AN ASSESSMENT OF THE ADOPTION OF IMPROVED TECHNOLOGIES AMONGST ATASP-1 BENEFICIARIES IN NIGERIA by Akinwale P. AKINTUNDE

AGRICULTURAL TRANSFORMATION AGENDA SUPPORT PROGRAM PHASE ONE

FEDERAL GOVERNMENT OF NIGERIA/ AFRICAN DEVELOPMENT BANK SUPPORTED AGRICULTURAL TRANSFORMATION AGENDA SUPPORT PROGRAM PHASE ONE (FGN/AfDB - ATASP-1)

AN ASSESSMENT OF THE ADOPTION OF IMPROVED TECHNOLOGIES AMONGST ATASP-1 BENEFICIARIES IN NIGERIA

2017

AN ASSESSMENT OF THE ADOPTION OF IMPROVED TECHNOLOGIES AMONGST ATASP-1 BENEFICIARIES IN NIGERIA By: Professor Omolehin Raphael Ajayi Dr. Muhammad Lawal Dr. Coker Ayodeji Alake Mr. Ajuwon Samuel Mr. Obinna George Opara

REVIEWED BY: Arabi, I.M., Habila E.K., Bagy H.D., Ejiogu L.C., Akintunde A.P., Falmata Z.G., Onyekineso Jp.C., Mallam M., Diso H.B., Sani S.G., Bashir J.Y.

Citation: Arabi, I.M., Egba, R.S., Manta I.H., Auwalu A.S., Abubakar A., Akwashiki H.K., Omolehin R. A., Muhammad L., Coker A.A., Ajuwon S., Obinna G.O., Akogun E.O., Habila E.K., Bagy H.D., Akintunde A.P., Ejiogu L.C., Falmata Z.G., Onyekineso Jp.C., Mallam M., Diso H.B., Sani S.G., Bashir J.Y. ISBN: 978-978-59560-0-9

Acknowledgment

he consultants wish to express their deep appreciation to ATASP- 1 Management, and in particular, National Program Coordinator for the overall coordination and supports that facilitated the smooth conduct of the study that produced this report.

We are also grateful to the National Monitoring and Evaluation Specialist for providing guidance and direction for the assignment. Moreover, our appreciation equally goes to the zonal program coordinators and their zonal officers for creating an enabling environment and logistic for the success of the assignment. Finally, we sincerely appreciate the farmers participating in this program for their efforts and for volunteering information needed for this study. These participating farmers represent the entire Nigerian resource-poor farmers that collectively toil and bear the burden of ensuring the nation's food security and national stability.

Prof. Omolehin Raphael Ajayi

TABLE OF CONTENTS Page

Acknowledgment ...............................................................................................................i Table of Contents.............................................................................................................iii List of Tables ....................................................................................................................vi List of Figures................................................................................................................viii List of Annexures.............................................................................................................ix Acronyms...........................................................................................................................x Executive Summary ........................................................................................................xi CHAPTER ONE 1.1 Introduction .............................................................................................................1 1.2 The Agricultural Transformation Agenda Support Program – 1 Description..........2 1.3 Purpose of the Study................................................................................................4 1.4 Objectives of the Study............................................................................................5 1.5 1.6

Scope of the study ...................................................................................................5 Limitations of the Study ..........................................................................................6

CHAPTER TWO 2.0 Brief on Agricultural Transformation Agenda Support Program Phase 1 .....................................................................................................................7 2.1 Program Overview...................................................................................................7 2.2 Program Goal...........................................................................................................7 2.3 Program Development Objectives...........................................................................7 2.4 Program End line Outcomes....................................................................................7 2.5 Program Implementation Strategy...........................................................................7 2.6 Program Coverage and Beneficiaries ......................................................................8 2.7 Program Components and Description ....................................................................8 CHAPTER THREE 3.1 Background of contributions to the ATASP-1 Program Development Objectives (PDO) .....................................................................................................................10 3.2 Menu of Technologies Disseminated and Adoption Strategies ............................10 Technologies disseminated to Sorghum farmers are: A. Good Agronomic Practices (GAP) ............................................................10 B. Mechanization............................................................................................10 C. Processing ..................................................................................................10 List of technologies disseminated to RICE farmers are: A. Good Agronomic Practices (GAP) ............................................................11 B. Post-Harvest Technology ...........................................................................11 iii

3.5 3.6 3.7 3.8 3.9

List of technologies disseminated to CASSAVA farmers are: A. Processing ..................................................................................................11 B. Nutrition and Health ..................................................................................12 C. Nutrition and Health ..................................................................................12 Demonstration Plots...............................................................................................12 Innovation Platform ...............................................................................................12 Farmers Field Days ................................................................................................13 Trainings ................................................................................................................13 Agricultural Research Institutes Supporting ATASP-I...........................................14 1. The International Institute of Tropical Agriculture (IITA) .......................14 2. AfricaRice..................................................................................................14 3. The International Crops Research Institute for the Semi-Arid Tropics (ICRISAT).....................................................................................15

CHAPTER FOUR 4.0 Study Approach and Methodology ........................................................................16 4.1 Study Area..............................................................................................................16 4.2 Study Design .........................................................................................................17 4.3 Sampling Procedure and Sample Selection ...........................................................17 4.4 Methods of Data Collection ...................................................................................17 4.5 Method of Data Analysis .......................................................................................17 4.6 Model Specification ...............................................................................................18 CHAPTER FIVE 5.0 Study Results and Discussions...............................................................................19 5.1 Socio-Economic Characteristics of the Farmers....................................................19 5.1.1 Age distribution of respondents .............................................................................19 5.1.2 Gender of Respondents ..........................................................................................20 5.1.3 Marital Status of Respondents ...............................................................................21 5.1.4 Educational Level of Respondents.........................................................................21 5.1.5 Household Size of Respondents.............................................................................22 5.1.6 Farm Size, structure and experience of Respondents under ATASP-I ...................23 5.1.7 Total farm size of the farmer..................................................................................23 5.1.8 Mode of acquisition of the Land ............................................................................24 5.1.9 Land area devoted to crop cultivation (cassava, sorghum and rice) ......................25 5.1.10 Years of experience in farming ..............................................................................25 5.1.11 Extension contact by ATASP-1 participating farmers............................................26 5.1.12 Farmers' participation in innovation platform, demonstration plots and field day in the project areas...........................................................................................27 5.1.13 Credit information for the last cropping season.....................................................29 5.1.14 Farmers' association membership ..........................................................................31 5.1.15 Access to agricultural training ...............................................................................34 5.1.16 Inputs used in crop production (Cassava, Sorghum and Rice) ..............................34

5.2. 5.2.1 5.2.2 5.2.3 5.2.4 5.2.5 5.2.6 5.2.7 5.2.8 5.2.9 5.2.10 5.2.11 5.3 5.3.1 5.3.2 5.4 5.4.1 5.4.2 5.4.3 5.4.4 5.4.5 5.5 5.5.1 5.5.2 5.6 5.6.1 5.6.2 5.7 5.7.1 5.7.2

Technology Disseminated to Farmers ....................................................................36 Technologies disseminated on cassava ..................................................................36 Technologies disseminated on sorghum production ..............................................38 Technologies disseminated on rice production ......................................................38 Mode of practicing technologies extended on cassava production........................40 Mode of practicing technologies extended on sorghum production ......................42 Mode of practicing technologies extended on rice production ..............................44 Reasons for farmers' adoption of Good Agronomic Practices (GAP) ...................47 Rate of adoption of technologies disseminated to farmers in the SCPZ................48 Rate of Adoption of technologies disseminated to cassava farmers ......................48 Rate of Adoption of technologies disseminated to sorghum farmers ....................50 Rate of adoption of technologies disseminated to rice farmers .............................51 Effects of Adoption of Good Agronomic Practices (GAP) on crop production ....52 Effects of adoption of Good Agronomic Practices (GAP) on crop production ....52 Effect of GAP on farmers' income (Cassava, Sorghum and Rice farmers) ...........53 Effects of ATASP-1 on other beneficiaries activities .............................................55 Effects of ATASP-1 on Fabricators outputs ...........................................................55 Effects of ATASP-1 on Processors outputs ............................................................56 Effects of ATASP-1 on the income and wellbeing of participating fabricators .....56 Effects of ATASP-1 on the income and wellbeing of participating processors .....56 Effects of ATASP-1 on Food security and the overall economic development of the country ...................................................................................................................57 Factor Influencing Adoption of cassava Technologies ..........................................57 Factor Influencing Adoption of Sorghum Technologies ........................................61 Factor Influencing Adoption of rice Technologies.................................................65 Constraints militating against the adoption of Good Agronomic Practices by cassava farmers .................................................................................................67 Constraints militating against the adoption of Good Agronomic Practices among sorghum farmers .........................................................................68 Constraints militating against the adoption of Good Agronomic Practices for rice production ..............................................................................................................70 Conclusion and Recommendations ........................................................................71 Conclusion..............................................................................................................71 Recommendations ..................................................................................................71 References ..............................................................................................................73

LIST OF TABLES Table 1: Structure of farmer's household across crops in the ATASP-1 Project ................20 Table 2: Gender of the farmers' household head................................................................21 Table 3: Marital Status of the farmers................................................................................21 Table 4: Educational qualification of the household head .................................................22 Table 5: Household size of farmers participating in the project ........................................23 Table 6: Cropping practices engaged in by farmers...........................................................23 Table 7: Total area of land owned by project farmer .........................................................24 Table 8: Mode of land acquisition by farmers ...................................................................24 Table 9: Land area devoted to the cultivation of each crop ...............................................25 Table: 10 Year of experience in farming by farmers..........................................................26 Table 11: Distribution of farmers by extension contact and membership of association ..27 Table 12: Distribution of farmers by extension contact and membership of association ..28 Table 13: Distribution of farmers by their accessibility to credit ......................................30 Table 14: Membership of Associations by farmers............................................................31 Table 15: Access to agricultural training among rice farmers ...........................................33 Table 16: Input used in crop production ............................................................................35 Table 17: Technologies disseminated on cassava ..............................................................37 Table 18: Technologies disseminated on sorghum.............................................................38 Table 19: Technologies disseminated on rice ....................................................................39 Table 20: Mode of practicing cassava technologies ..........................................................41 Table 21: Mode of practicing sorghum technologies.........................................................43 Table 22: Mode of practicing rice technologies.................................................................46 Table 23: Reasons for farmers' adoption of Good Agronomic Practices (GAP) ...............48 Table 24: Rate of adoption of cassava technologies ..........................................................49 Table 25: Rate of adoption of sorghum technologies ........................................................50 Table 26: Rate of adoption of rice technologies ................................................................51 Table 27: Effect of GAP on cassava, sorghum and rice production ..................................53 Table 28: Effect of GAP on farmers' income .....................................................................54 Table 29: Effects of ATASP-1 on fabricators outputs ........................................................55 Table 30: Effects of ATASP-1 on processors outputs ........................................................56 vi

Table 31: Effects of ATASP-1 on fabricators income ......................................................56 Table 32: Effects of ATASP-1 on processors income ......................................................57 Table 33: Analyses of factors influencing adoption of disseminated technologies to cassava farmers ............................................................................................61 Table 34: Analyses of factors influencing adoption of disseminated technologies to sorghum farmers ..........................................................................................64 Table 35: Analyses of factors influencing adoption of disseminated technologies to rice farmers ..................................................................................................66 Table 36a: Constraints militating against the adoption of Good Agronomic Practices cassava farmers.................................................................................68 Table 36b: Constraints militating against the adoption of Good Agronomic Practices among sorghum farmers ...................................................................69 Table 36c: Constraints militating against the adoption of Good Agronomic Practices among rice farmers ...........................................................................70

vii

LIST OF FIGURES Figure 1:

Map of Nigeria showing all the SCPZ where the project is located across the country..........................................................................16

Figure 2:

Crops farmers' participation in innovation platforms under the project ..................................................................................................28

Figure 3:

Crop Farmer's participation in demonstration plot ....................................29

Figure 4:

Farmer's access to credit by Crops.............................................................31

Figure 5:

Bar chart showing rate of technology adoption by cassava farmers (the serial number corresponds with the number on table 24)...................49

Figure 6:

Bar chart showing rate of technology adoption by sorghum farmers (the serial number corresponds with the number on table 25)...................50

Figure 7:

Bar chart showing rate of technology adoption by rice farmers (the serial number corresponds with the number on table 26) ..................51

Figure 8:

Yields of crops before and ATASP-1 implementation in the SCPZs .........53

Figure 9:

Farmers' income before and after ATASP-1 implementation across SCPZs .............................................................................................55

viii

LIST OF ANNEXURES Annexure 1: Farmers questionnaire..................................................................................74 Annexure 2: Processors FGD questionnaire ....................................................................82 Annexure 3: Fabricators FGD questionnaire ....................................................................86 Annexure 4: Interview with a farmer @ TungaKawo, Wushishi .......................................89 Annexure 5: A cassava crusher @ Tsadozhiko, Wushishi.................................................90 Annexure 6: Interview with a female farmers @ TunganKawo, Wushishi ........................91

ACRONYMS FGDs IAR FMARD GAPs ATA ATASP-1 AFDB DRC FAO SCPZs PZs SMEs IITA IFAD AfricaRice AgSS CAADP ECOWAS UA USD LGAs ICRISAT CGIAR PDO HIV/AIDS R4D WARDA NARS UNDP UN

Focus Group Discussions Institute for Agricultural Research Federal Ministry of Agriculture and Rural Development Good Agronomic Practices Agricultural Transformation Agenda Agricultural Transformation Agenda Support Program Phase One African Development Bank Democratic Republic of Congo Food and Agriculture Organization Staple Crop Processing Zone Processing Zones Small and Medium Scale Enterprises International Institute of Tropical Agriculture International Fund for Agriculture and Development Africa Rice Center Agricultural Sector Strategy Comprehensive African Agricultural Development Program Economic Community of West African States Unit of Account United State Dollar Local Government Authority International Crop Research Institute for Semi-Arid Tropic Consultative Group on International Agricultural Research Project development Objectives Human Immune Virus/Acquire Immune Deficiency Syndrome Research for Development West Africa Rice Development Association National Agricultural Research Systems United Nation Development Program United Nation

EXECUTIVE SUMMARY ATASP-1 commissioned consultants to evaluate the rate of adoption of technologies disseminated to farmers and other program beneficiaries (value chain actors) on the three crops being promoted across all the four Staple Crop Processing Zones of ATASP-1 in Nigeria. This is because the success of ATASP-1 program to a large extend will depend on the acceptance of the technologies being promoted among the cassava, sorghum and various rice value chain actors by the program. Consequently, justification for this study stems from the need to ascertain the level of technology options along cassava, sorghum and rice in the 4 SCPZs across the country. The study will also provide useful information for ATASP-1 Mid Term Review and is expected to aid the refinement of ATASP-1 agricultural technology outreach subprogram to address the concerns of targeted beneficiaries and increase their willingness to participate in program activities. The aim of the study was to determine the adoption rates and assess the effects of the adoption of improved technologies along the cassava, sorghum and rice value chains across the targetedSCPZs of Adani-Omor, Bida-Badeggi, Kano-Jigawa and Kebbi-Sokoto. The specific objectives were to ascertain beneficiaries' awareness of technologies extended under the Program; determine the perception of actors on adoption of improved technologies; examine the extent of adoption of improved technologies; determine the effects of technology adoption on crop production and incomes; ascertain the factors influencing the adoption of improved technologies extended; identify the constraints militating the adoption of improved technologies by value chain actors and make recommendations for improvement in the adoption of improved technologies for the project. The study focused solely on the program beneficiaries in ascertaining the rates of adoption of technologies under the program, complemented with focused group discussions (FGD) in selected communities. Consequently, a pre and mid-course no control design was used to determine the effect of adoption of good agronomic practices on crop production and incomes. Based on the need for selection of statistically sufficient sample and with due consideration to the sample frame of profiled value chain actors, 220 samples were selected using multi-stage sampling procedure, comprising 20 each of cassava, rice and sorghum farmers, spread across the four SCPZs of Adani-Omorcovering Enugu and Anambra States, Bida-Badggi in Niger State, Kano-Jigawa and Sokoto-Kebbi. Additional 32 FDGs were conducted across all the SCPZs at four each per SCPZ for fabricators and processors. Data collection was through primary and secondary sources. Primary data were solicited through the use of structured questionnaire, while secondary data were mainly from the Program's appraisal document, technical and progress reports. Questionnaires were administered to targeted value chain actors, comprising producers, processors and fabricators. Data collected xi

were coded along line the study objectives and analyzed using SPSS and STATA software. Analytical tools used were descriptive analyses like mean, frequency, standard deviation. Likert type Scales and Tobit binary regression model were also employed to analyze data collected for the study Findings showed that the mean age of participating farmers under the program were about 47 years for cassava farmers, about 44 years for sorghum and about 44 years for rice farmers. On the issues of gender of the farmers, 75% and 25 % of the cassava farmers respectively were male and female, about 49% and 51% of sorghum farmers nationally across the SCPZs were male and female respectively while about 93% and 8% of rice farmers were male and female respectively. However on the marital status of the farmers, about 68% of cassava farmers were married as against about 32% that were single which could be an indication that these unmarried farmers are youths. For sorghum, about 86% were married while about 14% were single and whereas for rice about 98% of the farmers were married while the remaining were singles. Moreover, majorityabout 77% of these farmers were educated. For cassava, about 67% of the farmers were educated, about 82% of sorghum farmers were also educated while for rice as much as 83% were educated. The high level of literacy among these farmers will enable them to easily comprehend innovation and consequently ease adoption level. The farmers in study areas also have fairly large households as the average for cassava and sorghum were 7 persons per household respectively while rice farmers have 11 persons per household. On the cropping systems adopted, 100% of cassava farmers under the program adopted sole cropping while about 89% of the sorghum farmers adopted sole cropping with about 11% practicing mixed cropping. On the other hand, about 98% of rice farmers under the program practiced sole cropping with just 2% practicing mixed cropping. All the farmers under the program are small holders as average farm size cassava was about 2 ha, while 1.7 ha for sorghum and about 2 ha for rice. Also, the average farming experience for these farmers were about 13 years for cassava, 18 years for sorghum and 18 years for rice indicating that these farmers are not new comers to farming of these crops. These farmers have adequate access to extension education with average visits of 15 times per annum for cassava, 14 times for sorghum and 15 times for rice farmers. These farmers also participated in innovation platforms with 60% for cassava farmers but poor participation by sorghum at 33% and 38% for rice. Most of these farmers were members of associations as represented by about 92% for cassava, 91% for sorghum and 100% for rice. This is an avenue through which farmers and other value chain actors can obtain assistance from government and nongovernmental organizations. Farmers under the program claimed they have poor access to credit and this might inhibit wholesale adoption of technology and confine them to small holders' status. There is need therefore to enhance their credit status for viable production activities. Farmers under the project have access to training with 98% of cassava claiming access, about 94% of sorghum and 100%

xii

rice have access, and most of the ATASP-1 trainingstook place in 2016 and 2017 when ATASP-1 started its training interventions. Substantial numbers of technologies were disseminated on each crop and the adoption rates of these technologies were very high except with a few like mechanization, conservation of stem, record keeping, yields assessment method that recorded low rate of adoption. There is need to focus on these few ones that have low rates of adoption to ensure total adoption. On the effect of adoption on crop yields, there were substantial improvement in the yields of cassava, sorghum and rice and the yields difference before and after ATASP-1 program were significant at 1% level of probability. For cassava, it was 9.44tons before versus 16.26tons after, for sorghum, it was 1.191ton versus 2.45tons after while for rice, it was 3.2tons versus 5.38tons after ATASP-1. These increases in yield were due to project effect. These yields increase has equally precipitated substantial increase in revenues and has thus changed the economic status of these farmers. There were noticeable increments in the activities of processor and fabricators as well as other stakeholders in these communities leading to overall improvement in their well being. Finally, the envisaged constraints were not really severe to warrant negative impact on adoption of technologies being promoted on each crop and as such it could be concluded that the program is on course in a bid to facilitate smooth adoption of technologies being disseminated on these crops. It is however recommended that weaker areas of adoption such as mechanization, stem conservation, environmental and record keeping should receive further attention to up their adoption. More so, credits should be made available as an incentive to encourage adoption of disseminated technologies.

xiii

CHAPTER ONE INTRODUCTION 1.1 Importance of Agriculture to the National Economy and Development Nigeria is endowed with abundant natural resources and has substantial agricultural potential. Agriculture is an important sector of the economy with high potentials for employment generation, food security and poverty reduction. However, these potentials has remained largely untapped which has led to the dwindling performance of the agricultural sector both domestically and in the international trade over years (Federal Ministry of Agriculture and Rural Development, FMARD, 2011). While Nigeria ranks first among the leading agricultural producers in the West African Sub-region, it is also the largest importer of staple products in West Africa. Despite the preponderance of hydrocarbons, the agricultural sector continues to play a decisive role in Nigeria's economic development. Agriculture accounts for about 36.5% of the Gross Domestic Product (GDP) in the country and employs nearly 45% of the country's workforce (Inter reseaux, 2015). The Federal Republic of Nigeria aims at diversifying the economy from reliance on oil, assure food security and create jobs, especially for the youth. In line with this, the Federal Ministry of Agriculture and Rural Development implemented Agricultural Transformation Agenda (ATA) to promote agribusiness, attract private sector investment in agriculture, reduce post-harvest losses, add value to local agricultural produce, develop rural infrastructure and enhance access of farmers to financial services and markets. The ATA sets out to create over 3.5 million jobs along the value chains of the priority crops for Nigeria's teeming youths and women, in particular(African Development Bank, 2013). The Agricultural Transformation Agenda Support Program, Phase One (ATASP-1) is an agricultural program developed by the African Development Bank (AfDB) in collaboration with Nigeria's Federal Ministry of Agriculture and Rural Development (FMARD) to contribute to food and nutrition security, employment generation, and wealth creation along the rice, cassava, and sorghum value chains (ATASP-1, 2017).The importance of the three key staple food crops namely cassava, rice and sorghum for which ATASP-1 is to bring about increase in production cannot be over emphasized. For instance, cassava (ManihotesculentaCrantz) which has been described as an industrial crop of the future in Africa, with the potential to generate income for poor farmers and a huge number of jobs has enormous potential to improve food security and the livelihoods of people in Africa. Cassava is an important food crop both for urban and rural consumers in Sub-Saharan Africa. Cassava is a basic staple food in Nigeria, Mozambique, Zambia, Democratic Republic of Congo (DRC), Ghana, Malawi, and Tanzania. Recently, cassava has increasingly gained importance as a cash crop for smallholder farmers in the region. Africa is the largest cassava producing region in the world accounting for nearly 55 percent of the world's cassava production. However, Africa's yields are the lowest in the world standing at only 10 tonnes per hectare compared to 26 tonnes per hectare in India (African Agricultural Technology Foundation, AATF, 2017).

Sorghum bicolor is an important food crop in Africa, Central America, and South Asia and is the fifth most important cereal crop grown in the world as well as the most important cereal food in the Northern states of Nigeria that covers the guinea savannah ecological zone (FAO, 2004). Finally, Nigeria depends on about 3 million tons of parboiled rice imports to meet half of its rice demand (Global Agricultural Information Network, 2014).Rice is a staple food in several African nations and constitutes a bigger portion of the diet on a regular basis. In the last thirty years, rice showed constant increases in sales and its rising significance reflects the strategic food security initiatives adopted in many nations. Aside from a handful of nations that enjoy selfsufficiency in rice cultivation, rice consumption surpasses production and substantial amount of the crop are imported to sustain local demand at the expense of hard earned foreign currency reserves. Throughout the closing decades of the 20th century, Nigeria's rice output reached overwhelmingly high levels. From the rapid rise in farmland area devoted to rice during that era in Nigeria, the production and consumption increased enormously. However, the growing output has not been adequate enough to meet the rising demand. To bridge such a huge deficit in the face of policy flaws, Nigeria resorted to the massive importation of rice at an unprecedented rate. Given the rising profile of rice as an essential element of Nigeria's food menu and the fact that imported rice accounts for a major portion of the nation's food imports, there is a growing desire among policy makers to boost rice production locally (Meremet al., 2017). 1.2 The Agricultural Transformation Agenda Support Program – 1 Description The approach: considering the innovative nature of the ATA, and the limited experience of the Bank and the Government in agricultural commodity value chains development, ATASP is being implemented along a pragmatic and flexible approach with the following two distinct phases: An Initial Phase of three years to put in place the delivery and institutional mechanisms through a learning by doing and piloting approach. During this phase, the Program will work on a limited number of commodity value chains, and in a limited number of Staple Crop Processing Zones (SCPZs) to develop approaches with respect to partnering with commercially-oriented rural women, youth and farmers' organizations, private sector, community-based, and other public sector delivery or enabling institutions. To conform to demand-driven and participatory intervention model, detailed implementation design studies and preparation of bidding documents for the development of infrastructure for retained commodity value chains will also be carried out during this phase. By the end of this phase, the Program would have adopted a robust inclusive private sector development approaches and instruments. The outcomes of this initial phase will be measured through clear indicators which will inform the expansion phase. An Expansion Phase of four years, building on the knowledge gained during the initial phase will first be undertaken. During this expansion phase, program design will be adjusted and its resource directed towards the most effective interventions and commodity value chains. Also, innovations developed during the initial phase will be scaled up, and a larger number of commodity value chains and SCPZs will be supported. The Program's exit strategy will be implemented.

ATASP-1 was formulated into three complementary and mutually reinforcing program components as follows: (i) Infrastructure Development; (ii) Commodity Value Chain Development; and (iii) Program Management. The Program will provide improved production, processing and marketing infrastructure necessary for selected commodity value chains. ATASP-1 will rehabilitate water conveyance structures necessary for irrigation; train value chain actors in technical and managerial skills; provide extension services to producers and processors; facilitate and improve key accesses through peri-urban/urban cities passing through markets. It will rehabilitate and construct schools, health centers; and provide sanitation and potable water facilities in the Processing Zones (PZs). The Program will enhance employment of youth and women by providing access to improved productive resources (including credit) and practical skills and increase the number of SMEs and persons engaged in the agriculture value chain. Objectives Its specific objective is to increase, on a sustainable basis, the income of smallholder farmers and rural entrepreneurs that are engaged in the production, processing, storage and marketing of the selected commodity value chains. The direct beneficiaries are the 45,300 economically active smallholders living in the rural areas who are already participating in commercial agriculture. This number is expected to increase significantly when other economically active value chain entrepreneurs enlist in the Program. The indirect beneficiaries include existing or potential small, medium and large-scale entrepreneurs and business associations who provide services to rural households. Among the target group, women and youth play a major role in crop and animal production, processing, small enterprises operation and marketing. They will be specifically targeted for Program activities and benefits. Rationale The Agricultural Transformation Agenda (ATA) has a great potential in enhancing the role of agriculture as an engine of inclusive growth leading to rural employment, wealth creation, and diversification of the economy. A major policy accomplishment in the sector is the liberation of seed and fertilizer supply, which had hitherto been controlled by the Federal Government, undermined the private sector and did not deliver the inputs to genuine farmers. Since September 2011, fertilizers and seeds are being sold by companies directly to farmers. Lending commitments from commercial banks has been leveraged using guarantees issued by the Ministry of Finance to finance the seed and fertilizer supply. In order to provide a legal framework for the establishment and perpetuity of Staple Crop Processing Zones, and transform the Nigerian agriculture sector with significant multiplier effects on the entire economy, an Act to provide a legal framework for the establishment of Staple Crop Processing Zones (SCPZ) was drafted and to be presented to the National Assembly for adoption. An assessment of past investments in the agriculture sector showed that the alignment of the country's strategic orientation with development objectives and strategy of the Bank Group were satisfactory. Current performance of the Bank's portfolio in Nigeria is satisfactory with a rating 3

of 2.3/3, compared to 2.2 in 2008. The Bank Group is ideally suited to supporting Nigeria through this intervention because: (i) the Bank Group has gained useful experiences in the development of the agriculture sector; and (ii) the partnerships with other technical and development agencies such as the Consultative Group of International Agricultural Research system (IITA, ICRISAT and AfricaRice), International Fund for Agricultural Development (IFAD), and others is an asset that the Bank can draw upon. Synergies and complementarities has been developed in on-going projects to sustain their achievements through ATASP-1 in the fields of infrastructure development, capacity development, science and technology, access to financial services and outgrowers' schemes or contract farming. Several studies were conducted in relevant areas, such as infrastructure surveys for the four PZs, and value chain assessments for the priority commodities, which guided the Bank's design approach. The Program is also in line with the Bank's Agricultural Sector Strategy (AgSS) (2010-2014) which emphasizes investment in agricultural infrastructure as means of boosting agricultural productivity, food and nutrition security, and wealth creation; and Bank's Strategy (2013-2022) as it pertains to inclusive growth objective through the involvement of youth, women and skills development. It is also in alignment with Pillar 2 (improving rural infrastructure and traderelated capacities for market access) and Pillar 3 (increasing food supply and reducing hunger) of the Comprehensive African Agriculture Development Program (CAADP). Furthermore, the Program is relevant to Pillar I (Linking Regional Markets) of the Regional Integration Strategy Paper of March 2011by potential increase in volumes of processed food commodities transported to landlocked countries such as Niger and Chad through rehabilitated access and trunk roads. 1.3 Purpose of the Study

Many technologies have been disseminated to boost cassava, sorghum and rice production through the effort of the intervention ATASP-1 program introduced by the Federal Ministry of Agriculture and Rural Development. The need to gauge how these technologies have really helped to increase crop productivity since inception and the need to increase agricultural productivity through the use of improved agricultural technologies and practices by the smallholder farmers in the face of acute food shortage and worsened living conditions necessitate this study. Nigeria is by far the largest agricultural producer of staple crops in ECOWAS. The most important crops for Nigeria are root crops and tubers on the one hand, and grains on the other. Root crops and tubers of which cassava is paramount account for more than two-thirds of staples grown in Nigeria. Nigeria's is the world's leading producer of cassava. Though, domestic cassava production has increased greatly since the late 1990s primarily due to the expansion/increase of farmed land, but cassava yield has stagnated at a low level (12t/h) on the national average. While the production of staple foods has risen sharply over the last twentyfive years, production cannot yet cover the rising demand for staples, particularly grains. Nigeria alone grows about 50% of the total production in West Africa. As is the case in nearly all West African countries, rise in grain production is due largely to the expansion of cultivated land than

to any significant improvement in yields. Meanwhile, sorghum yield has stagnated at an average yield of 1-1.5t/ha, rice yield has stagnated at about2 t/ha on the average since 1990 (Inter reseaux, 2015). Low agricultural productivity in Nigeria has been largely due to low, inappropriate and inadequate application of good agronomic practices such as fertilizer, improved seed utilization, and a wide gamut of on-farm and post-farm activities related to food safety, food quality and food security, the environmental impacts of agriculture (Hobbs, 2003; FMARD, 2011). In order to take corrective measures and achieve the ATASP-1 targets for cassava, rice and sorghum, concerted efforts must be made to provide information on the adoption of GAP among the farmers. This study is therefore an attempt to evaluate the progression of adoption of disseminated technologies under ATASP-1 in the various zones and across the entire country. 1.4 Objectives of the Study The major objective of the study is to determine the adoption rates and assess the effect of the adoption of Good Agronomic Practices (GAP) on cassava, rice, and sorghum production under the ATASP-1 Outreach Program in Adani-Omor, Bida-Badeggi, Kano-Jigawa and KebbiSokoto Staple Crop Processing Zones (SCPZs). The specific objectives are to: (i) identify the Good Agronomic Practices extended to the ATASP-1 smallholder famers; (ii) determine the perception of smallholder farmers on adoption of Good Agronomic Practices; (iii) examine the extent of adoption of Good Agronomic Practices; (iv) determine the effects of the adoption of Good Agronomic Practices on crop productivity and production; (v) Ascertain the factors influencing the adoption of Good Agronomic Practices amongst ATASP-1 farmers; (vi) Identify the constraints militating against the adoption of Good Agronomic Practices among farmers, and (vii) Make recommendations for improvement in the adoption of Good Agronomic Practices. 1.5 Scope of the study The study was conducted inthe four Staple Crop Processing Zones (SCPZs), namely AdaniOmor SCPZ (Anambra and Enugu States), Bida-Badeggi SCPZ (Niger State), and Kano – Jigawa SCPZ (Kano and Jigawa States) and Kebbi-Sokoto SCPZ (Kebbi and Sokoto States). While three crops namely cassava, sorghum and rice were the crops promoted by the program across the SCPZ in the North West, north central and south east, cassava was not part of crops promoted in Kebbi-Sokoto SCPZ and therefore only sorghum and rice farmers were sampled in the zone.

1.6 Limitations of the Study The key limitations of the survey stem from the survey design approach, which avoided the “with and without” comparison to ascertaining the effect of adoption of GAP on cassava sorghum and rice. This concern was however circumvented through the conduct of farmer interaction to affirm that only the adoption of ATASP-1 technologies caused the effects noticed. Other issues of concern were the obvious challenge of reliance on value chain actors' recall, given that the baseline survey relates to agricultural season which proceeded the year of survey. The problem of translation from English to vernacular was also an important concern, but was mitigated through the use of enumerators based in the sampled communities.

CHAPTER TWO BRIEF ON AGRICULTURAL TRANSFORMATION AGENDA SUPPORT PROGRAMME PHASE 1 2.1 Program Overview The ATASP-1 is being implemented for a period of 5 years (2015-2019), and it is estimated to cost UA113.54 million (USD174.85 million), with UA98.78 million (USD152.12 million) and UA0.25 million (USD0.385 million) financed from ADF loan and grant resources respectively, in four Staple Crops Processing Zones (SCPZs) of Adani-Omor, Bida-Badeggi, Kano-Jigawa and Kebbi-Sokoto. The Program is presently providing interventions in over 200 rural communities spreading across 33 LGAs in Seven States of Anambra, Enugu, Kano, Kebbi, Jigawa, Niger and Sokoto. These communities and Local Government Areas of the seven States occupy about 194,426 square kilometres of land area with a population of 32,121,944 people who are predominantly farmers and rural entrepreneurs. ATASP-1 Loan was signed on 22nd May, 2014. The Loan was declared effective on 20th February, 2015. The Program was launched on 6th March, 2015 at IITA Station, Kubwa. 2.2 Program Goal The goal of ATASP-1 is to contribute to poverty reduction, employment generation, import substitution, economic diversification and growth of Nigeria, particularly in Adani-Omor, BidaBadeggi, Kano-Jigawa and Kebbi-Sokoto Staple Crop Processing Zones. 2.3 Program Development Objectives The program development objectives are to improve food and nutrition security, create jobs and enhance the incomes and shared wealth of the program beneficiaries on a sustainable basis through rice, sorghum and cassava value chains. 2.4 Program End line Outcomes The Program's end line outcomes are detailed below: · 20, 000 metric tons of food crops produced per annum · 120, 000 new jobs created along commodity value chains · 25% Increased incomes of beneficiaries. · 200, 000 youths trained on agribusiness and enterprise development. 2.5 Program Implementation Strategy The program implementation strategy is based on commodity value chain development approach. This implementation strategy is geared towards ensuring improved crop productivity and continuous linkages with the off-takers of produce leading to incremental food supply and strong partnership of value chain actors in the Nigeria markets, thereby contributing to enhanced food and nutrition security, promoting employment creation, promoting income generation and wealth creation, and reducing hunger in Nigeria

2.6 Program Coverage and Beneficiaries The target beneficiaries of the program include: farmers and farmers' cooperatives, commodity processors, private sector operators and registered Small and Medium Enterprises (SMEs), input dealers and service providers in the four staple crop processing zones of Adani-Omor, BidaBadeggi, Kano-Jigawa and Kebbi-Sokoto agricultural production corridors. 2.7 Program Components and Description The Program is made up of three complementary and mutually reinforcing program components, as described below: Component 1: Infrastructure Development Rehabilitation of agricultural and ancillary social infrastructure, namely: irrigation water conveyance canals, various hydraulic structures, feeder roads, primary schools, community health centres, provision of potable water supply and sanitation/hygiene facilities; rehabilitation of demonstration and technology centres, and community produce markets. Component 2: Commodity Value Chain Development Capacity development for relevant ministries and departments; private and community-based institutions; training value chain actors in technical and managerial skills; promoting use of science and technology; training in post-harvest reduction methods; business and entrepreneurship training; training of communities and health workers on prevention and management of common diseases, nutrition and hygienic practices; development of market information system (MIS); management of environmental and social impacts; implementation of policies to promote private sector investment in agriculture. There is an outreach sub-program of ATASP-1, which is embedded in the component 2 of the program, and implemented by IITA and its consortium, comprising IITA, AfricaRice and ICRISAT. The responsibility of implementing Component 2, rest on CGIAR centres in Nigeria and with the objective of transforming Nigeria's cassava, rice, and sorghum sectors with the three CGIAR centres. The mandates of the CGIARs include; IITA for cassava; AfricaRice for rice; and ICRISAT for sorghum with their national partners, and IITA as the prime contractor for executing the outreach sub-program. This Sub-Program has three sub-components as follows: Sub-Component 1: Technology verification and extension with activities on (i) Technology verification, (ii) seed systems, planting material production, and diffusion. Sub-Component 2: Skill development activities on (i) agribusiness development, (ii) processing and marketing, and (iii) promotion of youth entrepreneurship in agriculture. Sub-Component 3: Effective program management comprising activities such as: (i) M&E studies, (ii) performance management and reporting, (iii) establishment of an appropriate management structure, and (iv) the establishment of Youth Agribusiness Training Centres.

The targeted beneficiaries of the outreach sub-program include; farmers' groups, processor groups, farmer input/service provider groups, sensitized persons (for market information services, open days, mass media), fabricators, marketers and transporters, seed companies, the youths, training participants, and policy makers. Component 3: Program Management Coordination of program activities; management based on results measurement framework; monitoring and evaluation; implementation of Environmental and Social Management Plan (ESMP); program procurement, disbursement, financial management, audit and reporting

CHAPTER THREE 3.1

Outreach Sub-Program contributions to the ATASP-1 Program Development Objectives (PDO) The overall purpose of ATASP-1 Outreach Sub-Programis to empower the selected youths in Nigeria through the full realization of the potential of cassava, rice, and sorghum value chains for employment/income generation and food security, especially among some of the country's poorest and most vulnerable populations. Outreach Sub-Program Specific Objectives § To identify and promote science-based solutions for cassava, rice, and sorghum value chains through technology verification, production, and diffusion of quality seed and planting material underpinned by sound seed systems. § To enhance skills acquisition and hence job creation through the development of agribusiness, processing, and marketing, and the promotion of youth entrepreneurship. § To ensure effective program management, monitoring, and evaluation using appropriate and quantitative results measurement frameworks to assess progress. 3.2

Menu of Improved Technologies Disseminated and Adoption Strategies

There are many technologies disseminated by the program on the three crops covered by the program in the four SCPZs across the country to enhance the achievement of goal and objectives of the program. The lists of these technologies transferred to farmers are as discussed below: Technologies disseminated to Sorghum farmers are: A. Good Agronomic Practices (GAP) This comprises the following: 1. Variety selection include; SAMSORG17 (SK5912), SAMSORG45 (Improved Deko), SAMSORG46 (Improved Zabuwa), CSR01, CSR02, CRS-03H, CRS-04H, SAMSORG14 (KSV-8), SAMSORG 40 (ICSV400), SAMSORG 41 (ICSV111), SAMSOR 44, SAMAORG 43, ZAUN-INUWA, EX-DAC. 2. Seed dressing with Apron Star. 3. Plant population: 0.75 x 0.3m 2 plants per hill. 4. Tillage: minimum Tillage (use of herbicides) Vs Conventional. 5. Fertilizer application: Micro-dosing of organic and inorganic fertilizer. B. Mechanization: Hand planter, mechanized thresher, Stover crusher, stover chopper, motorized weeded (starting 2018). C. 1. 2. 3. 4. 5.

Processing: Pop-sorghum machines, Hammer mills, hammer with cyclone. Harvesting, threshing, cleaning and packaging of sorghum. Effective Sorghum drying techniques (i.e of Solar dryer). Storage of Sorghum grains and flour for enhanced shelf life. Production of Pop Sorghum. Production of Sorghum flour using hammer mill with Cyclone. 10

6. Production of composite flour using Soyabean flour and sorghum flour. List of technologies disseminated to RICE farmers are: A. Good Agronomic Practices (GAP) This comprises the following: 1. Variety selection and sources of seeds (Already selected varieties are Faro 44, Faro52, Faro 60 and Faro 61). 2. Site/Land Preparation. 3. Field Preparation. 4. Seed Preparation. 5. Determining planting season. 6. Crop establishment (Direct seeding, nursery bed operations for transplanted rice, seed evaluation, transplanting. 7. Weed management. 8. Fertilizer application. 9. Pests and Diseases control. B. 1. 2. 3. 4.

Post-Harvest Technology Seed processing package and storage. Improved rice processing technology-use of Gem par boiler and rice cooking stove. Production of high quality rice flour. Production of rice flour based products (Rice, pancake, biscuit, chinchin, doughnut, short crust pastry, cake. 5. Production of rice beverages (rice milk, porridge, noodles, Kununshinkafa). 6. Production of extruded rice snacks (Rice/legumes snacks, noodles, cocktail bits, rice threads). List of technologies disseminated to CASSAVA farmers are: A. Good Agronomic Practices (GAP) This comprises the following: 1. Varietal selection: The varieties transferred are TME 419, TMS 30572, TMS 98/0505, TMS 01/1368 and TMS 070539. 2. Site Selection. 3. Land Preparation. 4. Plant Spacing/Population. 5. Weed Management. 6. Soil Fertility Management. 7. Harvesting Market. 8. Yield Assessment. 9. Conservation of stems across off-season. 10. Record keeping. B. Processing 1. Processing of Cassava into garri. 11

2. Processing of Cassava and starch. 3. Production of Cassava chinchin and doughnut. 4. Production of Cassava/bean crisp and eggroll. C. Nutrition and Health 1. Improved infant and young child feeding practices (exclusive breastfeeding, complementary feeding). 2. Production of complementary foods. (Rice and bambara nut mix, rice and beniseed groundnut mix, fermented millet, soyabeans and groundnut mix. 3. Food fortification and Diversification Techniques. 4. HIV/AIDs Awareness, prevention and management. 3.5

Demonstration Plots

A demonstration plot/farm is a farm which is used primarily to demonstrate variousimproved agricultural techniques, with any economic gains being an added bonus. Demonstration farms are often owned and operated by educational institution or government ministries. It is also common to rent land from a local farmer. The leaser is allowed to perform their demonstrations, while the land owner can be paid for the land usage or may be given the resulting crops. Many demonstration plots not only have crops, but may also have various types of livestock. Various techniques for feeding and bedding are tested on these farms. Demonstration farms run by universities are not only used for research, but are also used for teaching purposes. The one commonly used to disseminate proven technologies to farmers are on-farm demonstration plot, carried out by researchers on farmer's plot while allowing the farmers and other farmers in the village to observe the technologies so that they can pick up the technologies for their own use. In most cases, the harvested crops are left for the farmers after necessary data have been collected by researchers. It has been one of the methods adopted by the project and the collaborative institutions to disseminate technologies to participating farmers as well as other non-participants in the areas of coverage. 3.6 Innovation Platform Innovation platforms are widely used in agricultural research to connect different stakeholders to achieve common goals. An innovation platform is defined as 'a space for learning and change. It is a group of individuals (who often represent organizations) with different backgrounds and interests: farmers, traders, food processors, researchers, government officials etc. The members come together to diagnose problems, identify opportunities and find ways to achieve their goals. They may design and implement activities as a platform, or coordinate activities by individual members.’ Innovation platforms are particularly useful in agriculture because agricultural issues tend to be complex. They involve different biophysical, socioeconomic and political factors, and concern various formal and informal institutions. By bringing together stakeholders in various sectors 12

and from different levels, innovation platforms may be able to identify and address common concerns more effectively. So, we could have innovation platform to solve problems with rice production, processing, input dealers, fabricators, and marketing in such a way that each aspect have stakeholders joining forces with others to address the totality of the problems around this crop. We can also have for cassava, sorghum and other crops. Innovation platforms can be used to explore strategies that can boost productivity, manage natural resources, improve value chains, and adapt to climate change. Some innovation platforms focus on single issues; others deal with multiple topics. 3.7 Farmers Field Days The traditional role of field days and tours has been to introduce growers and agricultural professionals to new technologies and techniques so that the audience could see how these technologies or techniques could be practically used and applied. Based on this concept, the use of field days or tours to demonstrate the radically new technologies and site-specific management techniques behind precision farming is a perfect application of these tools. Indeed, a survey of precision farming field days held in a number of states found that field days were beneficial in showing growers and agricultural professionals global positioning systems, yield monitoring systems, techniques for grid soil sampling, software for geographic information systems, vehicle guidance systems, variable-rate application equipment, and a host of other technologies and processes. In particular, hands-on experiences, such as field demonstrations, guided sampling activities, and combine harvesting demonstrations are extremely well received and valuable. Indoor seminars featuring farmer panels, side-by-side software demonstrations, and demonstrations of geographic information systems have received high marks by participants. The survey found that a field day must be centered on a well-defined objective and a thorough understanding of the needs of the audience. Survey respondents unanimously agreed that precision farming field days and tours will be even more important as future advances in technology and management techniques are discovered. However, future precision agriculture field days or tours must be coupled with other issues or topics where precision agriculture technologies can be used to solve a practical problem and enhance management practices. A field day may include events such as ploughing competitions not usually associated with shows due to the larger space required. The events are good sources of agricultural information, as organizers can arrange for guest speakers to talk on a range of topics. 3.8 Trainings Training is very important in all businesses including agriculture. The implementation of ATASP-1 involved training the participants including youths about all aspects of agriculture like site selection, land preparation, preparation of seeds for planting, planting, weeding, and in fact all good agronomic practices that needs to be followed to ensure that farmers get the best for his efforts. The current farmers under the projects have been taught formally and practically and the training efforts are beginning to reflect in their performances as will be seen in results presentation in chapter 5.

3.9 Agricultural Research Institutes Supporting ATASP-I There are many international research institutions that have supported this project. These research institutions are: 1. The first is International Institute of Tropical Agriculture (IITA). The International Institute of Tropical Agriculture (IITA) is one of the world's leading research partners in finding solutions for hunger, malnutrition, and poverty. IITA is a non-profit international organization founded in 1967 and governed by a Board of Trustees. Its award-winning agricultural research for development (R4D) addresses the needs of the poor and vulnerable in the tropics. It works with public and private sector partners to enhance crop quality and productivity, reduce risk to producers and consumers, and generate wealth from agriculture. The Institute's R4D covers the following themes: biotechnology and genetic improvement, natural resource management, plant production and plant health, and social science and agribusiness. For the last 45 years, IITA's agricultural R4D has delivered over 70 per cent of CGIAR impact in sub-Saharan Africa. It has achieved this impact by focusing on key tropical food crops, such as banana and plantain, maize, cassava, soybean, cowpea, tree crops, and yam. With the mission to enhance food security and improve livelihoods through R4D, IITA tackles these challenges by pursuing these interrelated objectives: improving food security, increasing the profitability of foods and other agricultural products, reducing risks to producers and consumers, and helping national entities to expand agricultural growth. IITA is the prime contractor for the project but AfricanRice and ICRISAT were also involved in the midwife of the project. IITA was additionally apart from its overall role providing the necessary assistant on cassava while AfricanRice was in charge of rice and ICRISAT was in charge of sorghum. 2. AfricaRice The Africa Rice Center (AfricaRice) is a leading pan-African rice research organization committed to improving livelihoods in Africa through strong science and effective partnerships. AfricaRice is a CGIAR Research Center – part of a global research partnership for a food-secure future. It is also an intergovernmental association of African member countries. The Center was created in 1971 by 11 African countries. Today its membership comprises 26 countries, covering West, Central, East and North African regions, namely Benin, Burkina Faso, Cameroon, Central African Republic, Chad, Côte d'Ivoire, Democratic Republic of Congo, Egypt, Ethiopia, Gabon, the Gambia, Ghana, Guinea, Guinea Bissau, Liberia, Madagascar, Mali, Mauritania, Niger, Nigeria, Republic of Congo, Rwanda, Senegal, Sierra Leone, Togo and Uganda. Recognizing the strategic importance of rice for Africa and the effective geographic expansion of

the Center – which was constituted as the West Africa Rice Development Association (WARDA) in 1971 – its Council of Ministers took a historic decision in September 2009 to officially change its name to “Africa Rice Center (AfricaRice)” and to no longer refer to it as WARDA. Its mission is to contribute to poverty alleviation and food security in Africa, through research, development and partnership activities aimed at increasing the productivity and profitability of the rice sector in ways that ensure the sustainability of the farming environment. The modus operandi of the Center is partnership at all levels. Its research and development activities are conducted in collaboration with various stakeholders—primarily the National Agricultural Research Systems (NARS), academic institutions, advanced research institutions, farmers' organizations, non-governmental organizations, and donors—for the benefit of African farmers, mostly small-scale producers, as well as the millions of African families for whom rice means food. AfricaRice headquarters is based in Côte d'Ivoire. Staff is located in Côte d'Ivoire and also in AfricaRice Research Stations in Benin, Ghana, Liberia, Madagascar, Nigeria, Senegal, Sierra Leone and Tanzania. AfricanRice is providing the needed support for rice in the project. 3 ICRISAT The International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) is an international organization which conducts agricultural research for rural development, headquartered in Patancheru (Hyderabad, Telangana, India) with several regional centers in Bamako (Mali), Nairobi (Kenya) and research stations in Niamey (Niger), Kano (Nigeria), Lilongwe (Malawi), Addis Ababa (Ethiopia), Bulawayo (Zimbabwe)). It was founded in 1972 by a consortium of organizations convened by the Ford and the Rockefeller foundations. Its charter was signed by the FAO and the UNDP. Since its inception, host country India has granted a special status to ICRISAT as a UN Organization operating in the Indian Territory making it eligible for special immunities and tax privileges. ICRISAT is managed by a full-time Director General functioning under the overall guidance of an international Governing Board. The current Director General is Dr. David Bergvinson. The current chair of the Board is Prof Chandra Madramootoo. The Institute's R4D covers the following themes: biotechnology and genetic improvement, natural resource management, plant production and plant health, and social science and agribusiness. ICRISAT is providing the needed technical support for the sorghum component of the ATASP-1 program.

CHAPTER FOUR 4.0 STUDY APPROACH AND METHODOLOGY This chapter details the study area, study design and approach, method of data collection, sampling techniques, sample size, methods of data analysis and the tools employed. 4.1 Study Area The survey was implemented in the four SCPZs across the country. These zones are:Adani-Omor covering Anambra and Enugu States in the south east, Bida-Badeggi SCPZ in Niger State in the north central, Kano-Jigawa SCPZ and Sokoto-Kebbi SCPZ these two zones are located in the north western part of the country as shown in the Nigerian map. There is variation in climatic conditions across the zones with AdaniOmor located in the tropical rainforest in the South East, Bida-Badeggi located in the Guinea Savanna while Kano-Jigawa and Sokoto-Kebbi are located in the Sudan Savanna ecological zone of the country.

Figure 1: Map of Nigeria showing all the SCPZ where the program sites are located across the country Source: Agricultural Transformation Agenda Support Program Phase-1

4.2 Study Design The study focused solely on the program beneficiaries in ascertaining the rates of adoption of technologies disseminated to farmers of the three crops by ATASP-1 and this is complemented by focused group discussions in selected communities for fabricators and processors. A pre and mid-course no control design was also used to allow for the determination of the effect of adoption of good agronomic practices (GAP) on crop production and productivity. 4.3 Sampling Procedure and Sample Selection The multi-stage sampling procedure was used in selecting respondents for the study. However, given the preponderance of production-based value chain actors, 40 samples comprising 20 respondents each for rice and sorghum producers each were randomly selected from KebbiSokoto since this SCPZ have only these two crops promoted in the zone. On the other hand, 60 samples comprising of 20 respondents each for cassava, sorghum and rice were randomly selected in Kano-Jigawa SCPZ. Also, 60 samples of 20 respondents each of cassava, sorghum and rice were randomly selected in Bida-Badeggi SCPZ while 60 samples of 20 respondents each of cassava, sorghum and rice were equally selected for Adani-Omor SCPZ. The sampling was done to cover all the 33 local government areas (LGAs) where the program is being executed across the country. Similarly, to ensure that other stakeholders were not left out of the study, 4FDGs were conducted for processors and fabricators in each of the SCPZ making 8 per SCPZ and a total of 32 across the country. On the whole 220 farmers were sampled while a total of 32 FGDs were conducted across the country for the project. The process of data collection lasted for 8 days period. 4.4 Methods of Data Collection Data collection was through primary and secondary data. Primary data were solicited through the use of structured questionnaire. The questionnaires were administered to all value chain actors, comprising producers, processor and fabricators. Data collected covered value chain actors' background information, actors' specific details, institutional information, capacity building, input-output data, technologies disseminated, mode of practicing technology, rates of adoption and constraints to adoption of GAPs. 4.5 Method of Data Analysis Data collected were coded along the line of study objectives and analyzed using stata software. Objectives 1, VI and VII were analyzed using content and descriptive analysis like mean, frequency, standard deviation and count. Objectives II and III were analyzed using varied Likert type Scales, covering perception of usefulness of technologies, extent of usage of adopted technologies, perception of processing and fabrication technologies and constraints limiting adoption of GAPs. The ratings of perception were: Agree =3, Not sure =2 and Disagree =1. Objective IV was realized through the use of before and after analysis while objectives V was achieved through the use of Tobit model.

4.6 Model Specification Tobit model was used to ascertain the factors influencing the adoption of good agronomic practices among ATASP-1 farmers. The model is specified as follows in the implicit form: Yo* = Xoâ + µo

(1)

Where Yois the latent (hidden) dependent variable for the Oth farm; ? o is the vector of independent variables, vector â comprises the unknown parameters to be estimated associated with the independent variables for the Oth farm, and µo is an independently distributed error term assumed to be normally distributed with zero mean and constant variance. The independent variables considered were gender, age, marital status, education, household size and farm size. Other variables in the model were farmers' experience, extension visits, credit and association.

CHAPTER FIVE STUDY RESULTS AND DISCUSSIONS 5.1 Socio-Economic Characteristics of the Farmers This section of the study discusses the socioeconomic characteristics of farmers across the study areas by the three crops under consideration, which are cassava, sorghum and rice. Issues discussed under this section are age, gender, marital status, education and household size. These variables are very important for good planning and decision making by policy makers. The composition of these variables can also make or mar the ability of various actors' effectiveness in production process. 5.1.1 Age distribution of respondents The age structures of farmers across the three crops under ATASP-1 are as presented in table 1. From the table, about 12% of cassava farmers were within age 21-30 while for sorghum, about 14% of the farmers are within this age bracket and for rice, about 16% of the farmers are within that age bracket. There is a fairly wide variation between the age distribution at the zonal levels and the national level by crops as we have for the same age bracket for cassava, it was 25% for Bida-Badeggi SCPZ while for Kano-Jigawa, it was zero for this age bracket and for EnuguAnambra, it was 10% while cassava was not included for Kebbi-Sokoto Zone. However, for sorghum, it was zero for that age bracket and 25% for Badeji-Bida, 5% for Kano-Jigawa and 25% for Adani-Omor. Moreover, for rice, in the 21-30 age brackets, it was zero for Kebbi-Sokoto 5% for Niger, 50% for Kano-Jigawa and 10% for Adani-Omor. Nationally for rice it was about 17% of the entire sampled population falling within this age bracket. Furthermore, for 31-40 age brackets, cassava has 20% nationally while sorghum has about 19% and rice has about 21%. When these two age brackets are added together, we have 33% of farmers between the ages of 20- 40 growing these crops nationally. The implication is that the project has encouraged youth participation in food production as a business and this has a lot of significant for future food production and food security for the country. Also, looking at farmers within 41-50 age brackets, for cassava, we have about 28% of cassava farmers were in this category while 29% of sorghum farmers are in same category and about 38% of rice farmers are in the category. Farmers in this age bracket are still strong and agile and this shows that we can still continue to have sustainable food production if some of the technologies being promoted now are adopted by farmers across the country. On the average, the mean ages of farmers across the SCPZs across the country are about 47 years for cassava, 44 years for sorghum and about 44 years for rice. These mean ages are very similar to what is obtainable at various zones. For instance in Bida-Badeggi, the mean ages are 40 years for cassava, 39 years for sorghum and 42 years for rice while for Kebbi-Sokoto, it was about 47years for sorghum, and about 47 years for rice as well. In Kano-Jigawa the mean age was 52 years for cassava, about 46 years for sorghum and about 38 years for rice. Also, the mean age for cassava in Adani-Omor was 48 years for cassava, about 43 years for sorghum and about 48 years for rice. The significance of

the mean ages recorded across the zone stems from the fact that farmers across the zones are still at their active age of below 50 years and as such can still make meaningful contributions to agriculture activities in particular and economic activities in general. Table 1: Structure of farmer’s household across crops in the ATASP Crops Socio-economic characteristic Cassava Sorghum Age 21-30 7(11.67) 11(13.75) 31-40 12(20) 15(18.75) 41-50 17(28.33 23(28.75) 51-60 18(30) 20(25) > 60 6(10) 10(12.5) Mean 46.67 43.74 Min 31.00 27.25 Max 72.33 62.75 Figures in parentheses are percentages

-1 Project

Rice 13(16.25 17(21.25) 30(37.5) 18(22.5) 2(6.67) 43.6 21.5 62

5.1.2 Gender of Respondents On the gender distribution of the people engaged in ATASP-1 project, table 2 revealed that 75% of the people involved in cassava production under the project were male, while 25% were female nationally. However, looking at the gender structure by SCPZ, 90% of male in BadejiBida and 10% for female participated in the project while it was 100% for male in Kano-Jigawa and 75% male and 25% female in Adani-Omor. The non involvement of women in cassava production in Kano-Jigawa were possibly due to cultural-religion factor as well as the fact that the crop is relatively not as popular as grain crops where women are very much involved in their production and processing. On the other hand the gender distribution showed that about 49% of those involved in sorghum production under the project nationally are men while 51% are women. Looking at it on zonal basis, it was 20% for men and 80 for female in Sokoto-Kebbi, 95% for men and 5% for women in Badeji-Bida, 15 for men and 85% for women in Kano-Jigawa and 65% for men and 35% for women in Adani-Omar. The result showed that there was heavy participation of women in the sorghum production under the project than men in the north which is the traditional home for sorghum production. For rice, in Kebbi-Sokoto SCPZ, only 10% of the participants in rice are women while 90% are male, for Bida-Badeggi SCPZ, only 5% of rice participants are women while 95% are men. However, in Kano-Jigawa SCPZ, there were no women involved in rice production while in Adani-Omor, 15% of rice participating farmer are women while 85% are male. The national outlook showed that 92.5% of total participating farmers are men while only 7.5 are women.

Table 2: Gender of the farmers’ household head Gender

Crop Sorghum 39(48.75) 41(51.25)

Cassava Male 45(75) Female 15(25) Figures in parentheses are percentages

Rice 74(92.5) 6(7.5)

5.1.3 Marital Status of Respondents The distribution of farmers under this project by marital status is as shown in table 3. For cassava, in Bida-Badeggi, 90% of participants are married while 10% are single. On the other hand in Kano-Jigawa, 100% of the participants are married and at Adani-Omor only 15% are married while 85% are single. The demographic distribution by marital status as shown in Adani-Omor where single participant predominate could mean that youths were the major participants in cassava project in the SCPZs. Also, for sorghum, the demographic distribution by marital status of participants as shown in table 3 revealed that 100% of participants in Kebbi-Sokoto and Bida-Badeggi are married while in Kano-Jigawa, 85% are married while 15% are single and in Adani-Omor 60% are single. On the whole, about 86% of sorghum participants are married while only about 14% are single nationally. The non participation of single participants in Kebbi-Sokoto and Bida-Badeggi could mean that youths in these areas are showing apathy to farming as a business and there is need to do more to encourage them so that we can have sustainability in farm business in the country. Finally for rice, except in Adani-Omor where we have just 5% of the participating farmers that are yet to marry, and 90% married, in all others SCPZs, all participating farmers in rice project are married.

Table 3: Marital Status of the farmers Marital Status

Crop Sorghum 69(86.25) 11(13.75)

Cassava Married 41(68.33) Single 19(31.67) Others Figures in parentheses are percentages

Rice 78(97.5) 1(1.3) 1(1.3)

5.1.4 Educational Level of Respondents Another important socioeconomic variable is educational attainment of the household head. From table 4, cassava participants have highest, about 13% as illiterate while sorghum and rice have 5% and 2.5% respectively as illiterate participants. It is very significant that farmers participating in all crops in the project have one form of education or the other and surprisingly, of the total participants in cassava, over 60% have secondary and tertiary education while for sorghum about 48% have secondary and tertiary education and for rice, about 62% have secondary and tertiary education. The implication of this is that these participants are better 21

positioned to understand and adopt innovations that will facilitate productivity and better livelihood as opposed to when we have illiterate participants. These educated farmers will equally be able as opinion leader influence non literate farmers around them.

Table 4: Educational qualification of the household head Education

Cassava

Sorghum

Rice

None

8(13.33)

4(5)

2 (2.5)

Koranic

2(3.33)

4(5)

10(12.5)

Primary

4(6.67)

5(6.25)

12(15.0)

Juninor

14(23.33)

9(11.25)

4(5.0)

Senior secondary

22(36.67)

29(36.26)

17(21.3)

Tertiary

10(16.67)

27(33.75)

33(41.3)

Adult education

2(2.50)

2(2.5)

Figures in parentheses are percentages

5.1.5 Household Size of Respondents Finally on socioeconomic characteristics, the household size of the participants as shown in table 5 revealed that 30% of participants in cassava have between 1-5 people in their household, while 25% have between 6-10 people, 20% have 11-15 people and 25% have more than 15 people in their household and the average size for cassava was 7 people per household. On the other hand, for sorghum, about 21% of the participants have 1-5 people in their household while about 34% have 6-10 people in their household, about 24% have 11-15 people in their household while about 21% of the participants in sorghum have over 15 people in their households. The average number of household member was also 7 people. Finally for rice, 20% of the household members have family size of between 1-5, about 31% have family size of between 6-10, and 30% of the participants have family size of 11-15 while about 19% have family size greater than 15 people. On the whole, the average family size for rice participants was 11 people per household. The implication of the fairly large family size is that in some cases where the members are over 18 years old, they could give helping hands in farming particularly during planting, weeding and harvesting of crops.

Table 5: Household size of farmers participating in the project Household size

Cassava

Sorghum

Rice

1-5

18(30)

17(21.25)

16(20.0)

6-10

15(25)

27(33.75)

25(31.3)

11-15

12(20)

19(23.75)

24(30.0)

>15

15(25)

17(21.25

15(18.8)

Average

Figures in parentheses are percentages

5.1.6 Farm Size, structure and experience of Respondents under ATASP-I Table 6 shows farm structure, participants under each of the crop in ATASP-1 project across the study areas.On the farm structure, all participants in cassava practiced sole cropping while about 89% of participants in sorghum practiced sole cropping and about 11% practiced mixed cropping. On the other hand, about 98% of participants in rice practiced sole cropping while about 2% practiced mixed cropping. One can deduce from this result that the traditional mixed cropping pattern in beginning to dwindle as an important cropping pattern in Nigeria.

Table 6: Cropping practices engaged in by farmers Variables

Crops Cassava

Sorghum

Rice

Sole cropping

60(100)

71(88.75)

78(97.5)

Mixed cropping

9(11.25)

2(2.5)

Cropping practices

Figures in parentheses are percentages

5.1.7 Total farm size of the farmer On the total land areas possessed by these participating farmers, it was found from table 7 that about 23% of the cassava farmers have land areas within 0.1-0.5 ha, about 18% have land between 0.51-1.0 ha, about 178 have land between 1.10-1.50, while about 17% have land between 1.51-2.0 and 30% of the cassava participants have land that is above 2 ha as total land under their possession. The average land possessed by all cassava participant was 2.77 ha with minimum of 0.77 ha and maximum of 6.33 ha. On the other hand, for sorghum, the participants with total farm size of 0.1-0.5 represents about 24%, participants with land between 0.51-1.0 are about 36%, participants with 1.10-1.5 are 5%, 1.51-2.0 are about 8% while about 26% have total land area that were more than 2 ha for crop cultivation. The average total land area for sorghum participants was 2.38 ha while the minimum and maximum were 0.5 and 4.0 respectively. Finally, for rice participants, those with total available land areas between 0.1-0.5 represents about 6%, those with land area of 0.51-1.0 represents about 38% of the participants, those with

total land area of 1.1-1.5 represents 10%, those with 1.51-2.0 represents about 11% while those with over 2 ha of total land area represents 35%. The mean land area for rice participants was 2.1 ha while the minimum and maximum were 0.4 and 6.6 ha respectively. From this presentation, it is very clear that farmers participating in this project are mostly small scale farmers. Table 7: Total area of land owned b y project farmer Total farm size

Cassava

Sorghum

Rice

0.1-0.5

14(23.33)

19(23.75)

5(6.25)

0.51-1.0

11(18.33)

29(36.25)

30(37.5)

1.1-1.5

11(18.33)

4(5)

8(10)

1.51-2.0

10(16.67)

6(7.5)

9(11.3)

>2.0

18(30)

21(26.25

28(35.0)

Average

2.77

2.38

2.1

Min

0.77

0.5

0.4

Max

6.33

4.0

6.6

Figures in parentheses are percentages

5.1.8 Mode of acquisition of the Land On the mode of land acquisition by these farmers, from table 8, it was discovered that most of the farmers acquired their land through inheritance as about 63% of cassava farmers claimed to have obtained their land through this means, about 54% of sorghum obtained theirs through inheritance while about 63% of rice farmers obtained land through inheritance. Other mode of land acquisitions are purchase, rent, lease and gift which are less that 50% of total land acquisition for each of the crop. The implication of land acquisition through inheritance is the tendency for land fragmentations into smaller sizes that will make mechanization a very difficult task.

Table 8: Mode of land acquisition by farmers Mode of land acquisition

Cassava

Sorghum

Rice

Inheritance

38(63.33)

42(53.75)

50(62.5)

Purchase

9(15)

14(6.25)

13(16.25)

Rent

8(13.33)

8(8.75)

15(18.75)

Lease

4(6.67)

10(12.5)

1(1.25)

Gift

1(1.67)

6(7.5)

Others

Figures in parentheses are percentages

5.1.9 Land area devoted to crop cultivation (cassava, sorghum and rice). Land area in farm production is an important variable as this will determine the scale of production and to some extent the financial outcome of the business. Looking at the land areas devoted to the cultivation of crops under these three crops by participating farmers as presented in table 9, it is evidently clear that majority of them are small scale farmers as about 57% of cassava participants cultivated between 0.1-1.0, 34% cultivated between 1.1-2.0 while only about 8% cultivated cassava plot greater than 2 ha. The average land area devoted for cassava cultivation was 1.91 ha while the minimum and maximum were 4.0 ha. The result is similar in sorghum where about 65% cultivated land that were between 0.1-1.0, 16% cultivated land that were between 1.1-2.0 and about 2% cultivated land that were greater than 2 ha. The average land area devoted to sorghum cultivation was 1.66 ha while the minimum and maximum were 1.0 and 5.0 respectively. Table 9: Land area devoted to the cultivation of each crop Size of land for cultivation of Cassava/sorghum/rice

Cassava

Sorghum

Rice

0.1-0.5

24(40)

25(31.25)

5(6.25)

0.51-1.0

10(16.67)

43(53.75)

31(38.75)

1.1-1.5

8(13.33)

9(11.25)

10(12.5)

1.51-2.0

13(21.67)

5(6.25)

11(13.75)

>2.0

5(8.33)

1(1.25

24(30)

Average

1.91

1.66

2.1

Min

0.77

1.0

0.4

Max

4.00

5.0

6.6

Figures in parentheses are percentages

5.1.10 Years of experience in farming Finally in this section, we look at the year of experience of these participating farmers in the crops they are engaged in as presented in table 10. For cassava participants, about 43% of them have between 1-10 years of experience in cassava production, about 43% have 11-20 years of experience, and about 12% have 21-30 years of experience in cassava production while very few, about 12% have over 30 years of experience in cassava production. The average years of experience in cassava production was about 13 years which showed that these farmers have been familiar with cassava production and probably, using modern production technology may be the issues that needs to be addressed under this very important project. The pattern of farming experience is also similar in sorghum production as about 41% of the participating farmers have 1-10 years of experience as shown in table 10, about 29% have between 11-20 years of experience in sorghum production, about 19% have between 21-30 years of experience in sorghum production while about 14% have over 30 years of experience in sorghum production. On the overall, the average years of experience in sorghum production was 25

18.2 years showing that these participating farmers are well familiar with sorghum production to enable them understand and cope based on their high levels of education about the newly introduced production technologies. For rice, about 29% have 1-10 years of experience in rice cultivation while 45% have 11-20 years of experience, 15% have 21-30 years of experience and about 11% have over 30 years of experience in rice cultivation. The average year of experience nationally for rice cultivation was 18 years. This shows that the cultivation of rice has been with us as a nation for a fairly long time.

Table: 10 Year of experience in farming by farmers Farming Experience

Cassava

Sorghum

Rice

1-10

26(43.33)

33(41.25)

23(28.75)

11-20

26(43.33)

23(28.75)

36(45.0)

21-30

7(11.67)

15(18.75)

12(15.0)

>30

7(11.67)

11(13.75)

9(11.25)

Average

12.67

18.2

17.9

Figures in parentheses are percentages

5.1.11 Extension contact by ATASP-1 participating farmers Contact by farmers with the extension workers is very important as this is an important source of technology diffusion to farmers particularly farmers in the rural communities. Table 11 presents information about extension contact, number of visits and membership of association by ATASP-1 participating farmers. From table 3, 98% of cassava participating farmers claimed they have contact with extension agents while less than 2% claimed they do not, about 99% of sorghum participating farmers claimed they have contact with extension agents while barely 1% claimed they do not and about 98% of rice farmers claimed they have contact with extension agents while about 2% claimed they do not. On the number of visits, averagely, cassava had about 15 visits, sorghum 14 visits while rice had 15 visits annually. This is considered to be very substantial and sufficient enough to enhance adequate information dissemination to these farmers.

Table 11: Distribution of farmers by extension contact and membership of association Variables

Crops Cassava

Sorghum

Rice

Yes

59(98.33)

79(98.75)

78(97.5)

1(1.67)

1(1.25)

2(2.25)

1-5

26(43.33)

13(16.25)

24(30)

6-10

7(11.67)

24(30)

18(22.5)

11-15

9(15)

19(23.75)

18(22.5)

16-20

9(15)

10(12.5)

6(7.5)

>20

8(13.33)

13(16.25)

14(17.5)

Average

15.33

Extension visit

Number of visit

Figures in parentheses are percentages

5.1.12 Farmers' participation in innovation platform, demonstration plots and field day in the project areas. On the other hand, farmers in the project also claimed they participated in innovation platforms such as rice innovation platform, sorghum innovation platform and cassava innovation platform. It is evident that there are national and international research organizations like ICRISAT, IITA, AFRICA Rice and IAR showing visible presence in these zones that must have facilitated the involvement of many of these farmers in innovation platform participation. Demonstration plots participation is a very important medium of physically introducing innovations to farmers rather than verbal description of innovation. On the participation of these farmers in demonstration, table 12 showed that 55% of the participating cassava farmers have participated in demonstration plot while 45% have not, 90% of sorghum farmers have participated in sorghum demonstration plots while 70% of rice farmers have participated in demonstration plots. The highest percentage recorded for sorghum could be due to long time working relationship of farmers with IAR and ICRISAT that have been working on this crop for ages particularly in northern parts of the country. Farmers' field day is an important event that enables researchers and farmers to observe the difference in crop yields between the improved technologies and the traditional practices of crop production. Across the three crops, it was found that most participating farmers as shown in the table 12 participated in farmers' field day. For cassava, about 52% participated in field day, about 61% of sorghum farmers participated in field day while for rice, 90% participated in farmers' field day. Figure 2 presents farmers participation in innovation platforms across the three crops and across the SCPZs over Nigeria. It is quite clear by the graphical presentations that 60% and above of the farmers across the three crops under the project have participated in innovation

platforms and this will facilitate quicker understanding of the innovations being disseminated to these farmers. Also, figure 3 presents the participation of these farmers in demonstration plots and from the figure, it was quite clear that over 60% of these farmers have participated in demonstration plots which it is believed will accelerate understanding of technologies being disseminated to these farmers. Table 12: Distribution of farmers by extension contact and membership of association Variables

Crops Cassava

Sorghum

Rice

Yes

36(60)

26(32.5)

30.0(37.5)

24(40)

54(67.5)

22.5(28.12)

Yes

33(55)

72(90)

56(70)

27(45)

18(22.5)

28(35)

Yes

49(51.67)

49(61.25)

72(90)

31(48.33)

31(38.75)

8(10)

Participation in innovation platform

Participation in demonstration plot

Participation in farmers’ field day

Figures in parentheses are percentages

Figure 2: Crops farmers' participation in innovation platforms under the project

Figure 3: Crop Farmer's participation in demonstration plot 5.1.13 Credit information for the last cropping season Credit is very important in all production process because it is needed to procure inputs, hire labour, carry out the marketing process and to even process the raw produce from farms to intermediate and final products that are desired by the ultimate consumers. From table 13, it was found that majority of farmers under the ATAPS-1 project claimed they had no access to credit. From the table, about 62% of the cassava participants claimed they had no access to credit, about 53% of sorghum participants claimed they had no access to credit while about 61% of rice participants claimed they had no access to credit. These farmers may continue to remain small holders since they have no access to credit for production process. Table 13 also talked about the sources of credit available to these farmers and from the table, these farmers obtain credit from commercial banks, cooperatives, agricultural bank, traders, NGOs and family and friends. The problem with the non institutional lenders is that their interest rates could be a times too exorbitant. Looking at table 13 again, it was discovered that credit obtained by farmers were less than what they required. The average credit required by cassava farmers was N72, 583.33 while the corresponding average credit obtained was N53, 200.00. On the other hand, the average credit required by sorghum farmers was N151, 772.40 while the corresponding credit received by sorghum farmer was N71, 253.29. On a final note, the average credit required by rice farmer was N88, 170.73 while the corresponding average received was N46, 668.75. It is very clear from the quantum of credit required that these farmers are small holder producers. On the nature of credit, from the table it is very clear that farmers usually preferred cash and most of the credits given to farmers were cash.Figure 4 presents farmers access to credit in a graphical way for better understanding. It is quite clear from the figure that less than 50% of farmers across all the crops and zones have access to credit. This is not really good enough as lack of access to credit will hamper adoption of technology and consequently productivity of these farmers. 29

Table 13: Distribution of farmers by their accessibility to credit Variables Crops Cassava Sorghum Access to credit Yes 23(38.33) 38(47.5) No 37(61.67) 42(52.5) Source of credit Credit program 2(3.33) 5(6.25) Commercial bank 5(8.33) 1(1.25) Cooperatives 1(1.67) 4(5) NGOs Traders 2(2.5) Agricultural bank 4(6.67) 4(5) Family and friends 2(3.33) 8(10) Others Credit required 1000-50000 6(7.5) 50001-100000 7(8.75) 100001-150000 7(8.75) 150001-200000 6(7.5) 200001-250000 6(7.5) 250000-300000 3(3.75) >3000000 Average 72583.33 151772.4 Credit received 1000-50000 6(10) 12(15) 50001-100000 10(16.67) 10(12.5) 100001-150000 4(6.67) 1(1.25) 150001-200000 2(3.33) 200001-250000 1(1.25) 250000-300000 >3000000 Average 53200.00 71253.29 *Nature of credit Cash 22(36.67) 20(25) Kind 1(1.67) 6(7.5) Figures in parentheses are percentages * Multiple responses were allowed

Rice 31(38.75) 49(61.25) 2(2.5) 6(7.5) 7(8.75) 1(1.25) 5(6.26) 9(11.5) 12(15)

13(16.25) 8(10) 6(7.5) 6(7.5) 11(13.75) 1(1.25) 2(2.5) 88170.73 18(22.5) 14(17.5) 3(3.75) 3(3.75) 5(6.25) 46668.75 38(47.5) 10(12.5

Figure 4: Farmer's access to credit by Crops 5.1.14 Farmers' association membership Membership of association exposes farmers to several benefits such as training, inputs purchase at reduce price, easy marketing of farm produce and easy access to credit. From table 14, it was found that sizeable number of participating farmers were members of cooperative association. For cassava, about 92% of the participants were members of cooperative association, about 91% of sorghum were members while 100% of rice participants were members of cooperative association. This in fact will give these farmers opportunities to access much assistance from government and nongovernmental organizations Finally, on the number of years these farmers have participated in cooperative associations, it was found that the average for cassava was 6 years, for sorghum it was 4 years while for rice it was 5.5 years.

Table 14: Membership of Associations by farmers Membership of association Yes No Years of participation 1-5 6-10 11-15 >15 Average

Cassava 55(91.67) 5(8.33)

Sorghum 73(91.25) 7(8.75)

Rice 80(100) -

33(55) 13(21.67) 3(5) 6(10) 6

39(48.75) 19(23.75) 8(10) 4(5) 4

47(58.8) 24(30.0) 7(8.75) 2(2.5) 5.5

5.1.15 Access to agricultural training Training is very important in running any business and farming is not an exemption as the person being trained will be able to receive get better understanding on how such business should be managed. From table 15, about 98% of cassava participating farmers in ATASP-1 project claimed they have been trained, about 94% of sorghum participating farmers also claimed they have been trained while 100% of farmers participating in rice production claimed they have been trained. It was equally discovered that the bulk of the training given to these farmers took place in 2016 and 2017 after the inception of ATASP-1 project indicating that the training were organized by ATASP-1 project. As shown in table 15, training have been organized for farmer under the project in farm establishment method, cultivar selection, water management, nutrient management, weed management, farm production practices and in other areas so as to help these farmers improve their productivity and income. However, these farmers have indicated that they would still want more training in those topic that have been taught to them and additional training in other areas such as farm establishment, cultivar selection, water management, nutrient management, weed management, farm production practices, seed treatment and good storage practices. The fact that these farmers are clamoring for more training is an indication that they understand the importance of training and new technologies for improved production and it also shows that they will be willing to adopt new technologies that are geared towards productivity improvement.

Table 15: Access to agricultural training among rice farmers Variables

Crops Cassava

Sorghum

Rice

Yes

59(98.33)

75(93.75)

80(100)

1(1.67)

5(6.25)

Before 2015

1(1.25)

2015

2(2.5)

2016

17(28.33)

32(40)

46(57.5)

2017

50(83.33)

63(78.75)

65(81.2)

Farm establishment method

26(43.33)

33(41.25)

53(66.3)

Cultivar selection

17(28.33)

18(22.5)

27(33.8)

Water management

6(10)

15(18.75)

46(57.5)

Nutrient management

13(21.67)

27(33.75)

40(50.0)

Weed management

21(35)

45(56.25)

51(63.8)

Farm production practices

42(70)

55(68.78)

54(67.5)

Farm establishment method

8(13.33)

15(18.75)

19(23.8)

Cultivar selection

17(28.33)

19(23.75)

23(28.8)

Water management

8(13.33)

18(22.5)

17(21.3)

Nutrient management

11(18.33)

21(26.25)

22(27.5)

Weed management

18(30)

19(23.75)

23(28.8)

Farm production practices

15(25)

13(16.25)

8(10)

Financial management

4(5)

2(2.5)

Seed treatment

7(8.75)

3(3.8)

Good storage practices

3(3.75)

1(1.3)

Access to training

*Years of training

*Aspect of training

Others Aspect of production requiring more training

Figures in parentheses are percentages

5.1.16 Inputs used in crop production (Cassava, Sorghum and Rice) Inputs are an essential derivatives from which production are made possible in any production system. Without inputs, there can be no outputs. Table 16 showed the inputs that were used by farmers under the project for the production of their cassava, sorghum and rice. The average Inputs that were used in cassava production as shown in table 16 were 58.05 Kg of cuttings, 5.25 litres of agrochemical, 50.97 mad-day of labour, 191.93Kg of fertilizer while the average output was 18732.22Kg of cassava tuber.More so, the average inputs used for sorghum production by participating farmers were 16.165Kg of seed, 5.258 litres of agrochemical, 65.10 man day of labour, 300.54 Kg of fertilizer while the output was averagely 1535.82Kg of grain. On the other hand, the average inputs used in rice production per ha were 64.83Kg of seed, 11.57 litres of agrochemical, 86.50 man day of labour, 573.38 Kg of fertilizer while the output was averagely 5647.14Kg. There seems to have been an increment in yields over what is obtainable under local production as a result of good agronomic practices employed under the project by the participating farmers.

Table 16: Input used in crop production Input used

Crops Estimates

Seed (kg)

Agro-chemical (litre)

Labour (man-day)

Fertilizer (kg)

Cassava

Rice

Mean

58.05

16.165

64.83

Min

22.00

4.5

1.50

Max

176.67

63.75

500.00

38.75

18.3375

82.60

CV(%)

60.37

86.4025

127.42

Mean

5.25

5.2575

11.57

Min

1.67

1.3

1.00

Max

24.67

12.5

62.00

5.72

3.3425

12.42

CV(%)

147.53

68.275

107.31

Mean

50.97

65.0975

86.50

Min

10.00

14.5

10.00

Max

177.67

282.25

650.00

47.03

67.9575

114.78

CV(%)

87.40

80.27

132.69

Mean

191.93

300.54

573.38

Min

150.00

78.125

100.00

Max

275.00

825

3000.00

41.85

209.5825

619.61

196.99

72.3

108.06

18732.22

1535.818

5647.14

Min

7166.67

620.875

750.00

Max

86133.33

3475

21000.00

18950.24

757.4025

4638.88

85.94

51.1

82.15

CV(%) Output (kg)

Sorghum

Mean

5.2. Technology Disseminated to Farmers There were many technologies disseminated to farmers participating in the production of cassava, sorghum and rice in the various SCPZs to facilitate the achievement of program objectives of improving substantially output so as to alleviate poverty and ensure food security in the country. The technologies disseminated on each crops are as presented below: 5.2.1 Technologies disseminated on cassava Table 17 presents technologies disseminated to farmers on cassava by the program. Technologies disseminated to enhance improved productivity in cassava production are the introduction of improved varieties which all the cassava farmers claimed they are aware of. Others are site selection with full awareness by all, land preparation known to about 98%, plant spacing/population, known to all farmers in the project, weed management known to over 98% of the farmers in the project, soil fertility also known to about 92% of the farmers, harvesting and marketing, known to about 62% of the participant, yield assessment, known to about 55% of the farmers, conservation of stem, known to about 67% of the farmers and record keeping also known to about 82% of the participating farmers. The level of awareness of farmers involved in the dissemination of these technologies was found to be very high and this might help to facilitate speedy adoption of these technologies in these SCPZ.

Table 17: Technologies disseminated on cassava Technologies

Frequency

Percentage

Yes

100

Site selection

100

Yes

98.33

1.67

Yes

100

Yes

98.33

1.67

Yes

91.67

8.33

Yes

61.67

38.33

Yes

54.67

43.33

Yes

66.67

33.33

Yes

81.67

18.33

Improved variety

No Land preparation

Plant spacing/population

Weed management

Soil fertility

Harvesting market

Yield assessment

Conservation of stem across

Record keeping

5.2.2 Technologies disseminated on sorghum production The awareness of technologies disseminated on sorghum was as presented in table 18. From the table, all the farmers were aware of improved varieties technology. The second technology was seed dressing with apron plus and 90% of the project participant claimed they know this technology while the right plant population was also known to about 99% of the farmers. The fourth in the list of the technologies was minimum tillage which was known to about 83% of the farmers under the project followed by micro dosing of organic and inorganic fertilizer known to all the farmers in the project and the last but not the least was mechanization known to by about 81% of the farmers involved in the project. Table 18: Technologies disseminated on sorghum Technologies Frequency

Percentage

Improved variety Yes

100

Yes

98.78

1.25

Yes

82.5

17.5

Yes

100

Yes

81.25

18.75

Seed dressing with Apron star

Plant population 0.75 x 0.3m 2 plants per hill

Tillage: minimum Tillage (use of herbicides)

Fertilizer application: Micro dosing of organic and inorganic fertilizer

Mechanization

5.2.3 Technologies disseminated on rice production There were many technologies disseminated to rice farmers under the project as shown in table 19. From the table, all the farmers were aware of improved rice varieties while site selection for production was known to about 89% of the farmers under the project and all the farmers-100% were aware of field preparation for rice production. More so, about 99% were aware of the right planting season for rice production while about 98% were aware of crop establishment. Other technologies these farmers are familiar with are weed management and fertilizer application 38

method aware of by all the participatingfarmers and finally, pest control were known to about 99% of the participating farmers. It is hoped that these level of awareness will stimulate improved adoption by these farmers and consequently improved level of productivity.

Table 19: Technologies disseminated on rice Technologies Frequency Improved varieties (Faro 44, Faro 52, Faro 60 and Faro 61 Yes 80 No Site/Land preparation Yes 71 No 5 Field preparation 80 Seed preparation 77 Yes 3 No Determine planting season Yes 79 No 1 Crop establishment Yes 78 No 2 Weed management Yes 80 No Fertilizer application Yes 80 No Pest and Disease control Yes 79 No 1

Percentage

100 88.8 6.3 100 96.2 3.8 98.8 1.2 97.5 2.5 100 100 98.8 1.2

5.2.4 Mode of practicing technologies extended on cassava production The analysis of the mode of practicing good agronomic practices delivered to cassava farmers are as presented in table 20. From the table, it was found that improved cassava varieties were highly in use by these farmers as the average weighted score was 4.1 which was by far greater than 3.00 indicating the cutoff point where the effective usage of this technology begins. For this improved crop varieties, about 28% of the farmers affirmed that they regularly use it, 35% claimed they often use it while about 17% claimed they sometime use it. If we sum these together, we have 80% that are using this particular technology showing that this particular technology is very popular among these farmers. On site selection, we also have a weighted average of 4.4 showing that farmers have keyed into this technology. With about 62% of them claiming that they regularly use this technology, while about 28% claimed they often use it and about 17% claimed they sometime use the technology. Summing all of these will give us a total of 107%. This is an indication that this particular technology has been overwhelmingly embraced by these farmers. The total sum here is above 100% because multiple choices were allowed. Land preparation method was another technology disseminated to cassava farmers and this technology also has a weighted score of 4.7 showing its wider applicability among these farmers. From the table, it was found that 55% of the farmers claimed they regularly make use of the technology while 40% claimed they often use the technology and 10% claimed they sometime use the technology. It could be concluded that there is overwhelming use of these technology among these farmers. Furthermore plant spacing and the right plant population was another technology disseminated to farmers and this is very important if optimum crop yields are to be obtained from any cropping system. From the table, it was found that about 53% claimed they regularly use this technology, about 28% claimed they often use it while about 17% claimed they sometime use it. The weighted score of 4.3 is an indication that farmers are using this technology to the maximum. Weed management is very important because good management of weed could lead to substantial yields while lack of weed management could spell doom for the crop yield. For this technology, the weighted score was 4.5 showing it has been widely accepted. About 63% of these farmers claimed they regularly use this technology, about 28% claimed they often use it while about 8% claimed they sometime use it. Furthermore, soil fertility weighted score was 3.4 and about 28% claimed they regularly use it, about 23% claimed they often use it while 25% claimed they sometime use it. There is need to place more emphasis on this technology because the fertility of any soil will determine the output from such soil. Record keeping was also among the technologies disseminated to farmers in the study area under ATASP-1 project and this has a weighted score of 3.1 showing its marginal acceptability. From table 20, about 42% of these farmers claimed they regularly use this technology; about 8%

claimed they often use it while about 8% claimed they sometime use it. Of all the ten technologies disseminated on cassava, seven have been widely accepted while three that have weighted score of less than three have not been widely put into use and these three are harvesting market, yield assessment and conservation of cassava stem. There is need to therefore put more efforts in persuading farmers about these technologies till they are widely accepted. Table 20: Mode of practicing cassava technologies Technologies Improved variety

Extent Frequency Regularly 17 Often 21 Sometime 10 Rarely 5 Never 2 Weighted score 4.1 Site selection Regularly 37 Often 17 Sometime 10 Rarely 3 Never 2 Weighted score 4.4 Land preparation Regularly 33 Often 24 Sometime 6 Weighted score 4.7 Plant spacing/population Regularly 32 Often 17 Sometime 10 Rarely 1 Weighted score 4.3 Weed management Regularly 38 Often 17 Sometime 5 Weighted score 4.5 Soil fertility Regularly 17 Often 14 Sometime 15 Rarely 10 Never 4 Weighted score 3.4 Harvesting market Regularly 13 Often 6 Sometime 11 Rarely 14 Never 16 Weighted score 2.5 Yield assessment technique Regularly 10 Often 10 Sometime 6 Rarely 11 Never 23 Weighted score 2.5 Conservation of stem across Regularly 15 Often 9 Sometime 8 Rarely 8 Never 20 Weighted score 2.8 Record keeping Regularly 25 Often 5 Sometime 5 Rarely 14 Never 11 Weighted score 3.1 Note: weighted score less than 3.0 indicates that respondents rarely use the technology

Percentage 28.33 35 16.67 8.33 3.33 4.1 61.67 28.33 16.67 5 3.33 4.4 55 40 10 4.7 53.33 28.33 16.67 1.67 4.3 63.33 28.33 8.33 4.5 28.33 23.33 25 16.67 6.67 3.4 21.67 10 18.33 23.33 26.67 2.5 16.67 16.67 10 18.33 38.33 2.5 25 15 13.33 13.33 33.33 2.8 41.67 8.33 8.33 13.33 18.33 3.1

5.2.5 Mode of practicing technologies extended on sorghum production There were six technologies disseminated to sorghum farmers under ATASP-1 project as presented in table 21. From the table, improved sorghum variety has a weighted score of 4.43 showing that it is widely accepted by farmers. From the table, about 64% of the farmers claimed they regularly make use of this technology, about 21% claimed they often use this technology while about 13% claimed they sometime use this technology. From all indication, there is overwhelming acceptance of this technology among the participating farmers across the SCPZs of the project. Seed dressing with apron star was another technology disseminated to farmers under the project and result from table 21 indicated that the weighted score was 3.35 when the modes of practicing technologies were analyzed. From the analyses, 25% of the farmers claimed they regularly use this technology, about 31% claimed they often use it while about 18% claimed they sometime use this technology. The acceptance of this technology rating marginally crosses the border line and there is need to devote more attention to its promotion. The right plant population was another technology disseminated to these sorghum farmers and the weighted score was 4.2 which are considered to be very high and as such this technology enjoys wider applicability. About 51% of sorghum farmers claimed they use this technology, about 23% claimed they often use it while about 24% claimed they sometime use it. Fertilizer application employing the micro dosing of organic with inorganic fertilizer is another technology disseminated and it has a weighted score of 4.03 showing its wider acceptability. About 29% of the farmers claimed they regularly use this technology, 25% claimed they often use it while about 29% claimed they sometime use it. However, two of the technologies disseminated are yet to be widely accepted and these two are minimum tillage with a weighted score of 2.75 and mechanization with a weighted score of 2.6. There is therefore the need to intensify efforts at convincing these farmers of the importance of these two technologies so as to change their acceptability.

Table 21: Mode of practicing sorghum technologies Technologies Extent Frequency Percentage Improved variety Regularly 51 63.75 Often 17 21.25 Sometime 10 12.5 Rarely 2 2.5 Never Weighted score 4.425 4.425 Seed dressing with Apron star Regularly 20 25 Often 25 31.25 Sometime 14 17.5 Rarely 7 8.75 Never 14 17.5 Weighted score 3.35 3.35 Plant population 0.75 x 0.3m 2 plants Regularly 41 51.25 per hill Often 18 22.5 Sometime 19 23.75 Rarely 2 2.5 Never Weighted score 4.2 4.2 Tillage: minimum Tillage (use of Regularly 14 17.5 herbicides) Often 15 18.75 Sometime 15 18.75 Rarely 11 13.75 Never 25 31.25 Weighted score 2.75 2.75 Fertilizer application: Micro dosing of Regularly 23 28.75 organic and inorganic fertilizer Often 20 25 Sometime 23 28.75 Rarely 10 12.5 Never Weighted score 4.03 4.03 Mechanization Regularly 19 23.75 Often 8 10 Sometime 11 13.75 Rarely 11 13.75 Never 31 38.75 Weighted score 2.6 2.6 Note: weighted score less than 3.0 indicates that respondents rarely use the technology

5.2.6 Mode of practicing technologies extended on rice production Rice production technologies disseminated enjoyed wide acceptability and applicability among farmers under ATASP-1 project as can be seen in table 22 as all the nine technologies recorder well over 4.0 weighted scores from the analyses that were done. From table 22, improved varieties had the highest weighted score of 4.7 indicating that there is overwhelming acceptance and applicability of this technology among rice farmers under the project. It was observed that about 63% of the farmers claimed they regularly use this technology, about 31% claimed they often use the technology while about 4% claimed they sometime use the technology. On site selection and land preparation, we have a weighted score of 4.6 showing its wider acceptability and applicability. About 71% of the farmers claimed they use this technology, 25% claimed they often use it while about 1% claimed they sometime use the technology. More so, field preparation equally has a weighted score of 4.6 showing its wider acceptability and applicability. From the table, about 69% claimed they regularly use it, about 23% claimed they often use it while about 6% claimed they sometime use it. There is therefore and overwhelming acceptance of this technology. Another very important technology disseminated was seed preparation which recorded a weighted score of 4.2 showing it wider acceptability. From the table, 50% claimed they regularly use this technology, about 28% claimed they often use it while about 14% claimed they sometime use it. Getting the seed aspect of production right is absolutely important and the acceptance of this technology is very important at getting the production right. Determination of the planting season is another technology disseminated to farmers under ATASP-1 project as planting at the right time will enhance crop productivity. From the table this technology has a weighted score of 4.2 showing its high level of acceptability. From the table, 55% of the farmers claimed they use this technology regularly, 20% claimed they use it often while about 14% claimed they sometime use it. Moreover, crop establishment was another technology disseminated to rice farmers with weighted score of 4.2. From the table, about 53% claimed they use this technology regularly; about 24% claimed they use it often while about 16% claimed they sometime use it. Another important technology disseminated on rice was weed management with a weighted score of 4.5. it was found that about 68% of the farmers claimed they use this technology regularly, about 20% claimed they use the technology often while about 6% claimed they sometime use this technology. The wider acceptability of weed control technology is of great significant since this will enhance higher yield. Fertilizer application technology is another very important technology disseminated and it recorded a weighted score of 4.5 showing its wider acceptability and applicability among the farmers. From the table, about 69% claimed they regularly use it, about 19% claimed they often use it while about 6% claimed they sometime use it. It is to be noted that using the right fertilizer and the right quantity is a sure way of boosting rice productivity.

Finally, pest and diseases control is another technology disseminated by ATASP-1 project to rice farmers in the project areas and this recorded a weighted score of 4.0. This showed that this technology has gained wider acceptability among these farmers. From the table, about 54% claimed that they regularly use this technology; about 14% claimed they often use it while 10% claimed they sometime use it. The acceptance of technology for pest and diseases control is very significant since pest and disease can reduce yield to almost zero when left unchecked. From the results presented here, there is bound to be very significant increase in production of rice nationwide if these promising technologies are made to go round all rice producing zones in the country.

Table 22: Mode of practicing rice technologies Technologies Improved varieties (Faro 44, Faro 52, Faro 60 and Faro 61

Site/Land preparation

Field preparation

Seed preparation

Determine planting season

Crop establishment

Weed management

Fertilizer application

Pest and Disease control

Extent Regularly Often Sometime Rarely Never Weighted score Regularly Often Sometime Rarely Never Weighted score Regularly Often Sometime Rarely Never Weighted score Regularly Often Sometime Rarely Never Weighted score Regularly Often Sometime Rarely Never Weighted score Regularly Often Sometime Rarely Never Weighted score Regularly Often Sometime Rarely Never Weighted score Regularly Often Sometime Rarely Never Weighted score Regularly Often Sometime Rarely Never Weighted score

Frequency 50 25 3 1 1 4.7 57 20 1 1 1 4.6 55 18 5 1 1 4.6 40 22 11 5 3 4.2 44 16 11 6 1 4.2 42 19 13 4 1 4.2 54 16 6 1

Percentage 62.5 31.3 3.8 1.3 1.3 4.7 71.3 25.0 1.3 1.3 1.3 4.6 68.8 22.5 6.3 1.3 1.3 4.6 50.0 27.5 13.8 6.3 3.8 4.2 55.0 20.0 13.8 7.5 1.3 4.2 52.5 23.8 16.3 5.0 2.5 4.2 67.5 20.0 7.5 1.3

4.5 55 15 5 3 1 4.5 43 11 16 8 2 4.0

4.5 68.8 18.8 6.3 3.8 1.3 4.5 53.8 13.8 20.0 10.0 2.5 4.0

5.2.7 Reasons for farmers' adoption of Good Agronomic Practices (GAP) Farmers like other entrepreneurs have reasons for any business decisions they take and questions were therefore posed to these farmers to give reasons for adopting good agronomic practices they adopted and their responses are as presented in table 23. From the table, about 77% of cassava farmers claimed they adopted these agronomic practices because they are considered to be labour saving while 15% claimed they are not sure of the labour saving capability of these practices and about 8% claimed they disagree of this assertion. Still on cassava, about 87% of the farmers that participated claimed these practices enhance higher yield while about 13% claimed they are not sure. Furthermore, about 72% of these farmers claimed these practices enhance soil moisture retention while about 28% claimed they are not sure, 85% of these cassava farmers claimed that these practices help to control erosion and about 13% claimed they are not sure. Moreover, about 78% of these farmers claimed that these practices enhance soil fertility while about 17% claimed they are not sure and finally, about 38% of these farmers claimed that these practices help crops to adapt to climate change while 60% claimed they are not. Sorghum farmers also have their good reasons for adopting good agronomic practices as shown in table 23. From the table, about 64% of the farmers claimed that these practices are labour saving while about 11% claimed they are not sure and 25% claimed that they disagreed with this assertion. On the other hand, 100% of these farmers claimed these practices encourage higher yields and furthermore, about 61% of these farmers claimed that these practices enhance soil moisture retention and about 37% claimed they are not sure. Also, soil erosion control was mentioned as one of the attributes of these practices and about 74% of these farmers were in affirmative that these practices enhance erosion control while about 24% claimed they are not sure. More so, about 81% of these farmers claimed that these practices enhance soil fertility while about 18% claimed they are not sure. Finally, about 50% of sorghum farmers claimed that these practices help crops to adapt to climate change while about 39% claimed they are not sure. Rice farmers also expressed their opinion on why they adopted good agronomic practices as follows; about 63% claimed these practices are labour saving while about 34% claimed they disagreed. Also, 95% of these farmers claimed that these practices enhances higher yield and about 89% claimed they help in soil moisture retention while 10% claimed they are not sure. Moreover, about 83% of these farmers claimed these practices enhance soil fertility while 15% claimed they are not sure. Soil erosion control is equally one of the reasons why farmers adopted these practices as about 81% claimed that was their reason for adopting these practices while 15% claimed they are not sure. On a final note, about 49% of rice farmers equally claimed these practices are capable of helping crops to adapt to change in climate while 45% claimed they are not sure. From all these, one could see that these farmers have very good reasons for adopting good agronomic practices delivered to them by ATASP-1 project and one should expect a spillover effect since they will be able to convince other non participating farmers in their neighborhood to adopt these practices and that will surely bring about improvement in agricultural production and food security nationally.

Table 23: Reasons for farmers’ adoption of Good Agronomic Practices (GAP) Reasons

Opinion

Cassava

Sorghum

Rice

Labour saving

Agree

46(76.7)

51(63.8)

50(62.5)

Not sure

9(15.0)

9(11.3)

3(3.8)

Disagree

5(8.3)

20(25.0)

27(33.8)

Agree

52(86.7)

80(100.0)

76(95.0)

Not sure

8(13.3)

2(2.5)

Disagree

2(2.5)

Agree

43(71.7)

49(61.3)

71(88.8)

Not sure

17(28.3)

30(37.5)

8(10.0)

Disagree

1(1.3)

Agree

51(85.0)

59(73.8)

65(81.3)

Not sure

8(13.3)

19(23.8)

12(15.0)

Disagree

1(1.7)

2(2.5)

3(3.8)

Agree

47(78.3)

65(81.3)

66(82.5)

Not sure

10(16.7)

14(17.5)

12(15.0)

Disagree

3(5.0)

1(1.3)

2(2.5)

Agree

23(38.3)

40(50.0)

39(48.8)

Not sure

36(60.0)

31(38.8)

36(45.0)

Disagree

1(1.7)

9(11.3)

5(6.3)

Higher yield

Soil moisture retention

Soil erosion control

Enhancement of soil fertility

Climate change adaptation

Figures in parentheses are percentages

5.2.8 Rate of Adoption of Technologies disseminated to farmers in the SCPZ There is need to constantly monitor the rate of adoption as the project progresses so as to know what review to undertake to facilitate good level of adoption that will result in the envisaged outcome conceptualized by the project from the onset. The rate of adoption of technologies under each crop has been captured by the study and they are as presented. 5.2.9 Rate of Adoption of technologies disseminated to cassava farmers From table 24, there were good levels of adoption of technologies disseminated to cassava farmers in the SCPZs across the country. Improved varieties and site selection witnessed about 97% and 97% respectively while land preparation was at about 98% level of adoption. On the other hand, plant spacing and weed management recorded 100% level of adoption while soil fertility management recorded 95% level of adoption. Moreover, stem conservation and record keeping recorded 60% level of adoption while the two that have the least records of adoption were yield assessment technique and harvesting techniques at about 47% and 48% respectively. There is therefore the need to redouble efforts on these low areas so as to maximize output by farmers under the programto achieve the desired outcome. It is also believed that good outcome will definitely spread to farmers within the communities and beyond. Figure 5 presents rate of adoption of technology adoption by cassava farmers under the project. From the figure, it was very clear that except for harvesting market and yield assessment, all technologies disseminated to cassava farmers have 60% and above rate of adoption. It is an 48

indication that these technologies enjoyed wider acceptability and adaptability. One is therefore expectant of improve crop productivity arising from the adoption of these technologies. Table 24: Rate of adoption of cassava technologies S/No

Technologies

Frequency*

Percentage

Improved variety

96.67

Site selection

96.67

Land preparation

98.33

Plant spacing/population

100

Weed management

100

Soil fertility

Harvesting market

48.33

Yield assessment

46.67

Conservation of stem across

Record keeping

* Multiple responses were allowed

Figure 5: Bar chart showing rate of technology adoption by cassava farmers (the serial number corresponds with the number on table 24)

5.2.10 Rate of Adoption of technologies disseminated to sorghum farmers There were considerable high levels of adoption of technologies disseminated to sorghum farmersunder ATASP-1 project as shown in table 25. From the table, cultivation of improved seed recorded100% level of adoption while plant population was at about 93% level of adoption. On the other hand, fertilizer application with micro dosing of organic with inorganic fertilizer recorded about 99% level of adoption while minimum tillage recorded 60% level of adoption. The only technology with the very low level of adoption at about 38% is mechanization. There is therefore the need to intensify effort on this as well as provide incentives that will encourage the uptake of this particular technology to enable farmers engage in large scale production which can only be possible under mechanized farming. Also, a graphical presentation of technologies disseminated to sorghum farmers are as presented in figure 6. From this figure, except mechanization where the rate of adoption was about 38%, all other technologies have an impressive scores ranging from 60% to 100%. It is an indication that farmers have embraced these technologies and this is expected to lead to substantial increase in output in sorghum production. Table 25: Rate of adoption of sorghum technologies S/No 1 2 3 4 5

Technologies Improved variety Plant population 0.75 x 0.3m 2 plants per hill Tillage: minimum Tillage (use of herbicides) Fertilizer application: Micro dosing of organic and inorganic fertilizer Mechanization * Multiple responses were allowed

Frequency* 80 74 48 79 30

Percentage 100 92.5 60 98.75 37.5

Figure 6: Bar chart showing rate of technology adoption by sorghum farmers (the serial number corresponds with the number on table 25)

5.2.11 Rate of adoption of technologies disseminated to rice farmers As observed from table 26, rice recorded very impressive levels of technology adoption under ATASP-1 project. It was found that improved seed and weed management recorded 100% adoption levels while field preparation, determination of appropriate planting period and crop establishment all recorded about 99% levels of adoption while site preparation and fertilizer application recorded about 98% levels of adoption while the least which was pest and diseases control was 95% level of adoption. This is an indication of the high interest these farmers in dedicatedly joining the train of rice production. Figure 7 presents the graphical presentation of adoption of technologies disseminated to rice farmers under the project, from the figure; it was found that rice farmers have the best technologies adoption rate as there was no technology that has less than 95% rate of adoption. This has raised the hope that we are on course towards becoming a major rice producing nation able to produce enough to meet national demands thus conserving our scarce foreign reserve for better use. Table 26: Rate of adoption of rice technologies S/No 1 2 3 4 5 6 7 8 9

Technologies Improved varieties (Faro 44, Faro 52, Faro 60 and Faro 61 Site/Land preparation Field preparation Seed preparation Determine planting season Crop establishment Weed management Fertilizer application Pest and Disease control

Frequency* 80 78 79 77 79 79 80 78 76

Figure 7: Bar chart showing rate of technology adoption by rice farmers (the serial number corresponds with the number on table 26) 51

Percentage 100 97.5 98.8 96.3 98.8 98.8 100 97.5 95.0

5.3 Effects of Adoption of Good Agronomic Practices (GAP) on crop production Adherent to good agronomic practices are very important to the realization of any crop production objectives and that is one of the reasons why ATASP-1 project has imbibed these practices as a way of educating farmers to enable them up their productivity. Consequent upon this, one of the objectives of this study is the evaluation of the effects of good agronomic practices on the production of crops under the project namely cassava, sorghum and rice. 5.3.1 Effects of adoption of Good Agronomic Practices (GAP) on crop production One of the ways of evaluating the effects of good agronomic practices introduced by ATASP-1 is by looking at the yield before and after the project. The result from this is presented in table 27. From table 27, the average yield of cassava before ATASP-1 project was 9442.105Kg/ha whiles the average yield after the project was almost double at 16259.44Kg/ha. Subjecting these yields to T-statistic test revealed that there was statistical significant difference between the yield before and after the project has taken off at I% level of significance. The import of this is that the different in yield can only be attributed to the positive effect of the technologies introduced to farmers by the project. Also looking at table 27, result revealed the yield of sorghum before the project to be 1186.185Kg/ha while the yield after the project was 2450.05Kg/ha. Subjecting these yields to tstatistical analysis showed that there was statistical significant difference between the yield before and after the project has started at 1% level of significant. This significance increase in yield is attributed to the effects of good agronomic practices introduced by the project to the participating farmers. Finally, we also looked at the effect of good agronomic practices introduced to rice producing farmers in the program and it was found that yields before the project was 3210.03Kg/ha while yield after the project was 5384.55Kg/ha. When these yields were subjected to t-statistical test of difference, it was shown that there was statistical significant difference between yield before the project and yield after the project at 1% level of significant. This significance increase in yield is attributable to the effect of good agronomic practices or technologies introduced to the farmers. Graphical presentation of yields before and after ATASP-1 is as shown in figure 8. From the figure, it is very glaring that there is considerable increase in yields after the project implementation by showing the yields were due to project effects for cassava, sorghum and rice.

Table 27: Effect of GAP on cassava, sorghum and rice production Variables Estimate Cassava Sorghum Output Before adoption of GAP Average 9442.105 1186.185 Min 5000 320 Max 18000 6000 SD 3092.31 1135.15 CV(%) 32.752 95.69 Output after adoption of GAP

Average Min Max SD CV(%)

16259.44 9000 25000 4469.934 27.49131

t-statistics ***P<0.001

4.46***

2450.05 365 7500 1890.35 77.15 5.68***

Rice 3210.03 800.00 18750.00 2911.06 90.69 5384.55 1500.00 26250.00 4174.24 77.52 7.16***

Figure 8: Yields of crops per ha before and ATASp-1 implementation in the SCPZs 5.3.2 Effect of GAP on farmers' income per ha (Cassava, Sorghum and Rice farmers) This section discussed the effect of good agronomic practices GAP in participating farmers' income. From the significant improvement recorded in yields after project compared with the yields before project, it is very obvious that there would be significant increase in income. However we have to do these analyses to enable us know how significant the increase in income would be. From table 28, it has been discovered that the income per hectare before project was N472105.3compared with income after project at N812972.2 which was significant at 1% level of probability when subjected to t-statistical difference. The significant increase in income is attributable to project effect that has resulted in significant yields over above the pre-project yields and consequently income.

Also, looking at the same table, the income per ha from sorghum farmer after project was N245005.88 which is significantly higher than income before project that was N118618.46 at 1% level of significance. This more than double income was attributable to the project effect which has resulted in tremendous increase in crop yields per ha compared with the traditional technologies formally in use by these farmers. Finally, looking at the table 28, rice farmers income per ha after project was N703128.95 which is significantly higher that before project income of N417303.47 at 1% level of significance. This significant increase in income is attributable to project effect which has brought about tremendous increase in yields and consequently income for rice farmers. Figure 9 presents the graphical representation of the difference in income of participating farmers before and after ATASP-1 project. From the figure, there is significant increase in income of farmers after ATASP-1 implementation for cassava, sorghum and rice. It is hoped that these increment will be sustained. Table 28: Effect of GAP on farmers’ income of farmer per ha Variables Income before adoption of GAP (? )

Estimate Average Min Max SD CV(%)

Cassava 472105.3 250000 900000 154615.5 32.75022

Sorghum Rice 118618.46 417303.47 32000.00 104000.00 600000.00 2437500.00 113515.71 378438.03 95.70 90.69

Income after adoption of GAP (? )

Average Min Max SD CV(%)

812972.2 450000 1250000 223496.7 27.49131

245005.88 703128.95 36500.00 195000.00 750000.00 3412500.00 189035.82 545552.61 77.16 77.59

t-statistics ***P<0.001

9.38***

7.75***

7.16***

Figure 9: Farmers' income per ha before and after ATASP-1 implementation across SCPZs 5.4 Effects of ATASP-1 on other beneficiaries activities There were also other beneficiaries of ATASP-1 project apart from farmers. These beneficiaries are farm equipment fabricators and processors that participated in the project. They were supported by the project to fabricate machines that can make crop production and processing more efficient. This section evaluated the effect of their participation on their outputs and income. They as discussed from section 5.4.1. 5.4.1 Effects of ATASP-1 on Fabricators outputs From table 29, it was found that fabricators claimed their customers have increased from 10 before their participation in project to 21 after their participation in the project per week. When subjected to t-statistical test of difference, the result showed that there is statistical significant difference between output before and after participation in ATASP-1 project at 1% level of significant. This significant increase in output is attributable to these fabricators participation in ATASP-1 project training and support. Table 29: Effects of ATASP -1 on fabricators outputs Variables Customers Before ATASP -1 Customers after ATASP -1 ***P<0.001

Average 10 21

SD 7.3 13.9

CV 78.26 67.7

t-statistics 3.98***

5.4.2 Effects of ATASP-1 on Processors outputs Table 30 showed that output of processors before and after participation in ATASP-1 program were 3175.40Kg and 5133.02Kg respectively per week. When these were subjected to tstatistical test of difference, it was found that there was statistical significant difference between the two outputs at 10% level of significance. The significant increase in output is attributable to these processors participation in ATSP-1 project due to the benefit of training and support they have received from the project. Table 30: Effects of ATASPA on processors outputs Variables Output Before ATASP -1 Output after ATASP -1 ***P<0.01

Average 3175.40 5133.02

SD 4350.73 6613.93

CV 142.36 126.12

t-statistics 1.88***

5.4.3 Effects of ATASP-1 on the income and wellbeing of participating fabricators Whenever there is increase in output, there is bound to be a concomitant increase in income. The average income of fabricators before participation in ATASP-1 program per month was N65, 812.50 while after participation, the income rose to N121, 208.30 per month. When subjected to t-statistical test of difference, it was discovered that there was statistical significant difference in the two incomes at 1% level of significance. The significant increase in income was due to training and other supports extended to these fabricators. Table 31: Effects of ATASPA on fabricators income Variables Income Before ATASP -1 Income after ATASP -1 ***P<0.001

Average 65812.5 121208.3

SD 60541.38 93449.3

CV 69.41 77.8

t-statistics 2.6***

5.4.4 Effects of ATASP-1 on the income and wellbeing of participating processors Looking at the effects of ATASP-1 participation on the income of processors, it is quite evident that an increase in output will translate to increase in income of the processors. From table 32, the incomes of processors before and after participation in ATASP-1 project were N100385.42 and N207, 390.31 per month. When this was subjected to t-statistical test of difference, it was found that there was statistical significant difference between income before and after participation in the project at 5% level of significant. This significant increase in income was as a result of the participation of these processors in project through training and supports from the project.

Table 32: Effects of ATASPA on proc essors income Variables Income Before ATASP -1 Income after ATASP -1 ***P<0.005

Average 100385.42 207390.31

SD 105246.38 233642.20

CV 108.05 103.63

t-statistics 2.11**

5.4.5 Effects of ATASP-1 on Food security and the overall economic development of the country The objectives of ATASP-1 as conceptualized were to improve food and nutrition security, create jobs and enhance the income and shared wealth of the program beneficiaries on a sustainable basis through rice, sorghum and cassava value chains. From the analyses done in the previous sections, ATASP-1 is in line towards fulfilling these objectives. The program has delivered on considerable increase in yields of the three crops. Cassava is currently around 18.7 tons per ha as against the initial pre-project yields of 12 tons per ha, sorghum is currently around 1.5 tons per ha from the pre-project output of 1 ton per ha while rice is currently 5.6 tons per ha from the preproject yields of around 2 tons per ha. The considerable increases in yields of these staple crops have enhanced food and nutritional capacity of the households of farmers and their communities at large. More so, the annual income of farmers have been more than double the pre-project era making these farmers and their family to be economically better. It has also been realized that the increase in crop yields has have multiplier effects around the various crop value chain actors involved in the value chains including the marketers of crops, transporters, processors, middlemen and wholesalers of crops have increased their businesses in the program areas of the four SCPZs. The equipment fabricators for farm, processors have all increased their patronages and have now better income making their family to be better off than they were before their involvement in project. On the whole, jobs are being created for various actors involved in the production, processing, fabricating, transportation and marketing of these crops thus helping in poverty alleviation across the SCPZs where the project activities are domiciled and across the country in general. It is hoped that at the completion of the project cycle, the entire country would have noticed a remarkable improvement in food security and improvement in the economic benefits for all and sundry. 5.5 Factor Influencing Adoption of cassava Technologies Table 33 presents factors influencing adoption of technologies disseminated to cassava farmers under ATASP-1 project. From the table, there were ten technologies disseminated to cassava farmers under the project. The first technology labeled 'A' is improved crop variety and three of the variables fitted into the regression were found to have significantly influenced adoption of improved variety of crop. Age was found to be significant at xx% level of significance, and age a time is a measure of experience and so the more the age of the farmer the more they will be ready to adopt improved crop variety. Marital status was equally found to be significant at 1% level of significance. This is so because in our traditional culture, married people are considered to be more responsible and ready to ensure they succeed in whatever they do. So a married person will set his mind in realizing maximum yields and as such will be willing to use improved seed that 57

will give him that yield. Lastly, membership of association empowers members to adopt innovation that could bring about improve in productivity and hence membership of association will motivate farmers to adopt planting of improved crop variety. The second technology labeled 'B' is the selection of good site for planting of cassava. Gender, marital status and household size were found to have statistically significantly influenced adoption of site selection by cassava farmers under the project. Any gender be it male or female will be interested in profitable production and selecting good site for production will facilitate good crop development and yields and therefore the relevance of gender in good site selection for cassava production. Married individuals are known to always pursue business with dedication to ensure the best output and hence the significance of marital status in selecting good site for cassava production. Moreover, the household size was found to be significant and this stem from the fact that a man with large household will be interested in profitable production that will enhance availability of food to feed his family and therefore the larger the household the more the willingness to select good location for cassava production. The third technology labeled as 'C' is land preparation technology. Six variables were found to have been statistically significant in influencing the adoption of land preparation technology among cassava farmers under the project. Gender was found to be significant at 1% level and it showed that in either side, any practice capable of facilitating good harvest will be adopted by either of the gender and so there is tendency for either male or female and even youth to adopt land preparation technology that will help to achieve good harvest. It is also to be noted that age is related to experience and hence the older a farmer, the more he will be willing to adopt land preparation technology. Also, married individuals are readily willing to adopt productive technologies and so the response of married person in the study was highly expected. Household size also played significant role in adoption of land preparation as higher size of household will translate to higher adoption of this technology since people with higher household size will be willing to adopt costless technology that will result in higher output. The more the farming experience, the more the prospect of adoption of technology and hence the significant of the adoption of land preparation technology with farming experience. Finally, access to credit facilitates adoption of technologies and hence the more access these farmers have to credit, the more their willingness to adopt good land preparation technology. The fourth technology disseminated to cassava farmers was plant spacing labeled as 'D'. Only gender was the variable found to have been significant determinant of adoption of this technology. Gender be it male or female or youth are interested in higher yield and since appropriate spacing will help to achieve this hence the significance of this variable in adoption determinant. The fifth technology disseminated to cassava farmers was weed management labeled as 'E'. Good control of weed is very important to the realization of good harvest and six variables significantly influenced the adoption of this technology. Gender of which ever divide will adopt technology that will result in better output and hence the adoption of weed controls technology

by gender in this project. Age is related to the level of experience and hence the older a farmer is the more he will be willing to adopt weed management control measure that will help to increase his output and hence the significance of age variable to this technology. Household size equally significantly influenced adoption of weed management technology since labour in the household could have played a role in executing the technology, so the more member there are in the household the more the capacity to implement weed management technology. Credit availability is very important in technology adoption and the higher the access to credit, the more the likelihood of adoption and hence the significant of credit to the adoption of weed management technology by the project participants. The sixth technology is soil fertility management and soil is very important input in productive activity and if the soil is not properly managed, production output will be poor or non existence. Soil fertility technology is labeled 'F' and four variables were significant in the model fitted to this technology. Gender was significant and whether male, female or youth, gender is interested in better yield and since good soil will enhance this, gender of any type will be willing to adopt soil fertility management technology. Similarly, the more education, household size and the more farming experience a farmer has, the more the likelihood of adopting soil fertility management technology that will results in better yields. The seventh technology disseminated to cassava farmers under the project is market harvest labeled as 'G'. the variable age was significant but carries negative sign showing that the more the age of the farmer, the less his knowledge about current day marketing process will be while farmers will lesser age will be better in marketing process. Household size was found to significantly influenced marketing as the more people in the household will drive the demand for money to meet other family needs and there is likelihood of younger members of the household to be more involved in marketing and hence the support of larger household for harvesting and marketing. Finally farmers that have access to credit are more likely to be market oriented in their production approach and hence the more credit a farmer use, the more his orientation to harvesting for market. The eighth technology disseminated to these farmers was yield assessment labeled as 'H'. Age was negatively significant showing that the more the age, the less insight the farmer will have about how to assess yield from his farm. Household size increase knowledge about yield assessment because the younger members of the household could become better in knowing how to handle this and hence the significance of this variable. The more extension contact a farmer has the better he will be in yield assessment technology because he must have been taught this during extension visits. Finally, the more access a farmer has to credit the more his knowledge in various technologies because some credit agencies also have extension arm that educate farmers on various technology and hence the significance of this variable to yield assessment technology. The ninth technology disseminated was conservation of stem labeled as 'I'. Household size was significantly related to the adoption of this technology as members of household could be handy in providing labour to support this conservation technology and hence the positive correlation

between this technology and household size. Also, membership of association was significant and this could be as a result of peer influence because members of association do things together, they receive training together and they also have access to credit and input at cost and as such the positive correlation between adoption of this technology and membership of association. The tenth technology disseminated on cassava production was Record keeping labeled as 'J'. Farm size was significant here and it showed that the bigger the farm, the more probability that a farmer will keep record since farmers that have bigger farms will want to be extra careful to establish production history to guide future production activities. Extension contact was also significant and this means the more the extension contact, the more the record keeping ability is enhanced since education on record keeping must have been part of the training given to farmers by extension agents. Finally, membership of association was equally significant since association members usually have training organized for their members where good production practices are taught to them and hence membership of association must have encouraged the record keeping ability of these farmers.

0.005(0.4) 0.002(0.5)

0.001(0.5)

0.030(1.1)

0.001(0.2) 0.001(1.3) 0.003(0.5) 0.001(0.2) ***, **, * = Significant at 1, 5 and 10 percent Note: A= improved variety, B=site selection, spacing/population E= weed management F=soil fertility G=harvesting/market stems across J=Record keeping

0.004(0.2) 0.002(0.5)

0.009(1.73*)

0.041(1.9*)

0.001(0.5)

0.007(0.7) 0.006(2.1**)

0.017(1.3) 0.008(2.9***)

0.024(0.9)

0.002(1.1)

0.002(0.2) 0.001(0.5)

0.037(2.0) 0.002(0.6)

0.048(2.2**)

0.002(1.5)

0.004(0.3) 0.002(1.0)

0.033(2.2**) 0.006(2.0**)

0.289(4.4***)

0.029(1.6) 0.012(3.6***)

0.253(2.9)

0.025(1.1) -

0.255(4.0***)

0.171(2.2**)

0.329(3.4***)

I= Conservation of

H= yield assessment

0.005(0.6)

0.120(2.2**)

0.007(1.7*)

0.023(0.9) 0.011(1.5)

0.064(1.8) 0.033(4.6***)

0.014(1.0)

D=plant

0.004(0.4)

0.095(1.7*)

0.003(0.6)

0.005(0.2) 0.005(0.7)

0.017(0.5) 0.029(3.8***)

0.147(0.9)

H 0.237(1.6) -0.014(-3.2***)

C= Land preparation,

0.006(0.9)

0.059(1.6)

0.004(1.5)

0.010(0.6) 0.010(2.0**)

0.065(2.6***) 0.017(3.3***)

0.107(1.0)

Factors influencing adoption of cassava technologies D E F G 0.251(3.6***) 0.205(3.5***) 0.187(1.9*) 0.162(1.0) 0.003(1.7) 0.002(1.7*) -0.003(-1.2) -0.009(-2.1**)

Marital status Education Household size Farm size Farming experience Extension contact Access to credit Association

C 0.240(4.3***) 0.003(1.9*)

A 0.091(1.09) 0.005(2.3**)

Variables Gender Age

B 0.252(3.6***) 0.002(1.2)

Analyses of factors influencing adoption of disseminated technologies to

cassava farmers

Table 33:

0.002(2.04**)

0.048(0.78)

0.002(0.55)

0.019(0.63) 0.005(0.59)

0.009(0.23) 0.029(3.51***)

0.169(0.91)

I 0.127(0.79) -0.007(-1.62)

0.024(2.0**)

0.027(0.4)

0.412(3.1***)

0.072(2.4**) 0.004(0.5)

0.053(1.2) 0.004(0.5)

0.091(0.5)

J 0.115(0.7) 0.005(1.01)

5.5.1 Factor Influencing Adoption of Sorghum Technologies Table 34 presents factors influencing adoption of sorghum technologies disseminated in the project areas. For Sorghum, there were six technologies promoted and each of them has been subjected to tobit analysis to test the socioeconomic variables that influence adoption. The first technology A was the dissemination of improved sorghum varieties and it was discovered that gender, age, marital status, and farm size were the factors that influence adoption of this particular technology. Gender was fund to be significant at 1% level and the love of women for this particular crop making them to be the major participant in these zones might be a factor in that direction. It was also found that age was significant at 1% level of significance and the fact that majority of participant across all the zone were within age 20 years to 55years ensure that the production of this crop is in the hands of very agile and capable people that are very strong enough to engage in viable production processes. More so marital status was found to be significant at 1% level of significance and it supported the traditional idea that married people tend to be more committed to performing in a dedicated ways any assignment they choose to engage in and as such people will be ready to engage in adoption of technology that will support efficiency in the performance of their farm business. Finally, farm size was found to be significant and it shows that the bigger a farmer's farm is, the more he will be ready to participate in technology adoption. The technology labeled as B is seed dressing with apron star and there were three variables that significantly influence this technology which are farm size, extension contact and membership of association. It is expected since the chemical for dressing seeds are better used when a farmer have a sizeable farm size to prevent wastage of the chemical, so the bigger a farmer's farm is, the better the incentive to use seed dressing technology. Also, extension contact is known to encourage and educate farmers about the importance of technologies and as such the more extension contacts/visits a farmer has the more his/her probability that he/she will adopt innovation. More so, membership of association are known to encourage adoption since some of the technologies like seed dressing are better learnt under joint association training and are also better used together since a group of farmer could buy the chemical and use it jointly when it would have been difficult for each farmer to afford such technology, so membership of association tends to encourage the adoption of technology at farm level. The third technology under sorghum labeled as C is the use of the right plant population and gender, age, marital status and association membership were found to be significant factors that influence adoption of this technology. This is very important since yield correlate with the plant population on the farmer's field. Five variables significantly influence the adoption of right plant population on the farm. These are gender, age, marital status and membership of association. It is evident that male or female will want to maximize output and therefore either sex will want to plant the right plant population to achieve this. More so older people will know the advantage of the right plant population since it will encourage higher yields. The farm size is equally related since farmers with bigger farms will be willing to adopt all known technologies that will enhance his return from his investment. Finally, membership of association enhances adoption since association membership enhances training of members and also provides financial support for

adoption. So being members of association will encourage adoption of the right plant population. The fourth technology disseminated to cassava farmers under the project was D technology referred to as minimum tillage and three variables were found to significantly influence these technology. They are household size, farming experience and membership of association. Family size plays an important role in technology adoption as too many people in the family may engender financial constraint that can limit technology adoption and in the case of minimum tillage, higher family size may encourage this since farmer will be spending less on labour. Also, farming experience will encourage adoption of minimum tillage since long time experience may have enable farmer to understand the advantage of this technology in terms of erosion prevention. More so, memberships of association are known to encourage adoption of technologies because group training and peer influence tend to stimulate adoption of technology. The fifth technology E is fertilizer micro dosing of organic with inorganic fertilizer and gender, age, marital status and farm size significantly influence the adoption of this technology. Farmers of all gender will use fertilizer because of the belief that it would increase their crop yield, while the more the age of the farmer, the more knowledge he would have on the positive attribute of fertilizer and the more the adoption. More so married individual takes serious increase in returns from production and will therefore use fertilizer since it will increase their yields. Finally, bigger farm size will encourage farmer to invest in fertilizer usage because they know the effect on output. The sixth technology disseminated to cassava farmer was F known as mechanization. This technology was significantly influenced by marital status and extension contact. Married individuals are considered to be adult laden with wisdom and able to adopt whatever innovation that will increase benefits accruing to his family and as such will be willing to adopt mechanization for larger production and outputs. Finally, extension contact would have schooled the farmer about the advantage of mechanization and hence the more the extension contacts the more the adoption of mechanization technology.

0.006(1.85*) 1.13e-06(1.56) 0.016(2.36**)

0.006(3.84***) 0.223(4.00***) 0.008(0.53) 0.001(0.25) 0.040(1.91*) 0.002(0.99)

0.001(0.51) 0.013(0.93) 0.003(0.63)

Age Marital status Education Household size Farm size Farming experience Extension contact Access to credit Association 0.003(1.46) 0.0004(0.02) 0.002(0.54)

0.004(2.46**) 0.167(2.77***) 0.007(0.41) 0.003(0.70) 0.048(2.10**) 0.003(1.40)

C=Plant population: 0.75x

0.006(1.47) 0.039(0.92) 0.015(1.83*)

0.002(0.59) 0.028(0.23) 0.041(1.16) 0.017(1.76*) 0.009(0.19) 0.008(1.67*)

B=Seed dressing with Apron Star

0.002(0.99) 0.021(1.38) 0.016(2.36**)

0.009(3.98***) 0.209(3.49***) 0.015(0.91) 0.005(0.97 0.016(2.02**) 0.001(0.64)

D= Tillage: Minimum Tillage (use of herbicides E= Fertilizer application: Micro dosing of organic and inorganic fertilizer F=Mechanization

A = Improved seed variety (specify) 0.3m2 plants per hill

***, **, * = Significant at 1, 5 and 10 percent

-0.002(-0.08) 0.145(1.33) 0.038(1.40) 0.002(0.25) 0.094(2.69***) 0.003(0.73)

A 0.142(2.55***)

Variables Gender

Factors influencing adoption of Sorghum technologies B C D E 0.069(0.66) 0.136(2.26**) -0.031(-0.26) 0.158(2.61***)

Table 34: Analyses of factors influencing adoption of disseminated technologies to sorghum farmers

0.007(2.34**) 0.012(0.52) 0.002(0.28)

0.0006(0.22) 0.186(1.98**) 0.026(1.01) -0.004(-0.47) 0.004(0.10) 0.001(0.22)

F 0.105(1.12)

5.5.2 Factor Influencing Adoption of rice Technologies There were nine technologies disseminated to participants of rice under ATASP-1 project. Each of these technologies was subjected to tobit analyses to evaluate factors influencing their adoption. From table 35, it was found that for the first seven technologies none of the variables fitted to the tobit regression was significant indicating that they may not have been able to influence the adoption of these technologies. These technologies that variables fitted into their models were not significant were A which is improved crop variety, B which is site selection/ land preparation, C is field preparation, D is seed preparation, E is planting date determination, F is crop establishment, G is weed management. We could not establish serious relationship between these technologies and the variables fitted into them. However, H which is fertilizer application had seven of the nine variables fitted into the model to be significant. Gender was found to be significant at 1% level and whatever is the sex of the individual involved in production of rice will have interest in higher yields and therefore will be encouraged to use fertilizer to boost yield and hence the use of fertilizer by these farmers. Marital status was equally significant in influencing adoption of fertilizer usage by rice farmers under the project as it is known that married individual are known to be very responsible willing to get maximum returns from whatever investment they engaged in. Also, education was found to significantly influenced adoption of fertilizer in rice production since educated people tend to know and understand that fertilizer increase output in agriculture so the more educated a farmer is the more he will be willing to use fertilizer. Farming experience is another variable that significantly influence fertilizer adoption in rice. The more experience a farmer is the more will be his understanding about the ability of fertilizer to boost crop production and the more will be the willingness to adopt fertilizer in rice production. Other important factor is credit. Credit facilitate adoption of technologies as credit is needed to buy necessary input like fertilizer, so the more access to credit a farmer has the more fertilizer he will use. Finally, membership of association is known to facilitate adoption of technologies as inputs like seeds and fertilizers and agrochemicals are usually obtained at costs through association. So being a member of association will facilitate adoption of fertilizer in rice production.

-0.018(-0.37) 0.048(3.87) 0.008(1.75) 0.003(0.26) 0.004(1.81) 0.004(2.42) 0.004(0.87) 0.010(0.54)

0.131(3.42) 0.039(3.45) 0.0001(0.03) 0.013(1.24) 0.003(1.44) 0.0001(0.06) 0.008(1.7) 0.018(1.06)

0.026(1.27)

0.005(0.87)

0.001(0.31)

0.002(0.59)

0.008(0.63)

0.006(1.16)

0.147(3.11) 0.046(3.34)

0.286(4.11) 0.001(0.56)

0.028(1.41)

0.003(0.55)

0.003(1.72)

0.003(1.06)

0.004(0.32)

0.0001(0.01)

-0.061(-1.05) 0.045(3.3)

0.274(3.99) 0.009(3.85)

0.031(1.74*)

0.008(1.67*)

0.0001(0.22)

0.004(1.79*)

0.016(1.36)

-0.003(-0.7)

0.116(2.81***) 0.052(4.33***)

0.288(4.74***) 0.003(1.44)

A= Improved varieties (Faro 44, Faro 52, Faro 60 and Faro 61, B=Site/land preparation, C=Field preparation D=Seed preparation, E=determining planting season, F=crop establishmentG=weed management H=fertilizer application, I=pests and disease control

0.297(4.74) 0.006(2.78)

0.282(4.99) 0.004(2.13)

Factors influencing adoption of rice technologies C D E F

Variables A B 0.302(5.47) Gender 0.302(5.75) 0.301(5.75) 0.003(1.7) Age 0.005(2.88) 0.003(2.88) 0.138(3.68) Marital status 0.135(3.78) 0.138(3.78) 0.039(3.59) Education 0.030(2.91) 0.039(2.91) 0.004(1.06) Household size 0.002(0.44) 0.004(0.44) 0.004(0.43) Farm size 0.015(1.5) 0.004(1.50) 0.003(1.21) Farming experience 0.002(1.02) 0.002(1.02) 0.001(0.44) Extension contact 0.001(0.64) 0.001(0.64) 0.007(1.62) Access to credit 0.005(1.19) 0.007(1.19) 0.012(0.76) Association 0.014(0.92) 0.012(0.92) ***, **, * = Significant at 1, 5 and 10 percent

farmers

Table 35 : Analyses of factors influencing adoption of disseminated technologies to rice

0.0236(1.13)

0.0005(0.09)

0.0004(0.17)

0.0004(0.16)

0.0233(1.75*)

-0.0007(-0.14)

0.1486(3.09***) 0.0389(2.76***)

0.3224(4.56***) 0.0036(1.56)

5.6

Constraints militating against the adoption of Good Agronomic Practices by cassava farmers There were many constraints militating against the adoption of good agronomic practices by cassava farmers under ATASP-1 project as conceptualized in the study. From the analyses in table 36a, it was found that of all the constraints analyzed, 12 were found not to be severe in their ability to hinder adoption of good agronomic practices amongcassava farmers that were sampled. For the purpose of understanding these analyses, weighted score that are less than 3 indicate not severe. From this, we have those constraints that were severe to be (i) low motivation and incentive to implement GAP as factors that hinder adoption of GAP, (ii) the absence of direct links with market by farmers while (3) is small number of large export companies and the (4) and the last was the shortage of skill labour for cassava production. Apart from these four that were found to be critical, all the other envisaged constraints in table 36a were found not to be severe against adoption of good agronomic practices introduced to cassava farmers to enhance cassava yields and productivity in the project areas. There is therefore the need for the project to work harder to address these four constraints to enhance optimal productivity of cassava in the project areas in particular and the country in general.

Table 36a: Constraints militating against the adoption of Good Agronomic Practices cassava farmers Constraints

Very severe

Severe

Mild severe

Not severe

Not a problem

Weighted score

Insufficient awareness about safety

9(15)

18(30)

11(18.33)

9(15)

13(21.67)

2.9

Environmental and social problem

13(21.67)

15(25)

16(26.67)

5(8.33)

7(11.67)

2.2

Insufficient knowledge of impact of agricultural practices

3(5)

10(16.67)

19(31.67)

8(13.33)

20(33.33)

2.4

Lack of knowledge and low education

4(6.67)

9(15)

18(30)

6(10)

23(38.33)

2.3

Poor understanding of technology (GAP) requirements

3(3)

10(16.67)

12(20)

17(28.33) 18(30)

2.4

Poor record keeping

11(18.33)

10(16.67)

9(15)

8(13.33)

22(36.67)

2.6

Low motivation and incentives to implement GAP

12(20)

15(25)

14(23.33)

4(6.67)

15(25)

Unhygienic practices in production and food processing

2(3.33)

9(15)

18(30)

13(21.67) 16(26.67)

2.7

No direct links with market

20(33.33)

21(35)

6(10)

7(11.67)

3.6

Small number of large export companies

13(21.67)

26(43.33)

8(13.33)

9(15)

4(6.67)

3.5

Insufficient organization of small growers in producers association

7(11.67)

11(18.33)

22(36.67)

8(13.33)

12(20)

2.8

Inappropriate use of pesticides

8(13.33)

12(20)

14(23.33)

12(20)

14(23.33)

2.7

Shortage of skill labour

13(21.67)

14(23.33)

17(28.33)

6(10)

10(16.67)

3.2

Poor understanding of the role of GAP

4(6.67)

14(23.33)

7(11.67)

21(35)

2.5

Insufficient dialogue with stakeholders

14(23.33)

10(16.67)

14(23.33)

12(20)

10(16.67)

2.9

Insufficient outreach and lack of coordination in training

2(3.33)

5(8.33)

17(28.33)

15(25)

21(35)

2.2

Figures in parentheses are percentages Note: weighted score less than 3.0 indicates not severe

5.6.1 Constraints militating against the adoption of Good Agronomic Practices among sorghum farmers There were equally 16 envisaged constraints that could militate against adoption of good agronomic practices by sorghum farmers in various zones under the project. These constraints are presented in table 36b. From the table all these constraints have weighted scores that were less than 3 meaning that none of them have severities in their ability to hamper adoption of agronomic practices disseminated to sorghum farmers. It does appear from the results in the table 68

that farmers have less to worry about in deciding to adopt good agronomic practices introduced to them for sorghum production. This is also consistent with the nature of this crop that is considered to be very tolerant and can even survive in marginal land and under considerable low rainfall regime.

Table 36b: Constraints militating against the adoption of Good Agronomic Practices among sorghum farmers Constraints

Very severe

Severe

Mild severe

Not severe

Not a problem

Weighted score

Insufficient awareness about safety

4(5)

13(16.25)

18(22.5)

25(31.25)

20(25)

2.45

Environmental and social problem

6(7.5)

12(15)

10(12.5)

17(21.25)

34(42.5)

2.23

Insufficient knowledge of impact of agricultural practices

8(10)

7(8.75)

24(30)

12(15)

29(36.25)

2.4

Lack of knowledge and low education

8(10)

19(23.75)

20(25)

16(20)

13(16.25)

2.8

Poor understanding of technology (GAP) requirements

7(8.75)

14(17.5)

10(12.5)

21(26.25)

28(35)

2.37

Poor record keeping

13(16.25)

15(18.75)

17(21.25)

24(30)

11(13.75)

2.9

Low motivation and incentives to implement GAP

10(12.5)

9(11.25)

20(25)

22(27.5)

19(23.75)

2.5

Unhygienic practices in production and food processing

2(2.5)

12(15)

23(28.75)

22(27.5)

21(26.25)

2.47

No direct links with market

9(11.25)

13(16.25)

20(25)

21(26.25)

2.62

Small number of large export companies

13(16.25)

16(20)

13(16.25)

15(18.75)

23(28.75)

2.75

Insufficient organization of small growers in producers association

12(15)

10(12.5

17(21.25)

25(31.25)

16(20)

2.7

Inappropriate use of pesticides

8(10)

18(22.5)

16(20)

14(17.5)

24(30)

2.625

Shortage of skill labour

8(10)

17(21.25)

9(11.25)

20(25)

26(32.5)

2.5

Poor understanding of the role of GAP

12(15)

19(23.75)

25(31.25)

2.55

Insufficient dialogue with stakeholders

6(7.5)

11(13.75)

19(23.75)

15(18.75)

29(36.25)

2.375

Insufficient outreach and lack of coordination in training

16(20)

13(16.25)

9(11.25)

42(52.5)

2.025

Figures in parentheses are percentages

Note: weighted score less than 3.0 indicates not severe

5.6.2 Constraints militating against the adoption of Good Agronomic Practices for rice production The envisaged constraints that could militate against the adoption of good agronomic practices introduced to rice farmers are presented in table 36c. From the table, we have 16 envisaged constraints and only one of them crossed the threshold of 3.0. From this, it means the constraint that has the capacity to hinder adoption of GAP is small number of large export companies to export rice from Nigeria to other countries. Looking at this constraint, one should rather not lose sleep over it since we are yet to attain ability to produce enough for local consumption talk less of exporting. Nigeria has the largest market for rice in Africa and we need to up our production in terms of quantity and quality to enable us meet national demand.

Table 36c:

Constraints militating against the adoption of Good Agronomic Practices among rice farmers

Constraints

Very severe

Severe

Mild severe

Not severe

Not a problem

Weighted score

Insufficient awareness about safety

3(3.8)

9(11.3)

13(16.3)

18(22.5)

35(42.8)

2.0

Environmental and social problem

3(3.8)

20(25.0)

17(21.3)

23(28.8)

2.5

Insufficient knowledge of impact of agricultural practices

3(3.8)

8(10.0)

15(18.8)

28(35.0)

2.1

Lack of knowledge and low education

2(2.5)

20(25.0)

8(10.0)

25(31.3)

2.3

Poor understanding of technology (GAP) requirements

2(2.5)

13(16.3)

9(11.3)

19(23.8)

37(46.3)

2.0

Poor record keeping

9(11.3)

23(28.8)

13(16.3)

15(18.8)

20(25.0)

2.8

Low motivation and incentives to implement GAP

9(11.3)

14(17.5)

19(23.8)

17(21.3)

16(20.0)

2.8

Unhygienic practices in production and food processing

8(10.0)

17(21.3)

15(18.8)

19(22.5)

22(27.5)

2.7

No direct links with market

7(8.8)

16(20.0)

24(30.0)

17(21.3)

2.6

Small number of large export companies

13(16.3)

20(25.0)

18(22.5)

10(12.5)

18(22.5)

3.0

Insufficient organization of small growers in producers association

3(3.8)

23(28.8)

15(18.8)

14(17.5)

28(35.0)

2.6

Inappropriate use of pesticides

3(3.8)

15(18.8)

13(16.3)

27(33.8)

23(28.8)

2.4

Shortage of skill labour

6(7.5)

21(26.3)

17(21.3)

21(26.3)

10(12.5)

2.5

Poor understanding of the role of GAP

7(8.8)

10(12.5)

13(16.3)

21(26.3)

29(36.3)

2.1

Insufficient dialogue with stakeholders

7(8.8)

9(11.3)

11(13.8)

20(25.0)

33(41.3)

2.2

Insufficient outreach and lack of coordination in training

9(11.3)

16(20.0)

39(48.8)

1.9

Figures in parentheses are percentages Note: weighted score less than 3.0 indicates not severe

5.7

CONCLUSION AND RECOMMENDATIONS

5.7.1 Conclusion The study revealed that substantial numbers of technologies were disseminated on each crop being promoted under ATASP-1 project and the adoption rate of these technologies were very high except with a few like mechanization, conservation of stem, record keeping, yields assessment that recorded low rate of adoption. It was equally discovered that the effect of adoption on crop yields have been very substantial in terms of improvement in the yields of cassava, sorghum and rice and the yields difference before and after ATASP-1 project were significant at 1% level of probability. For cassava, it was 9.44tons before versus 16.26tons after, for sorghum, it was 1.191ton versus 2.45tons after while for rice, it was 3.2tons versus 5.38 tons after ATASP-1. These increases in yield were due to mainly to project effects. These yields increase has equally precipitated substantial increase in revenues and has thus changed the economic status of these farmers. There were noticeable increments in the activities of processors and fabricators as well as other stakeholders in these communities leading to overall improvement in their wellbeing. Finally, the envisaged constraints were not really severe to warrant negative impact on adoption of technologies being promoted on each crop and as such it could be concluded that the project is on course in a bid to facilitate smooth adoption of technologies being disseminated on these crops. However, it was discovered that there were poor access to credit by these farmers and this could hamper progression in sustained adoption by these farmers and consequently impaired productivity of these crops. 5.7.2 Recommendations Based on the findings of this study, the following recommendations are made to strengthen and further improve the performance of the project as follows: i. Credit is a lubricant for the adoption of innovation. In view of the poor availability of credit to these farmers, it is recommended that farmers should be given better access to credit to stimulate adoption of disseminated technologies and consequently productivity of these farmers; ii. Participation of these farmers in innovation platform was very poor while participation in field day for cassava farmers was marginally good enough. There is need to strengthen these very important means of disseminating technologies to enhance better understanding of technologies by these farmers to facilitate better adoption across the SCPZs and the country in general; iii. Emphases should be laid on those technologies that have low adoption rate presently with a view to improving their adoption rate. These areas of low rate of adoption are mechanization, records keeping, harvesting for market, yield assessment. Improvement in these identified low areas of adoption will help farmers to be in better position for enhanced productivity; iv. There is need for continues training of farmers on the importance of these technologies as 71

well as techniques behind their utilization to help these farmer to continue to adopt them; There is need to encourage women the more to participate in the project as well as encourage them to take up farming as a business.

REFERENCES African Agricultural Technology Foundation, AATF (2017).Cassava Mechanization and Agro-processing Project. Retrieved on 4/11/17 from https://www.aatfafrica.org/Cassava-Mechanizsation-Agro-Processing-Project African Development Bank (2013). Agricultural Transformation Agenda Support Program – Phase 1 Strategic Environmental and Social Assessment. Retrieved on 10/3/2018 from https://www.afdb.org/fileadmin/uploads/afdb/Documents/Environmental-andSocial-Assessments/Nigeria%20%20Agricultural%20Transformation%20Agenda%20Support%20Program%20%E2% 80%93%20Phase%201%20%28ATASP-1%29%20%20Executive%20SESA%20Summary.pdf African Development Bank (AfDB), (2013). Agricultural Transformation Agenda Support Program Phase 1, Strategic Environmental and Social Assessment. ATASP-1 (2017).ATASP-1 News, January – March, 2017. Retrieved on 11/3/2018 from http://www.iita.org/wp-content/uploads/2017/05/ATASP-news_Jan-March-2017.pdf FAO, (2004).United Nations Food and Agriculture Organization.Retrieved from http://faostat.fao.org. Federal Ministry of Agriculture & Rural Development, (2011). Agricultural Transformation Agenda: We Will Grow Nigeria's Agriculture Sector. Federal Ministry of Agriculture & Rural Development, (2016). Agriculture Promotion Policy 2016-2020, Area 11, FCT, Abuja. Federal Ministry of Budget and National Planning, (2017).Economic Recovery and Growth Plan, FCT Abuja, Nigeria. Inter reseaux (2015). Staple Crop Production and Consumption: Nigeria on the Way to Food Self-sufficiency. Retrieved on 4/11/17 from http://www.interreseaux.org/publications/revue-grain-de-sel/51-special-issue-nigeria/article/staplecrop-production-and Merem, E. C., Twumasi, Y., Wesley, J., Isokpehi, P., Shenge, M., Fageir, S., Crisler, M., Romorno, C., Hines, A., Hirse, G., Ochai, S., Leggett, S. &Nwagboso, E. (2017).Analyzing Rice Production Issues in the Niger State Area of Nigeria's Middle Belt.Food and Public Health 7(1): 7-22.

FEDERAL MINISTRY OF AGRICULTURE AND RURAL DEVELOPMENT AGRICULTURAL TRANSFORMATION AGENDA SUPPORT PROGRAM PHASE-1 (ATASP-1) 12A ATBARA STREET, OFF CAIRO STREET. OFF DETOKUNBO ADEMOLA CRESCENT WUSE II, FCT, ABUJA

Survey Questionnaire for theAssessment of Adoption of Improved Technologies amongst ATASP -1 Beneficiaries in Nigeria

ANNEXURES Annexure 1: Farmers questionnaire (A)

Background Information

A.1 Questionnaire number…………………………………………………….. A.2 Name of farmers (optional)……………………………………………… A.3 Name of Group………………………………………………………………… A.4 Cropping Enterprise: Rice ( ), Sorghum ( ), Cassava ( ) A.5 SCPZ:……………………………………………. A.6 State……………………………………………. A.7 LGA………………………………………. A.8 Community……………………………………………………………………………………….. A.9 Interview date: ..............................................................….../__/__/__/__/__/__/__/__/ (ddmmyyyy) A.10 Name of the Enumerator ………………………………………………………………….

(B) Socio-economic characteristics of farmers B.1Household structure Gender 1= male 2=female

Age of Household (HH) Head (years)

Marital Status 1=Married 2= Single 3=Others

Education level of HH Head (code1)

Household size (number)

No of wife/wives

Number of Children < 18years

Number of adult children >18 yrs

Others living with you

Code1: Education level 0=none ; 1= Koranic ; 2=primary, 3=junior secondary school, 4=senior secondary school, 5=tertiary, 6= other (specify)

B 2) Information on farmers’ plot

B2.2 What is the total size of your farm holding?………………………………………….ha Complete the table below on your farm size and experience 1 Crop Mode of acquisition Size of land (ha) Years of cropping experience Cassava Rice Sorghum 1

Mode: 1 = Inheritance 2=Purchase 3 = Rent 4=Lease 5 =Gift 6=Others (specify) ha: enumerators should be mindful of conversion 2.5 acre = 1ha, about 7000 big heaps = 1ha, 10000 small heaps = 1ha

B3 Extension Contact B3.1 Did extension staff visit you last growing season? Yes ( ) No ( ) B3.2 If yes, how many times did extension staff visit you last cropping season......................... B3.3Did you participate in the Innovation Platform? Yes ( ) No ( ) B3.4 Did you participate in demonstration plots? Yes ( ) No ( ) B3.5 Did you participate in farmers’ field day? Yes ( ) No ( ) B4.Credit information for the last cropping season 1 Access to Source of Credit required Credit received 1 credit credit (N) (N)

Nature of credit

Yes = 1

Cash=1

No = 0

Kind=2

What was the money used for?

Credit source: 1=credit program, 2= commercial bank, 3=cooperatives 4=NGO, 5=traders, 6=agricultural bank 7=family and friends 8= other (specify) 2 What was the money used for : 1=input purchase, 2=agricultural activity, 3=commerce, 4=health care, 5=purchase of food, 6=social functions, 7=other expenses (specify)

B5. Farmers’ association Membership Years of participation Yes = 1 No=0

Name of the association

Benefit derived from the association

Benefit: 1= Access to inputs, 2= Credit, 3= training, 4= Labour, 5= Information, 6=Marketing, 7= Others (specify) B6. Access to agricultural training Have you when did Where ever had you get did you any the get training training training? on (Year/s) farming? Yes = 1

Who organized the training?

What aspects of production were you trained in?

what aspects of production would you like to receive additional training

No = 0

C. Production information C1.Input used in sorghum production Quantity of seed (kg)

Total Price of seed/kg (N)

(i) (ii)

Quantity of insecticides used (litre)

Total cost of Insecticide (N)

Quantity of herbicide used (litre)

Total cost of Herbicides (N)

Quantity of hired labour (man-day)

Unit cost (N)

Quantity of family labour

Unit cost (N)

output kg

Price/ kg (N)

C2. Indicate the quantity of fertilizer used ……………………………… (Kg). C3. Cost per Kg__...................................................Naira

D. Production information D1.Input used in rice production Quantity of seed (kg)

Total Price of seed/kg (N)

Quantity of insecticides used (litre)

Total cost of Insecticide (N)

Quantity of herbicide used (litre)

Total cost of Herbicides (N)

Quantity of hired labour (man-day)

Unit cost (N)

Quantity of family labour

Unit cost (N)

Yield kg

Price/k g (N)

D2. Indicate the quantity of fertilizer used a …………………..(Kg).D3. Cost per Kg___________ Naira (E) Production information E1. Input used in cassava production Quantity of cuttings (Bundles)

Total Price of cutting/ bundle (N)

Quantity of insecticide s used (litre)

Total cost of Insecticide (N)

Quantity of herbicide used (litre)

Total cost of Herbicides (N)

Quantity of hired labour (man-day)

Unit cost (N)

Quantity of family labour

Unit cost (N)

Yield kg

Price/ kg (N)

E2. Indicate the quantity of fertilizer used ……………………(Kg).E3. Cost per Kg___________Naira F1. Improved Technologies Disseminated on Sorghum F1.1.Are you aware of any of the following technologies on Sorghum? S/N Technologies Disseminated Awareness 1Source of Indicate(Yes/No) Status awareness if you practice (Yes =1; any No=2) 1 Improved seed variety (Specify) 2 Seed dressing with Apron 3 4 5

Star Plant population: 0.75 x 0.3m 2 plants per hill. Tillage: minimum Tillage (use of herbicides) Fertilizer application: Microdosing of organic and inorganic fertilizer Mechanization

6 8 1 Source: ATASP_1, =1, ADP = 2, NGOs =3, Other Farmers =4 , Others (Specify) =5 2 . Very Useful = 4, Useful =3, Rarely Useful =2, Not Useful =1

Perception of usefulness of Technology

F2. Technologies Disseminated on Rice F2.1 Are you aware of any of the following technologies on Rice? S/N

Technologies Disseminated

Improved varieties (Faro 44, Faro52, Faro 60 and Faro 61) Site/Land Preparation Field Preparation Seed Preparation Determining planting season Crop establishment Weed management Fertilizer application Pests and Diseases control

2 3 4 5 6 7 8 9

Awareness Status (Yes =1; No=2)

Source of awareness

Indicate (Yes/No) if you practice any

Perception of usefulness of Technology

Source: ATASP_1, =1, ADP = 2, NGOs =3, Other Farmers =4 , Others (Specify) =5 2. Very Useful =4, Useful =3, Rarely Useful =2, Not Useful =1 F3. Technologies Disseminated on Cassava F3.1 Are you aware of any of the following technologies on Cassava? S/N Technologies Disseminated Awareness Source of Indicate (Yes =1; Awareness (Yes/No) if you No=2) practice any 1 Use of improved varieties 2 Site Selection 3 Land Preparation 4 Plant Spacing/Population 5 Weed Management 6 Soil Fertility Management 7 Harvesting Market 8 Yield Assessment 9 Conservation of stems

across off-season Record keeping

10 1 Source: ATASP_1, =1, ADP = 2, NGOs =3, Other Farmers =4 , Others (Specify) =5 2. Very Useful =4, Useful =3, Rarely Useful =2, Not Useful =1

Perception of usefulness of Technology

G1. Indicate your mode of practicing these extended technologies on sorghum production S/N TECHNOLOGIES Mode of practice (code) 1 Improved seed variety (Specify) 2 Seed dressing with Apron Star 3 Plant population: 0.75 x 0.3m 2 plants per hill. 4 Tillage: minimum Tillage (use of herbicides) 5 Fertilizer application: Micro-dosing of organic and 6

inorganic fertilizer Mechanization Others Specify I Ii iii. Code: 5 = Regularly, 4 = often, 3 = sometime, 2 = rarely, 1 = never

G2. Indicate your mode of practicing these extended technologies on rice production S/N TECHNOLOGIES Mode of practice (code) 1 Improved varieties (Faro 44, Faro52, Faro 60 and 2 3 4 5 6 7 8 9

Faro 61) Site/Land Preparation Field Preparation Seed Preparation Determining planting season Crop establishment Weed management Fertilizer application Pests and Diseases control Others (specify) i Ii iii. Code: 5 = Regularly, 4 = often, 3 = sometime, 2 = rarely, 1 = never

G3. Indicate your mode of practicing these extended technologies on cassava production S/N TECHNOLOGIES Mode of practice (code) 1 Use of improved varieties 2 Site Selection 3 Land Preparation 4 Plant Spacing/Population 5 Weed Management 6 Soil Fertility Management 7 Harvesting Market 8 Yield Assessment 9 Conservation of stems across off-season 10 Record keeping Others (specify) i ii iii. Code: 5 = Regularly, 4 = often, 3 = sometime, 2 = rarely, 1 = never

H. Practice of Technologies (Good Agronomic Practices, GAP) were based on the following reasons GAP Rank (Code Labour saving Higher yield Soil moisture retention Soil erosion control Enhancement of soil fertility Climate change adaptation Others (specify) 3 = agree, 2 = Not sure, and 1 = disagree

I. Constraints to adoption of Technologies (Good Agronomic Practices, GAP) Constraints Rank (Code) Insufficient awareness about safety environmental and social problem, Insufficient knowledge of Impact of agricultural practices lack of knowledge and low education poor understanding of technology (GAP) requirements, poor record keeping, low motivation and incentives to implement GAP, unhygienic practices in production and food processing, No direct links with markets. small number of large export companies, Insufficient organization of small growers in producers associations,

inappropriate use of pesticides, shortage of skill labour, poor understanding of the role of GAPs, insufficient dialogue with stakeholders, Insufficient outreach and lack of coordination in training. Production Constraints Product market Long distance to market Low prices for rice Low price for cassava Low price for sorghum High transport cost Lack of market/demand for product Extension services Unavailability of extension services Lack of effectiveness Long distance to the extension workers Others Problem of pest and diseases Poor roads network Inadequate capital Inadequate land Code= 5 = very severe, 4= severe, 3 = mildly severe, 2 = not severe, and 1 = not a problem J. Output from Crop Enterprise S/No Crops Output (Kg) 1 Rice Output before adoption of GAP

Output (Kg) Output after adoption of GAP

Sorghum

Output before adoption of GAP

Output after adoption of GAP

Cassava

Output before adoption of GAP

Output after adoption of GAP

Survey checklists for the assessment of the adoption of improved technologies amongst Processors under ATASP -1 Focus Group Discussion

Annexure 2: Processors FGD questionnaire (A)

Background Information

Questionnaire number…………………………………………………….. Name of Group………………………………………. Name of the Enumerator …………………………………………………………………. SCPZ:……………………………………………. 1 State……………………………………………. Source: ATASP – 1 =1, LGA………………………………………. ADP =2, NGOs =3, Other processors =4, Others (specify) =5 Community………………………………….. 1.date: Awareness and usage of rice Processing Technologies extended by ATASP -1 Interview .................................................................….../__/__/__/__/__/__/__/__/ (ddmmyyyy)

CHECKLISTS FOR PROCESSORS 1.

Awareness and usage of sorghum Processing Technologies extended by ATAS P-1 1 Sources of Awareness of Usage of awareness S/N List of Technologies Technologies Technologies of (Yes=1,No=2) % technologies 1 2 3 4 5 6 7

Harvesting, threshing, cleaning and packaging of sorghum Effective Sorghum drying techniques (i.e of Solar dryer) Storage of Sorghum grains and flour for enhanced shelf life Production of Pop Sorghum Production of Sorghum flour using hammer mill with Cyclone Production of composite flour using Soya bean flour and sorghum flour Other: Specify 1

Source: ATASP – 1 =1, ADP =2, NGOs =3, Other processors =4, Others (specify) =5

2. Awareness and usage of rice Processing Technologies extended by ATASP -1 1

S/N

1 2 3 4 5 6 7

List of Technologies

Awareness of Technologies (Yes=1,No=2)

Sources of awareness of technologies

Usage of Technologies %

Seed processing package and storage Improved rice processing technology Production of high quality rice flour Production of rice flour based products Production of rice beverages Production of extruded rice snacks Other: Specify

Source: ATASP – 1 =1, ADP =2, NGOs =3, Other processors =4, Others (specify) =5

1. Awareness and usage of cassava processing technologies extended by ATASP -1 1 Sources of Usage of Awareness of awareness Technologies S/N List of Technologies Technologies of % (Yes=1,No=2) technologies 1. 2. 3. 4. 5

Processing of Cassava into garri Processing of Cassava and starch Production of Cassava chin -chin and doughnut Production of Cassava/bean crisp and eggroll Other: Specify

Source: ATASP – 1 =1, ADP =2, NGOs =3, Other processors =4, Others (specify) =5

4. What are the support you have received from ATASP -1? ………………………………………………………………………………………………………………………………………… ……… 5. How useful are the support received under ATAP -1? …………………………………………………………………………………………………………………………………………………… ……… 6. Output from processing enterprise 7. What was your level of patronage before ATASP -1 ? ……………………….

1. What is your level of patronage under ATASP -1 intervention ………………… 2. What was the quantity of output processed before ATASP -1 ? ………………………. Kg 3. What is the quantity of output processed under ATASP -1 intervention ………………… Kg 4. What was your income per month before ATASP -1 ? ………………………. Naira 5. What is your income per month under ATASP -1 intervention ………………… Naira 6. What is your perception of the processing technologies extended by ATASP -1 ? S/N

TECHNOLOGIES

Very Satisfied

Satisfied

Sorghum 1

3 4 5

Fairly Satisfied

Rarely satisfied

Not Satisfied

S/N

TECHNOLOGIES

Very Satisfied

Satisfied

Fairly Satisfied

Rarely satisfied

Not Satisfied

Rice 1 2 3 4 5 6

Cassava 1. 2. 3.

Processing of Cassava into garri Processing of Cassava and starch Production of Cassava chin -chin and doughnut Production of Cassava/bean crisp and eggroll

1. What is your perception of the quality of your processed product(s) under ATASP -1? ……………… (1) Excellent (2) Very Good (3) Good (4) Fair (5) Poor 2. Contribution to infant and Adult nutrition by project (women) a. List food items supported for infant by the project from sorghum i. …………………………………………………………………………………………………… ii.

……………………………………………………………………………………………………

iii.

……………………………………………………………………………………………………

b. List various food fortification produced from Cassava under the project i. …………………………………………………………………………………………………… ii. …………………………………………………………………………………………………… iii.

……………………………………………………………………………………………………

3. What are the constraints to the usage of ATASP -1 Processing technologies? ………………………………………………………………………………………………………………………………………………………… ……………………………………………………………..…………………………………………………………………………………

Survey checklists for the assessment of the adoption of improved technologies amongst Fabricators under ATASP -1 Focus Group Discussion

Annexure 3: Fabricators FGD questionnaire (A)

Background Information

Questionnaire number…………………………………………………….. Name of Group………………………………………. Name of the Enumerator …………………………………………………………………. SCPZ:……………………………………………. State……………………………………………. LGA………………………………………. Community………………………………….. Interview date: ...............................................................….../__/__/__/__/__/__/__/__/ (ddmmyyyy)

CHECKLISTS FOR FABRICATORS 1. Awareness and usage of Fabricators Techno logies extended by ATASP -1 1 Sources of Usage of Awareness of List of awareness Technologies S/N Technologies Technologies of % (Yes=1,No=2) technologies 1 Hand planter 2 3

Mechanized thresher Stover crusher

Stover chopper

Motorize weeder

Source: ATASP – 1 =1, ADP =2, NGOs =3, Other processors =4, Others (specify) =5

18. What are the support you have received from ATASP -1? ………………………………………………………………………………………………………………………………………… ……. 19. How useful are the support received under ATAP -1? ………………………………………………………………………………………………………………………………………………. …………………………………………………………………………………. 20. Patronage and Income from Fabrication Enterprise What was the average number of customers per week before ATASP -1 ? ………………………. What is number of customers per week under ATASP -1 intervention ………………… …………. What was your average income per week before ATASP -1 ? ………………………. What is your average income per week under ATASP -1 intervention? ………………… …………. 21. What is your perception of the fabrication technologies extended by ATASP -1? S/N

TECHNOLOGIES

Very Satisfied

Satisfied

Sorghum 1

Harvesting, threshing, cleaning and packaging of sorghum

Effective Sorghum drying techniques (i.e of Solar dryer)

Storage of Sorghum grains and flour for enhanced shelf life

Production of Pop Sorghum

Production of Sorghum flour using hammer mill with Cyclone

Production of composite flour using Soya bean flour and sorghum flour

Fairly Satisfied

Rarely satisfied

Not Satisfied

S/N

TECHNOLOGIES

Very Satisfied

Satisfied

Fairly Satisfied

Rarely satisfied

Not Satisfied

Very Satisfied

Satisfied

Fairly Satisfied

Rarely satisfied

Not Satisfied

Rice 1

Seed processing package and storage

Improved rice processing technology

Production of high quality rice flour

Production of rice flour based products

Production of rice beverages

Production of extruded rice snacks

S/N

TECHNOLOGIES Cassava

Processing of Cassava into garri

Processing of Cassava and starch

Production of Cassava chin -chin and doughnut

Production of Cassava/bean crisp and eggroll

22. What is your perception of the quality of your fabrication operations under ATASP -1? ……………… (1) Excellent (2) Very Good (3) Good (4) Fair (5) Poor 23. What are the constraints to the usage of ATASP -1 fabrication technologies? …………………………………………………………………………………………………………… …………………………………………………………………………………………………………..

Survey checklists for the assessment of the adoption of improved technologies amongst Fabricators under ATASP -1 Focus Group Discussion

Annexure 4: Interview with a farmer at TungankawoWushishi

Survey checklists for the assessment of the adoption of improved technologies amongst Fabricators under ATASP -1 Focus Group Discussion

Annexure 5: A cassava crusher @ Tsadozhiko Wushishi

Survey checklists for the assessment of the adoption of improved technologies amongst Fabricators under ATASP -1 Focus Group Discussion

Annexure 6: Interview with a female farmer @ TungankawoWushishi

NATIONAL OFFICE

No. 15, Lord Luggard Street, Asokoro, Abuja FCT, Nigeria info@atasp1.gov.ng, atasp1_hq@atasp1.gov.ng 08137208947, 08036551491 www.atasp1.gov.ng ADANI-OMOR ZONE:

BIDA-BADEGGI SCPZ

Emeke Nwosu Street Abuja Estate, Opposite FMARD, Govt House, Enugu -Onitsha Exp Way, Awka, Anambra State. 07081037456 adaniomor@gmail.com

Farm Institute, Ministry of Agriculture and Rural Development, KM 12, Bida-Lemu Express way, Bida, Niger State. 08056039015 mail2manta@yahoo.com

KANO-JIGAWA SCPZ

KEBBI-SOKOTO SCPZ

No. 9, Ahmadu Bello Way, Servicom Center, Kano, Kano State. 08036923665, 08052683453 aadoshehu@yahoo.com

1st Floor Akoko Plaza, Opp. New Central Bank Building, Emir Haruna Road. Birnin-Kebbi, Kebbi State. 07036496038. aliyuaddaji@yahoo.com

Printed @ 08037566629

ZONAL OFFICES

AN ASSESSMENT OF THE ADOPTION OF IMPROVED TECHNOLOGIES AMONGST ATASP-1 BENEFICIARIES IN NIGERIA

Articles inside

Annexure 6: Interview with a female farmers @ TunganKawo, Wushishi

Annexure 5: Acassava crusher @ Tsadozhiko, Wushishi

Annexure 4: Interview with a farmer @ TungaKawo, Wushishi

Table 29: Effects of ATASP-1 on fabricators outputs

Table 36c: Constraints militating against the adoption of Good Agronomic Practices among rice farmers

Table 32: Effects of ATASP-1 on processors income Table 33: Analyses of factors influencing adoption of disseminated technologies

Practices cassava farmers

Table 36b: Constraints militating against the adoption of Good Agronomic Practices among sorghum farmers

Table 28: Effect of GAP on farmers' income

Table 26: Rate of adoption of rice technologies

Table 14: Membership of Associations by farmers

Table 23: Reasons for farmers' adoption of Good Agronomic Practices (GAP

Table 25: Rate of adoption of sorghum technologies

Table 15: Access to agricultural training among rice farmers

Table 16: Input used in crop production

Table 27: Effect of GAP on cassava, sorghum and rice production

Table 12: Distribution of farmers by extension contact and membership of association

Table 9: Land area devoted to the cultivation of each crop

1 Background of contributions to the ATASP-1 Program Development Objectives

Table 4: Educational qualification of the household head

1.3 Purpose of the Study

1.6 Limitations of the Study

1.1 Introduction

Table: 10 Year of experience in farming by farmers

Table 1: Structure of farmer's household across crops in the ATASP-1 Project