses. Andropogon had high NDIP and NSC levels. Megathyrsus, however, was distinguished for its high content of ash and acid insoluble ashes (AIA), and its low content (7.2 %) of CP. These values mirrored those found in the same similar-age species with climate Aw0 in Guerrero, Mexico(29). Cynodon had high NDF and low NSC contents. Grasses varied in their distributions of chemical constituents, which reflects differences in morphology and physiology. Previous reports have indicated variations in the chemical composition of tropical grasses due to species(30), season of year(31) and plant age(32,33). Across these studies high amounts of ash in Megathyrsus, low lignin in Urochloa and low amounts of crude protein in Cynodon were consistently observed. The chemical constituent findings are consistent with other reports for Cynodon(34), Megathyrsus(35), Urochloa(36) and Andropogon(29), suggesting potential inherent growth differences in their plant tissues(33).

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Table 1: Chemical composition (g/100g DM) of four tropical grasses fertilized with Nitrogen A. U. C. gayanus brizantha plectostachyus Ash 8.2c 9.6b 9.5b EE 2.0b 2.4a 1.3c CP 9.1a 9.0a 8.3ab NDF 69.8b 66.4c 74.9a a c NDIP 4.4 1.2 3.1ab ADF 41.0a 36.5b 41.2a ADIP 0.6b 0.3c 0.8a AIA 4.3ab 3.1c 3.3bc Cel 32.2a 29.7b 32.3a Hem 28.2b 31.3a 33.1a NSC 16.5a 14.7ab 10.7c Lig 4.4b 3.7c 5.6a ETOH 87.2ab 85.5b 89.1a

M. maximus

SEM

Non fertilized Fertilized SEM

11.3a 2.6a 7.2b 69.1bc 2.9b 42.3a 0.6b 5.0a 33.0a 28.3b 14.0b 4.3bc 87.9a

0.12 0.05 0.12 0.36 0.14 0.18 0.02 0.13 0.09 0.22 0.22 0.06 0.22

8.3b 1.6b 5.9b 72.6a 2.2b 40.3a 0.5b 3.5a 32.4a 33.1a 14.6a 4.5a 87.3a

10.9a 2.5a 10.9a 67.5b 3.6a 40.2a 0.7a 4.4a 31.2b 27.3b 13.3b 4.5a 87.5a

0.06 0.03 0.06 0.18 0.07 0.09 0.01 0.06 0.05 0.11 0.11 0.03 0.11

EE= ether extract; CP= crude protein; NDF= neutral detergent fiber; NDIP= neutral detergent insoluble protein; ADF= acid detergent fiber; ADIP= acid detergent insoluble protein; AIA= ash insoluble in acid; Cel= cellulose; Hem= hemicellulose; NSC= nonstructural carbohydrates; Lig= lignin; ETOH= residue insoluble in ethanol 90%. a,b,c Means with different superscript differ (Pâ&#x2030;¤0.05) for the grass effect or for the fertilization effect.

Fertilization with N modified the amount and distribution pattern of the nutrients in these plants (Table 1). Protein contents were increased in both the cell wall and cell soluble fractions. Because amino acids and proteins in plants are synthesized from sugars(37), an increase in N supply depresses the sugar content (less NSC). Fertilization also reduces the NDF content with most of this decrease occurring in hemicellulose, most of which is deposited in the secondary wall as plants mature. An increase in CP and reduction of NDF has also been found in Urochloa ruziziensis fertilized with 120 kg/N/ha and harvested at 30 d of regrowth(36).

Chemical constituents of the plant cell have been used to mathematically predict the feedstuff energy available to the animal(37,38). An alternative approach is to integrate digestion and passage rates using the relationship among different energy pools, kd=kd/(kd+kp), where Kd is rate of digestion and Kp is rate of passage. The estimated carbohydrate pools of the grasses in our study are in Table 2. The total carbohydrate content ranged from 77.8 to 80.4 % OM. The digestible NDF content (B2 fraction) ranged from 47.8 to 51.2 % on an OM basis with Andropogon containing the least and Cynodon the most. Conversely, the NSC content was greatest in Andropogon (17.4 % OM) and least in Cynodon (10.7 % OM). The C fraction (Lignin/NDF*2.4), which is assumed indigestible, ranged from 13.5 to 18.0 % with the largest 272

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amount found in Cynodon and the least in Urochloa. As a proportion of NSC, the A fraction (sugars, organic acids and short chain polysaccharides) constituted 68% of the total with the B1 fraction (starch and soluble fiber) made up the remainder. While the B1 fraction in tropical forages contains the smallest pool of carbohydrates (mostly as starch), it nonetheless represents about one-third (30 %) of NSC. The carbohydrate pools in this study are in agreement with the values shown in the LRNS and CNCPS feed libraries. Grasses elsewhere of the same species have been found that the B1 is the smallest CHO fraction and that is made of starch mainly(39). The NSC is a complex fraction where the starch is part of the non-fiber carbohydrates (NFC) and the pectin substances are part of the structural carbohydrates unaccounted in the B2 fraction.

Table 2: Carbohydrate fractions (g/100g OM) of four tropical grasses fertilized with Nitrogen

CHO A B1 NSC B2 C

A. gayanus

U. brizantha

C. Plectostachyus

M. maximus

SEM

Non fertilized

Fertilized

SEM

80.4a 10.6a 6.8a 17.4a 47.8b 15.2b

79.7a 10.8a 4.7ab 15.5ab 50.6ab 13.5b

79.9a 7.9b 2.7b 10.7c 51.2a 18.0a

77.8b 9.6ab 4.0b 13.6b 49.4ab 14.8b

0.12 0.19 0.26 0.24 0.32 0.20

83.7a 10.5a 4.5a 15.0a 53.9a 14.8b

75.2b 9.0b 4.6a 13.6b 45.6b 16.0a

0.06 0.10 0.13 0.12 0.16 0.10

CHO= total carbohydrate content, % OM=100-CP-ash-fat; A= (dry matter corrected for CP and Ash) - (residue remaining after extraction with 90% ethanol corrected for CP and ash); B 1=NSC-A; NSC=Non-structural carbohydrates=100-Crude protein-(NDF-NDIP)-fat-ash; B2=NDF on organic matter basis minus NDIP minus the C fraction; C =Lignin/NDF*2.4. a,b,c Class means with different superscript differ (P<0.05) for grass effect or for fertilizer effect.

Nitrogen fertilization had a dual negative impact on carbohydrate pools (Table 2). First, the total plant carbohydrate was reduced due to a smaller A pool. An increase in the N fractions requires a corresponding depression in non-nitrogen components, especially sugars(37). Second, the B2 pool was reduced by 15.4 %. At different levels of N fertilization the same effect on NDF it has been demonstrated(36). The positive effect of N fertilization in reducing the NDF content is offset by a negative effect in increasing lignification. The net result is a reduction in the availability of the B2 fraction and an increase in the indigestible (C) fraction. The overall effect on the plant is a reduction in the available total carbohydrates. This may be why there are no improvements in IVDMD with N fertilization(36). CNCPS predictions(15) found that the lower NDF in nitrogen fertilized tropical grasses was offset by higher CP and ash, which lowered the content of NSC. As a result, nitrogen fertilization did not significantly change the ME allowable milk. However, it improved the MP allowable milk dramatically. Because N fertilization increased both the CP and soluble protein content of the grasses, both 273

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the ruminal N balance and the peptide balance increased. Juarez-Lagunes et al(19) concluded that N fertilization could be expected to improve MP allowable milk, primarily because of increased pool sizes of CP and soluble protein.

Another challenge is to establish a connection between carbohydrate pools, energy yield from rumen fermentation and gas production. Gas production is not only affected by the amount of carbohydrates in a given pool, but it is also by their availability. Ranges from 27 to 30 mL of gas per 100mg of OM where found in whole forages in this study. Similar gas production was observed in 24 tropical grass species in Ethiopia(40). Cynodon produced less gas than Megathyrsus (Table 3) because Cynodon contains a larger C fraction than Megathyrsus (Table 2). A large C fraction indicates low availability of the cell wall. However, the C fraction does not explain the low availability of NSC. It is generally assumed that the NSC fraction is highly digestible(37). Because Andropogon has more total carbohydrates with the same C fraction size as Megathyrsus (Table 2), Andropogon should be expected to yield more gas than Megathyrsus. However, gas yields were similar (Table 3). Something may interfere with gas production from Andropogon.

Volumes of gas produced by the NSC also are shown in Table 3. Andropogon and Urochloa contain more NSC than Cynodon and Megathyrsus (Table 2), but they produce the same volume of gas from the NSC fraction. Moreover, the amount of gas per 100 mg of NSC is reduced suggesting that fermentations of the NSC of Andropogon and Urochloa were inhibited. Based on the subtraction technique, the fermentability of the A fraction of Urochloa and the B1 fraction of Andropogon seemingly were affected. We suspect that tannin-like substances (TLS)(41) or other secondary compounds interfere in the fermentability of NSC. During the preparation of the isolated NDF; tannins, biogenic silica or other secondary compounds are washed out, so the fermentability of the isolated NDF would be affected only by lignin content.

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Table 3: Gas production and digestion rates of four tropical grasses fertilized with Nitrogen A. Gayanus

Total carbohydrates Total gas, mL Gas, mL/100 mg OM Degradation rate, %/h Lag phase, h B2 fraction Total gas, mL Gas, mL/100 mg OM Degradation rate, %/h Lag phase, h NSC fraction Total gas, mL Gas, mL/100 mg OM Degradation rate, %/h Lag phase, h A fraction1 Total gas, mL Gas, mL/100 mg OM B1 fraction1 Total gas, mL Gas, mL/100 mg OM

U. Brizantha

C. Plectostachyus

M. Maximus

SEM

Non fertilized

Fertilized

SEM

23.7a 29.5ab

23.0a 28.9b

21.6b 27.1c

23.6a 30.3a

0.11 0.15

24.0a 28.7a

21.9b 29.2a

0.05 0.07

5.1ab

5.2ab

4.8b

6.0a

0.10

4.9b

5.7a

0.05

2.2b

2.4b

1.0c

3.0a

0.06

2.1a

2.2a

0.03

19.4a 40.9a

18.6ab 36.9ab

17.5c 34.0b

18.4ab 37.3ab

0 .14 0.43

19.2a 35.3b

17.8b 39.2a

0.07 0.21

7.3ab

8.4a

3.8c

6.8b

0.16

6.5a

6.6a

0.08

4.5b

5.2b

4.6b

6.7a

0.14

5.2a

5.3a

0.07

4.3b 24.5b

4.4b 28.1b

4.1b 38.6a

5.2a 38.6a

0.08 0.90

4.8a 34.1a

4.1b 30.8a

0.04 0.45

13.8b

27.4a

13.2b

8.6b

0.77

17.5a

14.0a

0.38

1.2a

0.5a

0.1b

0.6a

0.11

0.3a

0.8a

0.05

3.3a 31.7b

2.0b 18.2c

3.4a 42.6a

3.2a 33.4b

0.08 0.72

3.2a 32.0a

2.7b 31.0a

0.04 0.36

0.9b 13.8b

2.4a 54.7a

0.7b 24.4ab

2.0a 51.4a

0.09 3.44

1.6a 39.8a

1.4a 32.3a

0.05 1.72

Total carbohydrates= 100 - CP - Ash - Fat. B2 fraction= digestible structural carbohydrates= NDF/OM - NDIP - C fraction. NSC fraction= non-structural carbohydrates= 100 - CP - (NDF - NDIP) - Ash - Fat. A fraction= sugars and short chain polysaccharides= (dry matter corrected for CP and Ash) - (residue remaining after extraction with 90% ethanol corrected for CP and Ash). B1 fraction= starch and soluble fiber= NSC - A. 1 Degradation rates (%/h) and Lag phases (h) for A fraction and B 1 fraction were similar to NSC fraction. a,b,c Means with different superscript differ (Pâ&#x2030;¤0.05) for the grass effect and for the fertilization effect.

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When it was applied curve subtraction to NSC (whole forage - isolated NDF) all potentially interfering substances (tannins, biogenic silica or secondary compounds) were accounted in the NSC fraction, thus reducing gas yield. In our case, digestibility of the isolated NDF was 6.6 % greater than for whole forage NDF. These differences were 6.9 % for Andropogon and Urochloa, and 6.2 % for Cynodon and Megathyrsus. As a result, it may have experienced some under-prediction of NSC gas production. Because the amounts of soluble silica were similar in Cynodon and Megathyrsus compared to Andropogon and Urochloa (see AIA in Table 1), it was assumed that the major source of variation in gas produced by the NSC fraction likely resulted from secondary compounds. In a botanical survey Megathyrsus did not contain TLS, which obtains maximum expression in A. gayanus(41). In the study Urochloa did not appear to contain condensed tannins, however it is suspect that there indeed may be other interfering substances. These findings support the suggestion that lignin content should be added to the equation to estimate total carbohydrates by the CNCPS model. Therefore, this modified CNCPS equation would become:

CHO (g/kg DM) = 1000 - [CP (g/kg DM) + EE (g/kg DM) + MM (g/kg DM) + Lignin (g/kg DM)]

The interference by phenols in the digestion of legumes and grasses merits more study for better management of ruminant nutrition in the tropics.

Nitrogen fertilization reduced the total amount of carbohydrates available for rumen fermentation (Table 2). The volume of gas produced was proportionally diminished with the amount of carbohydrate (Table 3). For instance, there was no difference in the amount of gas per 100 mg of substrate from unfertilized and fertilized forages. In the B2 fraction, fertilized forage (FE) produced less gas than unfertilized forage (NF) because FE contained less fermentable structural carbohydrates (SC). In this study of same-age forages, fertilized grasses contained less NDF and the same amount of lignin as a percentage of dry matter as unfertilized grasses (Table 1), as has been found by others(42,43). Therefore, there was more lignin as a percentage of the NDF. On the other hand, the difference in SC content between NF and FE was due primarily to hemicellulose. It is known that hemicellulose has more complex linkages with lignin than cellulose(37). Therefore, hemicellulose should be less available, increasingly so as the plant cell wall matures from more linkages between hemicellulose and lignin(33). NF grasses contained more hemicellulose and more mature cell walls than FE(44). The linkages between lignin and hemicellulose was reflected by the reduction in the amount of gas per 100 mg of SC from the NF grasses (Table 3). In summary, fertilized grasses produced 7.3 % less total gas from a smaller SC pool. However, this was compensated by 10 % more gas per unit of SC because they are less mature than NF grasses at 276

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the same age.

Rates of digestion are presented also in Table 3. The range of the digestion rates obtained by the exponential equation for the whole forage was from 4.8 to 6.0 %/h (r2=99.7 ± 0.12; tvalue=61.2 ± 12.04), which agrees with other reports(45). For isolated NDF, digestion rates ranged from 3.8 to 8.4 %/h (r2= 99.8 ± 0.11; t-value= 62.6 ± 14.07), values that were higher than in other reports(4,18,19) of 2 to 4 %/h for the B2 fraction, and aligned with NDF digestion rates between 5.16 and 9.34 for C4 grasses(46), and corn silages(47). Updated versions of nutrition models (CNCPS; LRNS; NRC) should incorporate these rates to more accurately estimate ruminally available energy from the SC in C4 grasses. In tropical grasses, the B2 fraction is the largest pool of carbohydrates, so the impact on the ME available to the animal could be significant. The ME allowable milk predicted by the CNCPS(15) was very sensitive to change in the rate of digestion of the B2 carbohydrate fraction. The ME allowable milk increased 88 % when the rate increased from 3 to 6%/h, and it increased an additional 24% when the rate increased from 6 to 9%/h. The predicted MP allowable milk increased from a – 0.8 to 5.7 kg/d as the B2 rate increased from 3 to 6%/h and increased to 9.9 kg/d with a B2 rate of 9%/h. These increases are the result of greater rumen degradation of SC.

In this study, because the B1 was less than 10 % of the total DM, it was combined the A and B1 rates and used the combined NSC rate for both fractions (Table 3). The rates for the NSC were highly variable, ranging from 8.6 %/h in Megathyrsus to 27.4 %/h in Urochloa (r2= 99.2 ± 0.52; t-values= 13.7 ± 6.83), with an overall mean of 15.7 %/h. These values are near the average (13.7 %/h) for bromegrass, orchardgrass, and alfalfa, where rates of digestion were 13.9 %/h for the A fraction and 11.8 %/h for the B1 fraction(8), also from Brazilian tropical grasses with rates of digestion for the NSC fraction between 6 and 12 %/h(48). The CNCPS tabular values of digestion rates for the A fraction are fixed 40 %/h and for the B1 fraction are 30 %/h in most tropical grasses. There is need for more research on the rates of digestion of carbohydrate pools in tropical grasses, and more frequent revision of tabular values for field use. Nitrogen fertilization did not have much apparent influence on rates of digestion (Table 3). These were apparently more affected by inherent plant physical structure. Chemical differentiation was more related to the extent of digestion and volume of gas produced(48). Tissue anatomy strongly affects degradation rates. Cell types with thickened secondary wall, such as vascular bundles, sclerenchyma strands, epidermis and parenchyma bundle sheath of C4 grass leaves form solid, multicellular blocks of cells that constitute a barrier to microbial access to wall surfaces(49). If all cells had only thin primary walls, (e.g., mesophyll, phloem and undifferentiated parenchyma tissues of leaves and young stems) then the cell wall would degrade rapidly.

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In summary, chemically Andropogon and Urochloa had more NSC compared with Megathyrsus and Cynodon but they produced less gas per unit of NSC. It is suspected interference from secondary compounds. The rates of digestion for the B2 fraction ranged from 4 to 8 %/h and the rate of digestion for the NSC averaged 15.7 %/h. Nitrogen fertilization had a negative impact on carbohydrate pool sizes but did not affect rates of digestion.

Digestion rates found in this study suggest that the CNCPS, LRNS and NRC should update more frequently the ruminally available energy from SC and NSC in tropical forages. The impact on the prediction of the ME available to the animal could be significantly improved.

Acknowledgements This work was funded by Cornell University Animal Science Department, USA.

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https://doi.org/10.22319/rmcp.v11i1.4684 Technical note

Frequency of SNPs located in candidate genes for growth and their effect on live weight variables in beef cattle from Tamaulipas

Ana María Sifuentes Rincón a* Gaspar Manuel Parra Bracamonte a Williams Arellano Vera a Pascuala Ambriz Morales a Antonio Cantú Covarrubias b Víctor Ricardo Moreno Medina a

Instituto Politécnico Nacional. Centro de Biotecnología Genómica. Laboratorio de Biotecnología Animal, Blvd. Del Maestro esq. Elías Piña. Col. Narciso Mendoza s/n. Cd. Reynosa, Tamaulipas, México. b

Instituto Nacional de Investigaciones Forestales Agrícolas y Pecuarias, INIFAP, Campo Experimental Las Huastecas. Tamaulipas, México.

*Corresponding author: asifuentes@ipn.mx

Abstract: A full understanding of how specific genes affect live weight variables is required for their incorporation into genetic improvement programs. An analysis was done of the allelic frequencies of 28 single nucleotide polymorphisms (SNP) located in candidate genes for growth in cattle to identify their effect on live weight traits in Charolais and Simmental herds in the state of Tamaulipas, Mexico. Hair samples were collected from 313 animals and genotyped using the Sequenom MassARRAY system. Genotype analysis showed that all the markers were polymorphic in the evaluated populations and their allelic frequencies were significantly different between the two breeds (P<0.05). An association analysis found that in the Charolais population the marker PRL + 2723 had a significant effect (P= 0.0350) on birth weight and the marker GHR-6.1 affected

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weaning weight (P= 0.0226). In the Simmental population GHR-6.1 was associated with yearling weight and the marker LEP-3100 (P=0.0249) had a significant effect on weaning weight. The tested 28 SNP panel is polymorphic in both breeds and three of the markers had a significant effect on the evaluated live weight parameters. They can therefore be potentially validated for use as tools in the selection and breeding of beef cattle in Tamaulipas. Key words: Beef cattle, Somatotropic axis, SNP association, Allelic frequencies, Live weight.

Received: 08/11/2017 Accepted:31/10/2018

In cattle production, economically important traits are determined by various polygenic factors. One of the largest current challenges in animal genetics is to determine these traitâ&#x20AC;&#x2122;s genetic architecture and thus incorporate genomic information into animal selection criteria(1). Both birth weight and weaning weight impact livestock production and are relatively easy to record. They have been among the most studied data in traditional livestock genetics, and are currently important in genomic approaches based on marker-assisted selection applications in cattle(2,3). Although many physiological processes regulate growth the somatotropic axis is the main regulator of development and growth in cattle(4,5). Somatotropin, or growth hormone (GH), is secreted by the pituitary gland, is a potent regulator of physiological functions and plays a central role in growth. Release of GH is stimulated by growth hormone releasing hormone (GHRH), and is inhibited by somatostatin. In young animals GH is secreted at high levels during growth, but in adults, secretion levels vary. The most common stimulus for secretion in adults is reduction of plasma glucose concentrations. Although GH is the main regulator of the somatotropic axis, it acts in conjunction with other hormones, receptors and binding proteins. It stimulates release of somatomedins or insulin-like growth factors 1 and 2 (IGF-1 and IGF-2), which exert a regulatory effect through negative feedback on the hypothalamus and adenohypophysis, and thus influence growth. Also secreted primarily by the pituitary gland, prolactin (PRL) is a polypeptide hormone that participates in multiple endocrine processes. However, it participates most frequently in lactation and reproduction in mammals through signaling pathways that involve the STAT5 transcription factors(6). Other hormones do not directly influence growth but do affect weight; for example, leptin (LEP) regulates food intake and energy balance(7).

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In cattle, the genes controlling the above peptides and hormones have been considered as candidates for productive traits. They have been widely characterized and in different breeds their polymorphisms have been associated with body weight(5,7,8), carcass weight(5,7,9), milk yield and fertility(10,11). In Charolais herds in Mexico, for instance, associations have been identified between some molecular markers located in these candidate genes(2,12,13). An important consideration is that the association patterns of these markers vary widely between breeds and even more so among populations. Evaluations are therefore needed before they can be employed in genetic selection and improvement programs. The present study objective was to estimate and compare the allelic frequencies of a panel of SNP type markers and quantify its effect on live weight characteristics in Charolais and Simmental breed cattle in the state of Tamaulipas. Mexico.

From 2014 to 2015 samples were collected from 313 animals in beef cattle herds in municipalities in Tamaulipas. A total of 199 samples were collected from Charolais cattle in four herds located in three municipalities: San Fernando (2), Gustavo DĂaz Ordaz (1) and Victoria (1). The sample consisted of 105 offspring born between 2012 and 2014 (55 females and 50 males), 77 dams and 17 sires. Verification of the filial relationship between offspring (n= 13) and the sampled dams and sires was only possible for one herd in San Fernando. Information on the filial relationship between offspring (n= 18) and three sampled sires in the DĂaz Ordaz herd was also available. The sample for the Simmental breed was 114 animals, consisting of 32 offspring, 70 dams and 12 sires from a single herd in the municipality of Aldama. All the evaluated sires and offspring were registered animals. For all five herds management and productive record data were available for birth weight (BW), weaning weight adjusted to 205d (WW) and yearling weight adjusted to 365d (YW). As a result, the data analyzed in the association analysis for each characteristic vary from those of the total studied sample. Based on the existing literature a panel was designed of 28 SNP located in candidate genes for animal growth and weight. Using hair samples collected from each of the 313 animals, genotyping was run using the Sequenom MassARRAY System following specifications from GeneSeek Inc. (Lincoln, NE, USA). Once the genotypes were obtained, the genotype and allele frequencies of the analyzed markers were estimated using the Allele Frequency Analysis module of the Cervus 3.0 program(14). An exact test for Hardy-Weinberg equilibrium was run under the alternative hypothesis of heterozygous deficit (P>0.05) using the Genepop ver. 4.0.10 program(15). In the genetic differentiation analysis, the null hypothesis tested was Ho = identical allelic distribution across populations. For the populations, the test was done using

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population pairs contingency tables and unbiased estimation of the P value or Fisher’s exact test for each locus(15). With the genotype and productive data (BW, WW, YW) for the Charolais and Simmental breeds an association analysis was run for each breed. To isolate all the nongenetic effects of the genotypes each breed’s linear model was adjusted as follows: Yijklm= µ + Si + Aj + Ek + Gl + Hm +βev + εijklm, Where: Yijklm= birth, weaning or yearling weight; µ= general mean; Si= fixed effect of i-th animal sex; Aj= fixed effect of j-th birth year; Ek = fixed effect of k-th birth season; Gl= fixed effect of l-th genotype in analyzed SNP; Hm= fixed effect of m-th herd (only for Charolais animals); βev= mother’s age linear covariable; εijklm = residual random error. The model only included factors found significant in an exploratory analysis which considered evaluation of first-order interactions and analysis of the quadratic effect of mother’s age. Subsequently, the least-squares means and standard error of the SNP genotype effects were estimated using the GLM procedure and compared using the PDIFF method with the Tukey-Kramer adjustment. All analyses were run with the SAS 9.0 statistical package (SAS Institute Inc., Cary, NC, USA). Allelic frequency analysis of the 28 markers found them all to be polymorphic in the two evaluated populations (Table 1). Due to a heterozygous deficit, the LEP-1457 and PRL-RsaI markers deviated from Hardy-Weinberg equilibrium; the first in the Simmental breed (P<0.0003) and the second in the Charolais breed (P<0.0001). In both cases, sample size was the most probable explanation for the observed deviation, although another possible explanation was the level of inbreeding due to the limited number of sires used in the studied herds.

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Table 1: Allelic frequencies of the evaluated 28 SNP panel for the Charolais and Simmental breeds Charolais

SNP GHR-1.1 GHR-1.4 GHR-2.6 GHR-2.6 GHR-4. GHR-6.1 GHR-A536 GHR-F279 GHR-H54 GHR-N528 GHR-S555 GHRH+2279 GHRH-2298 GHRH-4241

A 0.9020 0.5758

G 0.0980 0.4242

0.1106 0.1106

0.3995

0.3819 0.3593

A 0.7479 0.4871

0.6197

0.8957 0.2759

0.7241 0.3319

0.6681

0.6034

0.3966

0.4655 0.3922

0.9696 0.9698 0.3803 0.5214 0.9698

0.4786 0.0302 0.1043

0.6457 0.6407

G 0.2521 0.5129

0.0304

0.5556

0.4548 0.3543 0.6181

0.0302

0.9472 0.3668

0.6332 0.6005

0.5452

0.8894 0.8894 0.4444 0.7814 0.9646

0.2186 0.0354 0.0528

Simmental

0.2328 0.5345

0.7672 0.6078

IGF1/Sna BI

0.6633

0.3367

0.5690

0.4310

LEP-1180

0.6106

0.3894

0.7802

0.2198

LEP-1457 LEP-3100 LEP-3157 LEP-3257 LEP-3272

0.5941

0.4059 0.7437

0.9898

LEP-978C LEPY7FA

0.8065

PRL/Rsa I

0.3081

0.6173 0.2563

0.0102

0.3827 0.8233

0.9957

0.1767 0.0043

0.1658 0.1658

0.8342 0.8342

0.2586 0.2586

0.7414 0.7414

0.4975

0.5025

0.7802

0.2198

0.1935 0.6919

0.9914

0.0086

0.1121

0.8879

PRL2723

0.2663

0.7337

0.2716

0.7284

STAT1-C213

0.9121

0.0879

0.9430

0.0570

STAT5A12735

0.9564

0.0436

0.8190

0.1810

bGH/Alu I

0.7828

0.2172

0.7888

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0.2112

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Comparison of allelic frequencies identified 25 markers that differ significantly between the two evaluated populations (P<0.001). Only three markers exhibited no differences between the populations: GHR-1.1 (P>0.389), LEP-3157 (P>0.516) and GH/Alu I (P>0.649). Although all the evaluated markers can potentially associate with productive traits, the GH/Alu I, IGF1-Sna BI and LEP-1180 markers had particularly high frequencies because all three have been associated with productive traits such as animal weight, and carcass and meat quality in cattle populations of different breeds, and in both Bos taurus taurus and Bos taurus indicus(16-20). The C/G transversion at nucleotide position 2141 of exon 5 of the GH gene (GH/Alu I marker) produces a change from valine (G allele) to leucine (C allele) at amino acid position 127 of the gene. Animals carrying a favorable C allele are usually associated with greater marbling and higher carcass weight(21,22). For this marker, the evaluated breeds exhibited a higher frequency of the favorable allele. An analogous situation was observed with the IGF1/Sna B1 marker in the form of a T/C transition at position -472 of the non-coding 5' region of the IGF1 gene. Animals carrying the favorable C allele for this marker have been associated with greater gains in weight at weaning than carriers of the T allele(8,18). The LEP-1180 marker is a non-synonymous transition from cytosine (C) to thymine (T) located in exon 2 of the leptin gene, which produces an amino acid change from arginine to cysteine(23). The alleles of this marker have been associated with dorsal fat content and meat softness(16,23). The studied populations exhibited a lower frequency of the T allele, considered favorable for the carcass characteristics mentioned above. This result may reflect the fact that selection pressure on beef breeds in Mexico has been skewed toward traits that are easily measured and recorded (e.g. live weight) rather than towards those associated with meat quality(2,12). In the Charolais population the association analysis indicated that the PRL2723 marker located in the prolactin gene had a significant effect (P= 0.0350) on BW (Table 2). Mean weight in animals with the homozygous CC genotype (44.69 kg) was 5.66 kg higher than those with the homozygous TT genotype and 6.43 kg more than those with the heterozygous CT genotype.

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Table 2: Markers with a significant effect on weight variables in the studied Charolais and Simmental populations Breed Genotype n LSM SE C Loci (P ) Charolais BW PRL2723 (0.0350) CC 7 44.69 2.64 a CT 42 38.23 1.27 b TT 54 39.03 1.22 b b WW GHR-6.1 (0.0226) AA* 0 AG 14 187.98 7.41 b GG 59 203.59 5.76 a Simmental LEP-3100 (0.0249)

WW CC CT TT*

75 30 0

204.38 225.98 -

7.11 7.66 -

b a

12.31 a 9.52 a 10.48 b

a a b

YW GHR-6.1(0.0369)

AA AG GG

19 35 22

261.24 266.42 237.12

LSM = least-squares means; BW = Birth weight; WW = Weaning weight; YW = Yearling weight. * Genotype excluded from association for lack of observations. ab Means with a different lowercase letter are different (P<0.04). SE = standard error.

Due to its crucial role in mammary gland development, lactogenesis and regulation of important genes involved in milk production, the prolactin gene is a strong candidate for marker-assisted selection. Some SNPs in this gene have been associated with different traits. However, SNP PRL-2723, located in intron 1 of the prolactin gene, has been used in some studies, although to date this allelic substitution has no known positive or negative effects. In beef cattle, changes in milk production and composition can be reflected in the offspring(24). A particularly relevant result of the association analysis was that the GHR6.1 marker had an effect on two live weight parameters in both evaluated breeds. In the Charolais population it significantly affected WW: average weight in animals with the homozygous GG genotype (203.59 kg) was 15.61 kg higher than in those with the heterozygous AG genotype (187.98 kg). Due to a lack of carriers (n = 0), genotype AA was excluded from the association analysis. In the Simmental population, the GHR-6.1 marker was associated with YW: animals with genotype AA and AG were heavier at one year than those with genotype GG (Table 2). Like many other genes of the somatotropic axis, polymorphisms located in this gene have been associated with different productive traits, mainly in dairy cattle. In Mexican 289

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beef cattle, in this case from Charolais herds in the states of Nuevo León and Sonora, this same marker (GHR6.1) is reported to explain approximately 9% of the genetic variance (P=0.0877) in birth weight, with an αG>A=0.509(12). Charolais producers in Mexico commonly acquire genetic material from cattle farms in Nuevo León. Evaluation of these markers’ effects on different live weight phenotypes will therefore validate this locus as a focal point in Charolais selection strategies in Mexico. This would also hold in the case of the Simmental breed since the GHR-6.1 marker was clearly associated with YW in the study population. In the Simmental population the LEP-3100 marker was closely associated with WW. Mean WW for the CT genotypes (225.98 kg) was 21.6 kg higher than for the homozygous CC genotype. Due to the low number of carriers (n= 4) the TT genotype was excluded from the association analysis. The leptin gene is among the most important biological candidates for study of body fat in animals and humans(19). Leptin is one of many hormones which participate in regulation of intermediate metabolism through effector mechanisms involving growth factors such as IGF-1. The leptin gene has been extensively studied in cattle and different polymorphisms described that have been associated with productive traits involving energy metabolism, adiposity and reproduction. This gene has also been associated with regulation of body weight via mediation of weight gain metabolism(19). The LEP-3100 polymorphism is a transition in exon 3 of the gene that causes an amino acid change of Ala>Val at position 80. This polymorphism has been positively associated with meat fatty acid composition; specifically, the C allele has been positively associated with C14:1 fatty acid content(20). This is the first time the association of this marker with weaning weight has been tested; this variable is an important indicator of weight gain and productivity in meat production in the Simmental breed. The 28 SNPs located in candidate genes for growth are polymorphic in the analyzed populations and exhibit significantly different allelic frequencies in the two evaluated breeds. In these breeds the association analysis identified three markers that significantly affect the evaluated live weight parameters.

Acknowledgements The research reported here was financed by the CONACYT (proyecto 294826) and the Instituto Politécnico Nacional (proyecto SIP-IPN No. 20180727). The authors thank the cattle producers of Tamaulipas for their participation and for permission to collect samples and use production information. 290

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Literature cited: 1.- Glazier AM, Nadeau JH. Aitman TJ. Finding genes that underlie complex traits. Science 2002;(298):2345-2349. 2.- Jahuey-Martínez FJ, Parra-Bracamonte GM, Sifuentes-Rincón AM, MartínezGonzález JC, Gondro C, García-Pérez CA, et al. Genome-wide association analysis of growth traits in Charolais beef cattle. J Anim Sci 2016;94(11):4570-4582. 3.- Takasuga A. PLAG1 and NCAPG-LCORL in livestock. J Animal Sci 2016;(87):159–167. 4.-Luna-Nevarez P, Rincon G, Medrano JF, Riley DG, Chase CC, Coleman SW, et al. Single-nucleotide polymorphisms in the growth hormone-insulin-like growth factor axis in straight bred and crossbred Angus, Brahman, and Romosinuano heifers: Population genetic analyses and association of genotypes with reproductive phenotypes. J Anim Sci 2011;(89):926-934. 5.- Sherman EL, Nkrumah JD, Murdoch BM, Li C, Wang Z, Fu A, et al. Polymorphisms and haplotypes in the bovine neuropeptide Y, growth hormone receptor, ghrelin, insulin-like growth factor 2, and uncoupling proteins 2 and 3 genes and their associations with measures of growth, performance, feed efficiency, and carcass merit in beef cattle. J Anim Sci 2008;(86):1–16. 6.- Lu A, Hu X, Chen H, Jiang J, Zhang C, Xu H, et al. Single nucleotide polymorphisms in bovine PRL gene and their associations with milk production traits in Chinese Holsteins. Mol Biol Rep 2010;(37):547-551. 7.- da Silva RCG, Ferraz JBS, Meirelles FV, Eler JP, Balieiro JCC, Cucco DC, et al. Association of single nucleotide polymorphisms in the bovine leptin and leptin receptor genes with growth and ultrasound carcass traits in Nellore cattle. Genet Mol Res 2012;11(4):3721-3728. 8.- De la Rosa-Reyna XF, Montoya-Martínez HM, Castrellón VV, Sifuentes-Rincón AM, Parra-Bracamonte GM, Arellano-Vera W. Polymorphisms in the IGF1/Sna B1 gene and their effect on growth traits in Mexican beef cattle. Genet Mol Res 2010;9(2):875-883. 9.- Cheong HS, Yoon DH, Park BL, Kim LH, Bae JS, Namgoong S, et al. A single nucleotide polymorphism in CAPN1 associated with marbling score in Korean cattle. BMC Genet 2008;(9):33-10. 10.- Oikonomou G, Michailidis G, Kougioumtzis A, Avdi M, Banos G. Effect of polymorphisms at the STAT5A and FGF2 gene loci on reproduction, milk yield and lameness of Holstein cows. Res Vet Sci 2011;91(2):235-239. 11.- Ruprechter G, Carriquiry M, Ramos JM, Pereira I, Ana M. Metabolic and endocrine profiles and reproductive parameters in dairy cows under grazing 291

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conditions: effect of polymorphisms in somatotropic axis genes. Acta Vet Scand 2011;53:35. 12.- Parra GM, Lopez N, Sifuentes AM, Morris S, Lopez LA, Meza LA. Single and composite influence of growth-related candidate gene polymorphisms on additive genetic variation of birth weight in Charolais beef cattle. Trop Anim Health Prod 2014;(46):509-512. 13.- Paredes-Sánchez FA, Sifuentes-Rincón AM, Segura-Cabrera A, García-Pérez CA, Parra-Bracamonte GM. Ambriz-Morales P. Associations of SNP located at candidate genes to bovine growth traits prioritized with an interaction networks construction approach. BMC Genet 2015;16(91):1-12. 14.- Kalinowski ST, Taper ML, Marshall TC. Revising how the computer program CERVUS accommodates genotyping error increases success in paternity assignment. Mol Ecol 2007;(6):1099-1106. 15.- Rousset F. Genepop'007: a complete reimplementation of the Genepop software for Windows and Linux. Mol Ecol Resour 2008;8:103-106. 16.-Schenkel FS, Miller SP, Yee X, Moore SS, Nkrumah JD, Li C, et al. Association of single nucleotide polymorphisms in the leptin gene with carcass and meat quality traits of beef cattle. J Anim Sci 2005;(83):2009–2020. 17.- Unanian M, Barreto C, Ribeiro-de Freitas A, Torres C, Josahkian, LA. Associations between growth hormone gene polymorphism and weight traits in Nellore bovines. Rev Bras Zootec 2000;(29):1380-1386. 18.- Siadkowska E, Zwierzchowski L, Oprzadek J y Strzalkowska N. Effect of polymorphism in IGF-1 gene on production traits in Polish Holstein-Friesian cattle. Anim Sci Pap Rep 2006;(3):225-237. 19.- Matos-Almeida S, Amazonas E, TerraI G, Pereira J, Bayard DP, de Azevedo T. Association between molecular markers linked to the Leptin gene and weight gain in postpartum beef cows. Cienc Rural 2007;37(1):206-211. 20.- Orrù L, Cifuni GF, Piasentier E, Corazzib M, Bovolenta S, Moioli B. Association analyses of single nucleotide polymorphisms in the LEP and SCD1 genes on the fatty acid profile of muscle fat in Simmental bulls. Meat Sci 2011;(87):344–348. 21.- Tatsuda K, Oka A, Iwamoto E, Kuroda Y, Takeshita H, Kataoka H, et al. Relationship of the bovine growth hormone gene to carcass traits in Japanese black cattle. J Anim Breed Genet 2008;(125):45–49. 22. Grochowska R, Lundén A, Zwierzchowski L, Snochowski M ,Oprzadek J. Association between gene polymorphism of growth hormone and carcass traits in dairy bulls. Anim Sci 2001;(72):441–447.

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23.- Buchanan FC, Fitzsimmons CJ, Van Kessel AG, Thue TD, Winkelman-Sim DC, Schmutz SM. Association of a missense mutation in the bovine leptin gene with carcass fat content and leptin mRNA levels. Genet Sci Evol 2002;(34):105-116. 24.- Pacheco-Contreras VI, Parra-Bracamonte GM, Lรณpez-Bustamante LA, MorenoMedina VR, Sifuentes-Rincรณn AM. Milk composition and its relationship with weaning weight in Charolais cattle. Rev Bras Zootec 2015;(44):207-212.

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https://doi.org/10.22319/rmcp.v11i1.5588 Technical note

Yield and nutritional value of common vetch (Vicia sativa l.) during fallwinter in Zacatecas, Mexico

Ricardo A. Sánchez-Gutiérrez a Juan José Figueroa-Gonzáles a José Saúl Rivera Vázquez b Manuel Reveles-Hernández a Héctor Gutiérrez-Bañuelos b Alejandro Espinoza-Canales c*

Instituto Nacional de Investigaciones Forestales Agrícolas y Pecuarias (INIFAP). Campo Experimental Zacatecas. Calera de V.R., Zacatecas, México. b

Universidad Autónoma de Zacatecas. Unidad Académica de Medicina Veterinaria y Zootecnia. Zacatecas, México. c

Universidad Autónoma de Zacatecas, Unidad Académica de Agronomía. Zacatecas, México.

*Corresponding author: alexespinoza82@live.com.mx

Abstract: Common vetch (Vicia sativa L.) can be used to improve overall livestock feed quality and improve soils, but more information is needed on optimum harvest time and plant nutritional profile to broaden it use in livestock production systems. An evaluation was done of forage yield, crude protein content and plant element yields in common vetch at six harvest times during a fall-winter season under irrigation in the state of Zacatecas, Mexico. Vetch seed was sown in early December 2016 following a completely randomized experimental design with four replicates. Plants were harvested 47, 61, 75, 89, 103 and 117 d after sowing. The

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variables measured included fresh and dry forage yield, green and senescent leaf, stem, flower and pod yields and crude protein content. Data were analyzed using a repeated measure analysis in the SAS statistical package. Fresh forage yield increased (P<0.05) from 493 kg ha-1 at 47 d to 20,562 kg ha-1 at 103 d. Dry forage yield increased constantly (P<0.05) from 14 kg DM ha-1 at 47 days to a maximum of 3,796 kg DM ha-1 at 103 d. Crude protein content decreased (P<0.05) after 60 d, remained between 27 and 29 % DM from 75 to 103 d, and then dropped to 20.7 % at 117 d (P<0.05). Under the experimental conditions optimal harvest time for common vetch intended as cattle feed is approximately 100 d, just as flowering begins. Key words: Common vetch, Yield, Crude protein.

Received: 05/09/2018 Accepted: 19/02/2019

Forages classified as having good protein quality, be it for grazing or harvesting, are those with the highest demand for animal feed. There are approximately 33.5 million cattle and 17.4 million sheep and goats in Mexico, all of which require quality feed to meet maintenance and production needs(1). Alfalfa (Medicago sativa L.) is the most widely used feed crop in beef and milk production systems, but has the limitation of decreased production during the winter months(2). In north-central Mexico small grain cereals such as oats, barley, wheat and triticale are used as alternative crops to alfalfa during the fall-winter cycle(3). These are characterized for having regular to low protein quality when at their highest dry matter (DM) production levels(4,5). A more promising alternative to alfalfa is annual fodder legumes. These have high crude protein content and improve soil properties, making them ideal for increasing resource use efficiency in livestock production systems(6). Common vetch (Vicia sativa l.) is used in making hay and for grazing livestock, and is known for tolerating temperatures as low as -10 Â°C(7). It can fix more nitrogen than many small grain cereals, especially under nitrogen-restricted conditions(8,9). This speciesâ&#x20AC;&#x2122; growth habit can become climbing when in competition with another crop, which has led to its mixing with different cereals(10). When vetch is associated with oats, triticale or barley, forage production is reported to increase from 3 to 33 %(11). When vetch was included in a forage mixture, neutral detergent fiber (NDF) and acid detergent fiber (ADF) did not improve compared to cereals, although crude protein (CP) content decreased because as a monocrop vetch contains from 14 to 45 % CP(12). Vetch can provide benefits in small ruminants. In a study using vetch as a supplement to forage hay at 0 to 1.5 % of live weight in lactating goats milk production increased from 40 to 50 % at the end of the lactation period(13). When lambs were grazed on vetch or barley monoculture pastures plus a feed concentrate feeding costs were reduced up 295

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to 20 % in the vetch treatment(14). In the state of Zacatecas, Mexico, 21,478 ha of oats are cultivated during the fall-winter cycle(1). Vetch is a possible alternative to oats but its adoption is limited by a lack of information on forage yield and quality as well as optimal harvest stage or date. The present study objective was to quantify the fresh and dry forage yield, crude protein content and yields for individual plant elements of common vetch (Vicia sativa L.) at six harvest dates with the aim of identifying optimum harvest time during the fall-winter cycle under irrigated cultivation in Zacatecas. The experiment was carried out at the Zacatecas Experimental Station (102°39’ W; 23°36’ N) of the National Institute of Forestry, Agricultural and Livestock Research (Instituto Nacional de Investigaciones Forestales, Agrícolas y Pecuarias – INIFAP). Located at 2,192 m asl, regional climate is semi-arid, with 340 mm average annual rainfall, mostly in July and August, and an average temperature range of 12.4 to 21.8 °C during the months of December to May(15). During the crop cycle, only 29.7 mm rainfall were recorded, representing 42 % of average rainfall during this period (Figure 1). Soil in the experimental field is sandy loam with a pH of 7. For the experiment V. sativa crop seeds were sown directly in the soil on 9 December 2016 using a completely random experimental design with four replicates. The seed (80 kg ha-1; 90 % viability) was sown in rows 0.76 m apart with double seed lines in each row. The experimental unit was eight rows 0.76 m wide and 5.00 m long. The effective plot consisted of the two middle rows along the 5 m length per harvest, omitting the two exterior rows of each experimental unit. A surface strip irrigation system was installed and an approximately 60 cm layer of water applied. An initial fertilization was done using 60-60 nitrogen (N)-phosphorus (P). Plants were harvested every 14 d, starting 47 d after sowing (DAS).

Figure 1: Cumulative monthly rainfall (mm) and mean temperature (°C) at INIFAPZacatecas Experimental Station during Winter and Spring 2016-17

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The variables were measured using the whole plant on the harvest date. They included crude protein content (CP); fresh forage yield (FFY); dry forage yield (DFY), and dry matter yield of the plant elements fresh leaf (FLY); senescent leaf (SLY); stems (SY); flowers (FY) and pods (PY). The estimate of FFY was made from the biomass harvested from the effective plot at 5 cm above ground surface and weighed. Two random samples (0.5 kg) were taken of the fresh forage. In one, stems, green and senescent leaves, flowers and pods were separated out and weighed while the other was used for quantifying CP. The plant element subsamples and all the remaining fresh forage sample were dried in an oven at 55 °C for 48 h. These were weighed separately to measure dry matter percentages. Estimation of DFY per hectare was calculated based on FFY and the dry matter percentages. The dried samples containing all plant elements were processed in a Wiley mill with a millimeter sieve. Crude protein content (CP) was calculated using total N which was quantified using the Dumas combustion analysis(16). The results were statistically analyzed following a completely random design with repeated measurements run with the “PROC MIXED” procedure of the SAS statistical package(17). Comparison of means was done using the “Lsmeans” function with a probability of less than 5 %(17). Trends in FFY, DFY and CP were identified with a regression analysis. Under the experimental conditions FFY increased (P<0.05) from 493 kg ha-1 on d 47 to 20,562 kg ha-1 on d 103, and declined thereafter (Figure 2). The model with the best fit was a third-degree polynomial, which exhibited a high coefficient of determination (R2=0.904). Dry forage yield (DFY) increased (P<0.05) constantly from 14 kg DM ha-1 on d 47 to 3,796 kg DM ha-1 on d 103, and then remained relatively constant (P>0.05). For this variable the third-degree polynomial model explained 96.3 % of variability (R2=0.963). The present FFY results coincide with the 20.49 t DM ha-1 reported at peak production, with quadratic behavior(18). Yields for dry forage (DFY) were similar to the 2.6 to 4.2 t DM ha-1 reported 85, 92, 106 and 118 d post-harvest in Zacatecas, although no differences between harvest dates were reported(19). The common vetch growth dynamic in the fall-winter observed in the present results can be useful in making decisions about different uses of this crop. Vetch is recommended as an alternative forage crop because it increases forage organic matter content, while benefiting soil conservation by preventing erosion(20,21). Optimal harvest date for vetch to be used as green manure is from 100 to 110 d after sowing, as this is when the foliage contains sufficient biomass and the highest amount of water, both favorable conditions for soil microorganisms to break down and mineralize organic matter(22).

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Figure 2: Fresh and dry forage growth dynamic in common vetch (Vicia sativa) during the 2016-17 fall-winter cycle in Zacatecas

Crude protein content (CP) decreased after 60 days, remained between 27 and 29 % from 75 to 103 d and reached a low (P<0.05) of 20.7 % at 117 d (Figure 3). The third-degree polynomial model exhibited the best fit with a 0.99 coefficient of determination (R2). This agrees with reports that CP in common vetch decreases towards the end of the growth cycle, with levels decreasing from 32 % at flowering to 14.4 % near physiological maturity(23). Minor decreases (P>0.05) in CP of 29 % at 85 d to 24 % at 118 d have also been reported in Zacatecas(19). One of the main factors affecting animal production is feed quality. In forages quality is linked to plant developmental stage, as well as to species and environmental adaptation. Under the present experimental conditions during the fall-winter cycle in Zacatecas, optimal harvest time is approximately 100 d after sowing, once DFY levels out and when CP begins to decrease.

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Figure 3: Crude protein content (CP) and dry forage yield (DFY) in common vetch during the 2016-17 fall-winter cycle in Zacatecas

Stem DM yield (SY) increased significantly at each harvest up to 89 d, after which it remained relatively constant (P>0.05) (Table 1). Green leaf DM yield increased (P<0.05) from 30 kg DM ha-1 after 47 d to 1,487 kg DM ha-1 after 103 d, with no differences thereafter. Both senescent leaves and flowers were first recorded after 103 d, and neither yield differed over time (P>0.05). Pods were only recorded in the final harvest at 117 d. Green leaf DM yield (GLY) was consistently higher than SY, a good indicator of forage quality and a predictor of forage intake since crude protein accumulates largely in the leaves and is the most digestible component of the plant(24). Dry or yellowed leaves began to appear in the harvest at 103 d. These indicate incipient senescence, during which the plant redistributes nutrients from the leaves to flower and seed development(25).

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Table 1: Yields (kg ha-1) of common vetch (Vicia sativa) plant elements (±SD) in six harvests during the 2016-17 fall-winter cycle in Zacatecas DAS

GLY

SLY

27±4 a

30±2 d

229±102 b

285±122 c

557±55 c

699±99 bc

913±194 d

1098±474 ab

103

1085±186 d

1488±348 a

662±469 a

871±194 a

117

1091±228 d

1183±570 a

1256±425 a

172±64 a

164±40

DAS= days after sowing; SY= stem yield; GLY= green leaf yield; SLY= senescent leaf yield; FY= flower yield; PY= pod yield; SD= standard deviation.

Based on the present results optimal harvest time for common vetch under the experimental conditions for use as green manure or as an ingredient in livestock feed was approximately 100 d. This generally coincides with the appearance of flowers and the highest crude protein content. Harvest when common vetch exhibits about 20 % flowering has been recommended in previous studies(10,11,26). Common vetch (Vicia sativa) is a promising element for use in sustainable livestock production and merits further research aimed at genetic selection and improvement. Six vetch lines exist in Zacatecas with yields higher than vetch lines sold in Mexico(27), highlighting the need to identify lines with potential as a monocrop forage, with erect or semi-erect growth habits and which can be mixed with small grain cereals.

Literature cited: 1.

SIAP. Sistema de Información Agroalimentario y Pesquero. SAGARPA, México. https://www.gob.mx/siap. Consultado 12 Sep, 2016.

2. Moreno DL, García AD, Faz CR. Manejo del riego en alfalfa. Producción y utilización de la alfalfa en la zona norte de México. Secretaría de Agricultura, Ganadería y Desarrollo Rural. Instituto Nacional de Investigaciones Forestales y Agropecuarias. Centro de Investigación Regional Norte Centro. Campo Experimental La Laguna; Libro Técnico núm. 2, 2002.

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3. Cruz CJJ, Núñez G, Faz R, Reta DG, Serrato HA. Potencial forrajero y eficiencia de uso del agua de canola (Brassica napus L.) en comparación con cultivos tradicionales en el ciclo de invierno. AGROFAZ 2012;12:125-130. 4. Feyissa F, Tolera A, Melaku S. Effects of variety and growth stage on proportion of different morphological fractions in oats (Avena sativa L.). Degefa T, Feyyissa F editors. Proc 15th Ann Conf Ethiopian Soc Anim Prod (ESAP) Ethiopia 2007:47-61. 5. Hadjipanayiotou M, Antoniou I, Theodoridou M, Photiou A. In situ degradability of forages cut at different stages of growth. Livest Prod Sci 1996;45(1):49-53. 6. Kuusela E, Khalili H, Nykänen-Kurki P. Fertilisation, seed mixtures and supplementary feeding for annual legume–grass–cereal pastures in organic milk production systems. Livest Prod Sci 2004;85(2-3):113-127. 7. Mikić A, Mihailović V, Ćupina B, Đorđević V, Milić, D, Duc, G, et al. Achievements in breeding autumn-sown annual legumes for temperate regions with emphasis on the continental Balkans. Euphytica Int J Plant Breed 2011;1(1):5. 8. Ruffo M, Parsons A. Cultivos de cobertura en sistemas agrícolas. Informaciones Agronómicas del Cono Sur 2004-21:13-16. 9. Kurdali F, Sharabi NE, Arslan A. Rainfed vetch-barley mixed cropping in the Syrian semiarid conditions. Plant Soil 1996;183(1):137-148. 10. Caballero R, Goicoechea EL, Hernaiz PJ. Forage yields and quality of common vetch and oat sown at varying seeding ratios and seeding rates of vetch. Field Crop Res 1995;41(2):135-140. 11. Dhima KV, Lithourgidis AS, Vasilakoglou IB, Dordas CA. Competition indices of common vetch and cereal intercrops in two seeding ratio. Field Crop Res 2007;100(23):249-256. 12. Lithourgidis AS, Dhima KV, Vasilakoglou IB, Dordas CA, Yiakoulaki MD. Sustainable production of barley and wheat by intercropping common vetch. Agron Sustain Dev 2007;27(2):95-99.

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13. Berhane G, Eik LO. Effect of vetch (Vicia sativa) hay supplementation to Begait and Abergelle goats in northern Ethiopia: II. Reproduction and growth rate. Small Ruminant Res 2006;64(3):233-240. 14. Rihawi S, Iñiguez L, Knaus WF, Zaklouta M, Wurzinger, M, Soelkner J, Bomfim MAD. Fattening performance of lambs of different Awassi genotypes, fed under cost-reducing diets and contrasting housing conditions. Small Ruminant Res 2010;94(1-3):38-44. 15. Medina GG, Ruiz CA. Estadísticas climatológicas básicas del estado de Zacatecas (Periodo 1961-2003). 1ª ed. México: INIFAP; 2004. 16. AOAC, Official Methods of Analysis.16th ed, Association of Official Analytical Chemists, Gaithersburg, MD, USA. 1999. 17. SAS. SAS/STAT User´s Guide. Statistical Analysis System. Inc. Cary, NC. Versión 9.1. 2011. 18. Lithourgidis AS, Vasilakoglou IB, Dhima KV, Dordas CA, Yiakoulaki MD. Forage yield and quality of common vetch mixtures with oat and triticale in two seeding ratios. Field Crop Res 2006;99(2-3):106-113. 19. Flores-Nájera MDJ, Sánchez-Gutiérrez RA, Echavarría-Cháirez FG, Gutiérrez-Luna R, Rosales-Nieto CA, Salinas-González H. Producción y calidad de forraje en mezclas de veza común con cebada, avena y triticale en cuatro etapas fenológicas. Rev Mex Cienc Pecu 2016;7(3):275-291. 20. Navarro-Garza H, Olvera P, Antonia M, Castillo-González F. Evaluación de cinco especies vegetales como cultivos de cobertura en valles altos de México. Rev Fit Mex 2007;30(2):151-157. 21. Viteri S, Martínez J, Bermúdez A. Selección de abonos verdes para los suelos de Turmequé (Boyacá). Agron Colom 2008;26(2):332-339. 22. Celaya-Michel H, Castellanos-Villegas AE. Mineralización de nitrógeno en el suelo de zonas áridas y semiáridas. Terra Latinoamericana 2011;29(3):343-356. 23. Ramos‐ Morales E, Sanz‐ Sampelayo MR, Molina‐ Alcaide E. Nutritive evaluation of legume seeds for ruminant feeding. J Anim Physiol Anim Nutr 2010-94(1):55–64.

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24. Alatorre-Hernández A, Guerrero-Rodríguez J, Olvera-Hernández JI, Aceves-Ruíz E, Vaquera-Huerta H, López SV. Productividad, características fisicoquímicas y digestibilidad in vitro de leguminosas forrajeras en trópico seco de México. Rev Mex Cienc Pecu 2018;9(2):296-315. 25. Buchanan-Wollaston V, Earl S, Harrison E, Mathas E, Navabpour S, Page T, Pink D. The molecular analysis of leaf senescence–a genomics approach. Plant Biotechnol J 2003;1:3-22. 26. Erol A, Kaplan M, Kizilsimsek M. Oats (Avena sativa) – common vetch (Vicia sativa) mixtures grown on a low-input basis for a sustainable agriculture. Tropical Grasslands 2009;43:191-196. 27. Flores OMA, Gutiérrez LR, Palomo RM. Veza común y Lathyrus sativus L.: alternativas para producir forraje en Zacatecas. Instituto Nacional de Investigaciones Forestales y Agropecuarias. Folleto científico No.13. 2007.

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https://doi.org/10.22319/rmcp.v11i1.4391 Technical note

“Wilman lovegrass Hercules”, Eragrostis superba (Peyr) a grass variety for arid and semi-arid regions

Sergio Beltrán López a Carlos Alberto García Díaz a Catarina Loredo Osti b* Jorge Urrutia Morales a José Antonio Hernández Alatorre a Héctor Guillermo Gámez Vázquez a

Instituto Nacional de Investigaciones Forestales Agrícolas y Pecuarias (INIFAP). CIRNECampo Experimental San Luis. México. b

Universidad Autónoma de San Luis Potosí. UASLP. Facultad de Agronomía y Veterinaria. México.

*Corresponding author: catarina.loredo@uaslp.mx:

SNICS registry: ERA-002-060608. Registration date: August 1st, 2008.

Abstract: The wilman lovegrass (Eragrostis superba) is a perennial specie, native to South Africa, from good forage value that adapts well to a wide range of soils and climatic conditions. The Hercules variety of wilman lovegrass comes from collections made in Central and Northern Mexico. It was assessed in arid and semi-arid zones in rainfed and irrigation from 1986 until the record in 2008. The registration granted by the National Service of inspection and certification of seeds (SNICS) is ERA-002-060608. To date, the first variety recorded for this

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specie in Mexico. The mean dry matter annual production of this variety performance ranges between 886 y 1,947, mean of 1,416 kg DM ha-1under rainfed conditions and between 24.8 y 11.4 t DMha-1, mean of 18.1t DMha-1 under irrigation conditions. This grass is tolerant to drought, easy settlement and rapid growth, is palatable to livestock, grazing-resistant and tolerant to salinity. It is used for the recovery of degraded rangeland and conservation of soil in grassland of arid and semi-arid zones in Mexico. Key words: Eragrostis superba, New variety, Arid lands, Semiarid lands.

Received: 27/02/2017 Accepted: 21/03/2019

Origin Originally from South Africa(1), Wilman lovegrass (Eragrostis superba Peyr) is an introduced perennial bunch grass currently distributed from the United States of America to Argentina(2), among other regions. Easily established, it is resistant to grazing and provides good forage quality, containing up to 15 % crude protein in the spring(3), and with an in vitro dry matter digestibility (IVDMD) of 49.7 %(4). It grows well at altitudes from 300 to 2,000 m asl(5), adapts to arid and semi-arid conditions, will prosper in a wide variety of soils, especially in sandy loam, and recovers well after intense grazing(3,5). This grass species is mainly used for forage production, but has also been used in revegetation of degraded lands in arid areas in association with bush vegetation and mesquite and huisache forests(6,7,8). It yields from 1,200 to 1,800 kg dry matter (DM) in seasonal cultivation(3,5), and is preferably used fresh to increase acceptance by livestock(5,6). Eragrostis superba tolerates arid conditions (annual rainfall of 250 to 350 mm)(5), and salinity (up to 150 meq/l)(9), and protects soils from erosion(10). Due to its good persistence it is recommended for rehabilitation of degraded grasslands(6). It can adapt to a wide range of different soil types at 5 to 8 pH(11), and has a high probability of success in the face of rainfall irregularities(3). This species has good hydrodynamics and presents no serious threat of uncontrolled dispersion(8). Yields of E. superba in the Mexican highlands (928 kg/ha) exceed those for Bouteloua gracilis (567 kg/ha)(12). The Garrapata Hercules variety originates in a collection of fourteen E. superba accessions from states in northern and central Mexico: Chihuahua, Durango, Zacatecas, Coahuila, Nuevo LeĂłn and San Luis PotosĂ(13). In 1986, these accessions were evaluated under seasonal, grazing-free conditions in observation plots at three sites in the highlands of San Luis PotosĂ, 305

Rev Mex Cienc Pecu 2020;11(1):304-310

Mexico: Villa de Arriaga (21°53’00” N, 101°16’00” W; 2,198 m asl); Venado (22°52’16” N, 101°14’51” W; 1,970 m asl); and Soledad de Graciano Sánchez in the INIFAP San Luis Experimental Station (22°14’03” N, 100°53’11” W; 1,835 m asl). These plots were monitored and measured for over four consecutive years (1986-1989). Based on its persistence, forage yield, stability and forage quality, accession 185515 was deemed optimal. This accession was originally collected in Tuitán, Durango (24°02’08” N, 104°15’03” W; 1,882 m asl). Once selected, accession 185515 was evaluated at the same sites as above for a further eight years. Between 1997 and 1999 seed from accession 185515 was harvested from these observation plots with the aim of establishing a seed production lot in 2000. Planted in a 1,500 m2 area in the INIFAP San Luis Experimental Station, the accession was grown under irrigation conditions to observe its growth potential in the absence of moisture limitations with the objective of producing seed for this new variety of grass for arid and semi-arid conditions in Mexico. As part of the research project “Characterization, description, production and registration of new varieties of pastures”, begun in 2001 and with an emphasis on outstanding accessions for altitudes higher than 1,800 m asl, this accession was planted on 5,000 m2 of irrigated land in the same experimental field in 2002 with the goal of botanically characterizing it and producing basic seed. In 2004 the forage potential of the Garrapata Hercules variety (accession 185515) was tested by planting it under seasonal conditions in one-hectare parcels with ten farmers at different locations in the arid and semi-arid region of San Luis Potosí (Table 1). Average yield at these ten parcels ranged widely from 1,200 to 2,100 kg DM ha-1. Table 1: Test parcel farms and location information Farm

Location

Predio El Chilar Villa de Zaragoza El Pedregal Villa de Zaragoza La Sabanilla, Ejido Santa Real de Catorce María del Refugio Tanque Dolores Real de Catorce La Mora, Fracción de Salinas de Triana Hidalgo Villa de Ejido San José de la Peña Guadalupe Villa de La Nopalera, El Leoncito Guadalupe San José del Muerto, Ejido Matehuala Francisco Sarabia La Loma, Ejido Presa Verde Cedral El Cuarejo Cedral

306

21°58’56” 21°57’54”

100°45’30” 100°49’01”

Altitude (m asl) 1950 1860

23°44’41”

101°17’19”

2505

23°39’35”

101°09’48”

1900

22°43’21”

101°39’21”

2050

23°15’46”

100°46’05”

1740

23°22’50”

100°45’18”

1650

23°22’00”

100°48’33”

1720

23°58’29” 23°49’54”

100°41’56” 100°34’37”

1910 1770

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Formal characterization of the E. superba Garrapata Hercules variety (accession 185515) was done at the INIFAP San Luis Experimental Station from 2002 to 2004. According to a pre-established format, seed volume production per hectare, germination quality, purity (%) and viability (%) were quantified. Once characterized, the variety was submitted to the National Seed Inspection and Certification Service (Servicio National de Inspecciรณn y Certificaciรณn de Semillas - SNICS) for possible registration as a new variety for arid and semi-arid areas. Final SNICS registration was completed in 2008 for Eragrostis superba Peyr Garrapata Hercules (ERA-002-060608); to date this is the only registered variety for this species in Mexico.

Variety morphological description The principal characteristics of the Garrapata Hercules variety are: root with deep ramifications (>50 cm) and fibrous growth; leaves 30.4 cm long and 0.92 wide, dark green, acicular shape; longevity 64 days; erect growth habit; stems dark green, cylindrical 0.24 cm thick and 88.8 cm long; glume, lemma and palea size 5.0 mm; glumes emerald green; plant height to base of inflorescence 69.8 cm; ovoid seed shape, dark brown color, 0.472 mg weight, 1.02 mm long, 0.208 mm wide; imbibition onset 3.0 h (0.13 days), imbibition complete 8.0 h (0.33 d); radicle emergence 13.0 h (0.54 d); coleoptile emergence 21.0 h (0.88 d); germination rate: 3.4 plants/h in one hundred seeds; days to emergence: 7; seedling vigor: strong; very high establishment capacity; regrowth mechanism with basal or root crown buds; degree of bunching: excellent; recovery vigor: excellent; days to flower issue: 78; type of flowering: undetermined; days to anthesis onset: 9; flower density per stem and plant: 62.09 (viable); days to flowering termination: undetermined; predominant flower fertility: 12.8; number of viable seeds per inflorescence: 1,284; resistance to matting: good; resistance to deseeding: good; pest tolerance: good; drought tolerance: good; burn tolerance: good; cold tolerance: regular; salinity tolerance: regular; acidity tolerance: regular; frost tolerance: bad; flood tolerance: good; persistence: good.

Agricultural characteristics The Eragrostis superba (Peyr) Garrapata Hercules variety grows well in arid and semi-arid areas with sandy and sandy loam soils where average annual rainfall ranges from 250 to 350 mm, with good distribution during the summer, and average annual temperature is 16 ยบC(5). According to the evaluations carried out from 1986 to 1997 in the municipalities of Venado, Villa de Arriaga and Soledad de Graciano Sรกnchez (370 mm average annual rainfall during 307

Rev Mex Cienc Pecu 2020;11(1):304-310

ten-year period), estimated average dry forage yield in seasonal conditions was 1,200 kg ha-1 and average plant height was 64.8 cm. When grown at the San Luis Experimental Station (1,835 m asl) under seasonal conditions over a three-year period dry matter yield and plant height (respectively) were 886 kg DM ha-1 and 42 cm (332.2 mm annual rainfall); 1,330 kg DM ha-1 and 72 cm (364 mm annual rainfall); and 1,075 kg DM ha-1 and 64 cm (340 mm annual rainfall). When evaluated from 1994 to 1996 in Villa de Arriaga municipality (2,198 m asl) under seasonal conditions, dry matter and plant height (respectively) were 980 kg DM ha-1 and 72 cm (286 mm annual rainfall); 1,370 kg DM ha-1 and 64 cm (394 mm annual rainfall); and 1,947 kg DM ha-1 and 80 cm (406 annual rainfall). In forage species potential seed production is a major factor in grassland vegetation communities due to its effect on species dominance, regeneration and survival(14,15,16). A species with high seed production and a good germination percentage is highly probable to have good establishment and persistence(16). At the INIFAP San Luis Experimental Station, under irrigation and fertilization (120-60-00), seed production was 1,651 kg non-scarified seed ha-1 in a single harvest per year, with 80 germination and 82 purity. These results are similar to previous reports(15,16). Fresh forage yield was 24.8 t ha-1 and dry forage yield was 11.4 t DM ha-1 in a single annual harvest, under irrigation. An evaluation of seed count resulted in 1’578,947 seeds kg-1 from scarified seed. Bromatological analyses showed this variety to contain 38 % dry matter; 10.2 % crude protein at flowering onset and 4.6 % at maturity; and 8.2 % digestible protein at flowering onset and 3.1 % at maturity. This protein content is high compared to most grasses in arid and semi-arid ecosystems(17). At flowering onset and maturity (respectively) ash content was 11.6 % and 5.4 %, calcium content was 0.39 % and 0.23 %, and phosphorus content was 0.09 % and 0.04 %.

Literature cited: 1.

Strickland RW. Dry matter production, digestibility and mineral content of Eragrostis superba Peyr and E. Curvula (Schrad.) Nees at Samford, South Eastern Queensland. Tropical Grasslands 1973(7):2.

Álvarez L. Evaluación del valor nutritivo de gramíneas perennes estivales a lo largo de la estación de crecimiento y su diferimiento, mediante la técnica in situ [tesis de Producción Agropecuaria]. Argentina: Universidad Católica Argentina; 2010.

Esqueda CMH, Carrillo RRL. Producción de forraje y carne en pastizales resembrados con gramíneas introducidas. Tec Pecu Mex 2001;39(2):139-152.

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Labarthe FS, Pelta HR. Introducción básica a la fotosíntesis y características de especies forrajeras megatérmicas. Sitio Argentino de Producción Animal INTA - Centro Regional Buenos Aires Sur 2009(0291):452-6506.

Beltrán LS, Loredo OC, García DCA, Hernández AJA, Urrutia MJ, Gámez VHG, González ELA, Núñez ST. Llorón Imperial y Garrapata Hércules; nuevas variedades de pastos para el altiplano de San Luis Potosí. Folleto Técnico No. 36. INIFAP – CIRNE – Campo Experimental San Luis. México. 2009.

Beltrán LS, Loredo OC, Urrutia MJ. Manejo y rehabilitación de agostaderos de zonas áridas y semiáridas. En: “Prácticas para la conservación del suelo y agua en zonas áridas y semiáridas”. Libro Técnico núm. 1. INIFAP – CIRNE – C. E. San Luis. San Luis Potosí, SLP. 2005.

Loredo OC, Beltrán LS, Barrón CJL. Reconversión de áreas agrícolas marginales a uso pecuario con módulos forrajeros. Folleto Técnico Num 10 INIFAP – CIRNE C.E. Palma de la Cruz. San Luis Potosí, S. L. P. 1998.

Morales CR. Establecimiento de pastos en agostaderos utilizando obras para captar agua de lluvia. Folleto Técnico Núm 6. Campo Exp. La Campana INIFAP-SAGARPA. Chih, México. 2001.

Ryan J, Miyamoto S, Stroehlein JL. Salt and specific ion effects on germination of four grass. J Range Management 1975;28(1).

10. Kevin ZM, Nashon KRM, Nyariki MD, Nyangito MM, Agnes WM, Wellington NE, et al. Dry matter yields and hydrological properties of three perennial grasses of a semiarid environment in east Africa. African J Plant Sci 2010;4(5):138-144. 11. USDA-Natural Resources Conservation Service. Plants Database. Conservation plant characteristics. Eragrostis superba Peyr. Wilman lovegrass, Er Su. https://plants.usda.gov/java/charProfile?symbol=ERSU. Accessed Aug 10, 2018. 12. Jurado GP, Negrete RLF, Arredondo TJ, Garcia RHB. Evaluación de especies forrajeras nativas e introducidas bajo condiciones del Altiplano Central Mexicano. Tec Pecu Mex 1990;(28)1:40-44. 13. García DCA. Evaluación de gramíneas nativas e introducidas en el Altiplano Potosino. Resumen en memorias de la Tercera Reunión Científica. INIFAP -CIRNE-S. L. P. 1992:61-63. 14. Esqueda, CMH, Melgoza CA, Sosa CM, Carrillo RR, Jiménez CJ. Emergencia y sobrevivencia de gramíneas con diferentes secuencias de humedad/sequía en tres tipos de suelo. Tec Pecu Mex 2005;43(1):101-115. 309

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15. Sáenz FE, Saucedo TRA, Morales NCR, Jurado GP, Lara MCR, Melgoza CA, Ortega GJA. Producción y calidad de semilla de pastos forrajeros como respuesta a la fertilización en Aldama, Chihuahua. Tecnociencia Chihuahua. 2015(IX)2:111-119. 16. Carrillo SSM, Arredondo MT, Huber-Sannwald E. Flores RJ. Comparación en la germinación de semillas y crecimiento de plántulas entre gramíneas nativas y exóticas del pastizal semiárido. Tec Pecu Méx 2009;47(3):299-312. 17. Stritzler NP. Producción y calidad nutritiva de especies forrajeras megatérmicas. Rev Arg Prod Anim 2008;28(2):165-168.

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Revista Mexicana de Ciencias Pecuarias

Edición Bilingüe Bilingual Edition

Rev. Mex. Cienc. Pecu. Vol. 11 Núm. 1, pp. 1-310, ENERO-MARZO-2020

ISSN: 2448-6698

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Effect of a Pennisetum purpureum and Tithonia diversifolia silage mixture on in vitro ruminal fermentation and methane emission in a RUSITEC system Vilma A. Holguín, Mario Cuchillo-Hilario, Johanna Mazabel, Steven Quintero, Jairo Mora-Delgado …...................................................................................................................................................................…19

Growth dynamics and senescence of digit grass as a response to several canopy heights

Dinámica de crecimiento y senescencia del pasto pangola como respuesta a diversas alturas de corte José Dantas Gusmão Filho,Daniela Deitos Fries, Braulio Maia de Lana Sousa, Jailson Lara Fagundes, Alfredo Acosta Backes, Daniel Lucas Santos Dias, Sarita Socorro Campos Pinheiro, Fábio Andrade Teixeira..................................................................................................................................................................................................38

Rendimiento y calidad nutritiva del forraje en un sistema silvopastoril intensivo con Leucaena leucocephala y Megathyrsus maximus cv. Tanzania

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Consumo de follaje de Erythrina americana Miller en ovejas Blackbelly x Pelibuey

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Pasture structure and sheep performance supplemented on different tropical grasses in the dry season

Estructura del pasto, y rendimiento de ovejas suplementadas con diferentes pastos tropicales en la estación seca Leonardo Santana Fernandes, Gelson dos Santos Difante, Marcone Geraldo Costa, João Virgínio Emerenciano Neto, Itânia Maria Medeiros de Araújo, Joederson Luiz Santos Dantas, Antonio Leandro Chaves Gurgel.........................................................................................................................................................................89

In vitro production of porcine embryos with use of chemically semi-defined culture media system

Producción in vitro de embriones porcinos con el uso de un sistema de medios de cultivo químicamente semi-definidos David Urbán Duarte, Horacio Álvarez Gallardo, Sandra Pérez Reynozo, José Fernando De la Torre Sánchez...........................................................................................................................................................102

Transmission of Anaplasma marginale by unfed Rhipicephalus microplus tick larvae under experimental conditions

Transmisión de Anaplasma marginale por larvas no alimentadas de garrapata Rhipicephalus microplus bajo condiciones experimentales Itzel Amaro Estrada, Miguel A. García-Or�z, Jesús F. Preciado de la Torre, Edmundo E. Rojas-Ramírez, Rubén Hernández-Or�z, Francisco Alpírez-Mendoza, Sergio D. Rodríguez Camarillo..............................116

Inclusion of concentrate and growth promoters’ additives in sheep diets on intake, digestibility, degradability, ruminal variables and nitrogen balance

Inclusión de concentrado y de aditivos promotores de crecimiento en las dietas de ovinos sobre el consumo, digestibilidad, degradabilidad, variables ruminales y balance de nitrógeno Marcelo Vedova�o, Camila da Silva Pereira, João Artêmio Marin Beltrame, Ibrahin Miranda Cortada Neto, Anderson Luiz de Lucca Bento, Gabriella de Oliveira Dalla Martha, Maria da Graça Morais, Gumercindo Loriano Franco......................................................................................................................................................................................132

Efecto del propóleo y aceite de orégano sobre parámetros productivos, leucocitos, metabolitos y estabilidad oxidativa de la pechuga de pollo

Supplementation of broiler diets with propolis and oregano oil and its effect on production parameters, leukocytes, metabolites and breast meat antioxidant stability José Inés Ibarra-Espain, Carlos Alfredo Carmona-Gasca, Francisco Escalera-Valente, Fidel Avila-Ramos...............................................................................................................................................................153

Relación genética, formación de biopelículas, movilidad y virulencia de Escherichia coli aislada de mastitis bovina

Genetic relationships, biofilm formation, motility and virulence of Escherichia coli isolated from bovine mastitis Alejandro Sergio Cruz-Soto, Valen�n Toro-Cas�llo, Cris�án Omar Munguía-Magdaleno, José Emmanuel Torres-Flores, Luis Enrique Flores-Pantoja, Pedro Damián Loeza-Lara, Rafael Jiménez-Mejía............167

Caracterización técnica y ambiental de fincas de cría pertenecientes a muy pequeños, pequeños, medianos y grandes productores

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Revista Mexicana de Ciencias Pecuarias Rev. Mex. Cienc. Pecu. Vol. 11 Núm. 1, pp. 1-310, ENERO-MARZO-2020

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Rev. Mex. Cienc. Pecu. Vol. 11 10 Núm. Núm.4, 1, pp. pp.801-1076, 1-310, ENERO-MARZO-2020 OCTUBRE-DICIEMBRE-2019