nutriFORUM 2019 - Ponencia sobre la aplicación del sistema Cornell en pequeños rumiantes

Page 1

APLICACIÓN DEL MODELO CNCPS (CORNELL) EN PEQUEÑOS RUMIANTES

Prof. Antonello Cannas Department of Agricultural Sciences, University of Sassari, Sardinia, Italy


Outline §  The development of the SRNS §  Prediction of requirements with the SRNS §  SRNS prediction of feed nutritive value §  SRNS nutritive values

§  SRNS evaluation §  SRNS application §  NDF and other CHO optimal values



Why developing the SRNS? Sheep & goat models:

•  more empirical, less flexible than recent cattle systems •  Have simplified body reserve models •  Do not consider dairy sheep (except for INRA) •  Do not account for: –  the effect of intake on feed digestibility (except for AFRC, 1995), animal requirements (except for CSIRO, 2007), microbial efficiency

–  the effect of rumen pH and N balance –  the effects of fiber and non fiber bacteria on digestion –  environmental effects on requirements (except for CSIRO, 2007)


Ewes and goats are not cows 10 2mes smaller !

Sheep and goats have a lower fermenta2ve capacity (rumen volume/Mcal maintenance energy) than ca5le

§  To compensate, they must:

§  be more selec2ve

§  eat more per day (as % of BW) than cows: lacta@ng ewes and goats : 3.5-­‐7.0% of BW lacta@ng cow : 2.0-­‐4.0% of BW

§  have higher feed passage rate à lower fiber diges@bility §  Ruminate feed par2cles more finely -  are more limited by the diet large par@cle size -  Higher grain diges@bility


The SRNS •  Approach used: –  to use the framework of the CNCPS –  to modify its submodels not suitable for S & G: •  summarizying the vast literature available on small ruminants •  finding scaling factors to apply research on cattle to small ruminants •  carrying new experiments only when strictly necessary ⇒ little money is available for S & G research


The SRNS •  Submodels of the CNCPS modified: –  –  –  –  –  –

ME & MP requirements: from CSIRO, INRA, AFRC Composition of the gain for growing animals: CSIRO, modified Body gains or losses of adults: new equations Passage rate: new equations Fecal output of CP, fat , ash : CNCPS, corrected DMI prediction: equations of Pulina et al (1998) and AFRC (goats)

•  Submodels of the CNCPS not modified: –  The whole supply submodel (but new passage rates) –  Amino Acid submodel ⇒ under work



The SRNS Cannas A., Tedeschi L., Fox D.G., Van Soest P.J., Pell A.N. 2004. Journal of Animal Science, 82:149-169 Tedeschi, L.O., Cannas, A., Fox D.G. 2010. Small Ruminant Research, 89, 174–184.

•  NRC (2007) based its requirements for sheep on Cannas et al. (2004)

•  SRNS software web site: http://nutritionmodels.com/srns.html free use for university students

•  Multilingual: English, Italian, Spanish, Portoguese, Turkish, Korean


Outline

§  The development of the SRNS §  Prediction of requirements with the SRNS §  SRNS prediction of feed nutritive value §  SRNS nutritive values

§  SRNS evaluation §  SRNS application §  NDF and other CHO optimal values


Sources of variations of MEm in lactating cattle Variable

% increase MEm

Source

Breed

0 à 30

Age

0 à -16

CNCPS CSIRO

Sex

0 à 15

AFRC, CSIRO

Diet quality

0 à 10

AFRC, CSIRO, INRA

Urea cost

0 à 14

CNCPS

Feeding level

0 à 40

CSIRO

-20 à 20

CNCPS - NRC

Cold stress

0 à 75

CSIRO – CNCPS

Heat stress

0 à 35

CNCPS

Activity confined

0 à 12

CNCPS

Grazing activity

8 à 55

CNCPS

Previous nutrition (BCS)


SRNS: ME maintenance requirements MEm (Mcal/d) = (SBW0.75 × 0.062 × K × a2 × exp(- 0.03 × AGE) + 0.09 × MEI × km + ACT + NEmcs + UREA)/km where: SBW = shrunk BW a2 = acclimatization AGE = age of the animals K = BMR adjustment 0.09 × MEI = ⇑ in maintenance req. as nutrient intake ⇑ ACT = Activity (flat and sloped distance) NEmcs = cold stress (°C, wind, rain) UREA = cost of urea production and excretion Km = 0.644


SRNS: ME maintenance requirements MEm (Mcal/d) = (SBW0.75 × 0.062 × K × a2 × exp(- 0.03 × AGE) + 0.09 × MEI × km + ACT + NEmcs + UREA)/km

K = BMR adjustment •  Sheep: K = 1 è a1 × K = 0.062 Mcal •  Goats: Based on Sahlu et al. (2004) K = 1.25 for dairy goats è a1× K = 0.0775 Mcal K = 1.05 for other goats è a1 × K = 0.0651 Mcal


MP maintenance requirements CleanWool 0.147 × FBW + 3.375 15.2 × DMI + + 0.6 × 365 0.67 0.67

Sheep !

MPM =

Goats !

0.03 × BW 0.6 × Hair 0.147 × FBW + 3.375 15.2 × DMI MPM = + + 0.6 × 365 0.67 0.67

•  1st term : endogenous CP from scurf & wool, g/d •  2nd term : urinary endogenous CP, g/d •  3rd term : fecal endogenous CP, g/d SRNS = MPm increases as DMI increases to account for higher visceral costs


SRNS energy and protein requirements of adult sheep Assuming clean wool production per year equal to 4% of BW Milk with 6.5% fat, 5% true protein (kg/d) 0 1 2 3

Energy requirements (ME, Mcal/d) 50 kg FBW 1

Protein requirements (MP, g/d)

70 kg FBW 2

50 kg FBW 1

70 kg FBW 2

TOTAL

maint.

TOTAL

maint.

TOTAL

maint.

TOTAL

maint.

1.61 3.53 5.35 7.15

1.61 1.90 2.05 2.20

2.07 4.04 5.85 7.65

2.07 2.40 2.55 2.70

48 147 247 346

48 61 74 87

59 158 257 357

59 72 85 98

based on the hypothesis that DMI is equal to 1.2, 1.8, 2.4, and 3.0 kg/d for dry ewes or lactating ewes producing 1, 2 and 3 kg/d of milk , respectively, and that total daily MEI equals total requirements. 1

based on the hypothesis of DMI is equal to 1.5, 2.1, 2.7, and 3.3 kg/d for dry ewes or lactating ewes producing 1, 2 and 3 kg/d of milk , respectively, and that total daily MEI equals total requirements. 2


NEL total requirements in lactation: ewes Milk with 6.5% fat, 5.0% true protein

70 kg of BW SNRS 1

INRA 2007 2

INRA 2017 2

(kg/d)

TOTAL

maint.

TOTAL

TOTAL

0 1 2 3

1.33 2.60 3.77 4.93

1.33 1.55 1.64 1.74

1.36 2.42 3.48 4.55

1.42 2.48 3.55 4.61

based on the hypothesis of DMI equal to 1.5, 2.1, 2.7, and 3.3 kg/d for 3-y old dry ewes or lactating ewes producing 1, 2 and 3 kg/d of milk, respectively, and that total daily MEI equals total requirements. Assuming NE of milk equal to 1.063 Mcal/kg. 1

2

assuming NE of milk equal to 1.063 Mcal/kg



Heat exchange in animals Conduction

Convection Solar radiation

Muscle+fat layer Skin surface

HEAT

TOTAL INSULATION = IT + IE IT = Thermal insulation

Wool or hair

of internal tissues IE = External thermal insulation from wool or hair

Evaporation Convection

Conduction Radiation


Sheep Total maintenance requirements expressed as index thermoneutral conditions index = 100)

Wind (km/h) Rain (mm/d) Adults, dry Temp. +5 °C Temp. 0 °C Temp. -5 °C Adults, in lactation Temp. +5 °C Temp. 0 °C Temp. -5 °C

Wool 25 mm 0 30 0 30 0 30

Wool 50 mm 0 30 0 30 0 30

115 129 144

134 149 164

234 267 300

247 280 313

100 103 183 195 100 114 208 220 109 124 233 245

100 100 100

100 100 104

125 137 149

133 145 157

100 100 107 114 100 100 116 123 100 100 125 132


Growth requirements

Soccer’s World Cup, 2006 (won by Italy)


NEL total requirements in lactation: ewes Milk with 6.5% fat, 5.0% true protein

70 kg of BW SNRS 1

INRA 2007 2

INRA 2017 2

(kg/d)

TOTAL

maint.

TOTAL

TOTAL

0 1 2 3

1.33 2.60 3.77 4.93

1.33 1.55 1.64 1.74

1.36 2.42 3.48 4.55

1.42 2.48 3.55 4.61

based on the hypothesis of DMI equal to 1.5, 2.1, 2.7, and 3.3 kg/d for 3-y old dry ewes or lactating ewes producing 1, 2 and 3 kg/d of milk, respectively, and that total daily MEI equals total requirements. Assuming NE of milk equal to 1.063 Mcal/kg. 1

2

assuming NE of milk equal to 1.063 Mcal/kg


Cost of gain vs. maturity (CSIRO, 1990) FAT set A Fat set B Protein set A Protein set B

Content in EBG (g/kg)

700 600 500 400 300 200 100 0 0.00

0.20

0.40

0.60

0.80

1.00

With this approach the cost of growth of all sheep and goat breeds can be predicted with the same model

Relative size (P) P = current BW/ mature BW

Mature BW P for 30 kg lamb

Sarda female

Sarda male

Merino female

Merino male

45

65

60

84

0.67 (30/45)

0.46 (30/65)

0.50 (30/60)

0.36 (30/84)


500

NRC (1981)

NE required (kcal/100 g ADG)

450 AFRC (1998)

400 350

SRNS Female

300

SRNS - Male

250 200

Sahlu & NRC(2007) Dairy & Meat

150 100 0

10

20

30

40

Sahlu & NRC (2007) Indigenous

BW (kg)

Simulation of the relationship between BW and NE requirements for 100 g/d of ADG. For the SRNS a mature weight of 55 kg for females and 85 kg for males was considered


CNCPS Sheep: body reserves model (Cannas & Boe, 2003)

BW = a + b BCS Breed

production

Meat/wool Aragonesa Awassi Milk Bergamasca Meat/wool Boutsko Milk Churra Milk Karagouniko Milk Laxta Milk Manchega Milk Merino Meat/wool Scottish Black. Meat Serres Milk Western range Meat/wool a = mature weight at BCS = 0 * original relationship is curvilinear

a

b

BW at BCS 2.5

Authors

* Texeira et al., 1989 8.95 42.66 11.80 57.40 Treacher e Filo, 1995 8.10 63.90 Susmel et al., 1995 7.36 37.90 Zy goyannis et al., 1997 5.57 44.00 Frutos et al., 1997 9.27 56.80 Zygoyannis et al., 1997 7.10 48.65 Oregui et al., 1997 10.9 67.30 Molina et al., 1998 7.27 41.38 Guerra et al., 1969 10.56 59.69 Russel et al., 1969 8.62 48.25 Zygoyannis et al., 1997 8.10 61.10 Sanson et al., 1993 b = BW variation for 1 BCS variation

22.52 27.90 43.60 19.50 30.12 33.60 30.90 39.50 2 3.20 33.29 26.70 40.85


full BW, kg

SRNS

120

70 kg FBW at BCS 2.5

100

50 kg FBW at BCS 2.5

60 kg FBW at BCS 2.5 40 kg FBW at BCS 2.5

80 60 40 20

Simulation of body reserve model in sheep

0 0

1

2

3

4

5

4

5

BCS (scale 0-5) 70 kg FBW at BCS 2.5 60 kg FBW at BCS 2.5 50 kg FBW at BCS 2.5 40 kg FBW at BCS 2.5

40

body FAT, kg

35 30 25 20 15 10 5 0 0

1

2

3

BCS (scale 0-5)


Outline

§  The development of the SRNS §  Prediction of requirements with the SRNS §  SRNS prediction of feed nutritive value §  SRNS nutritive values

§  SRNS evaluation §  SRNS application §  NDF and other CHO optimal values


SRNS feed energy and protein value §  based on the CNCPS dynamic rumen model §  Predict nutrient supply from carbohydrate and protein fractions and their digestion and passage rates

§  Predicts separately rumen N requirements and balance and whole body MP balance

§  Variable microbial efficiency §  Predicts variable ME and MP values from feed analysis


SRNS: feed fermented in the rumen depends on degradation rate (kd) and passage rate (Kp) UNDEGRADED

Intake Kd

Kp

Intestine

DEGRADED

Degradation rate (%/h) = rate at which feed fractions ferment Passage rate (%/h) = rate at which a feed particle escapes the rumen tract


SRNS: 4 carbohydrate fractions Organic Acids & Sugars

CHO A: kd 175 - 300%/h

NFC Starch & pectins

available NDF unavailable NDF

Lignin

CHO B1:

kd

CHO B2:

kd 3 - 6%/h

CHO C: kd 0 %/h

25 - 40%/h


SRNS = 5 protein fractions A

Non protein N Soluble CP

Kd istantaneous

NPN

citoplas m

B1

175-300%/h

sol. citopl.

B2 insol. citopl.

True protein

5-12%/h

Insolubile CP

B3

NDF

0.15 - 2%/h

NDIP

C ADIP

0%/h


Kd (%/h) of CHO of some feeds § Degradation rates are pool and feed specific, based on research data §  Can be altered by degree of processing and rumen pH § same feed library of cattle Feed

A

B1

B2

Corn grain, whole

115

7.5

4

Corn grain, ground

200

10

4

Corn grain, flaked

300

30

6

Barley, ground

300

25

5

Corn silage, medium particles

250

20

6

Corn silage, fine particles

300

28

9


SRNS passage rates (Kp) (Cannas and Van Soest, 2000); equations developed on cattle, sheep and goats (few) data Kp forage, diet 17% CP Kp concentrate, diet 17% CP

9

Kp forage, diet 10% CP

8

Kp concentrate, diet 10% CP

Kp (%/h)

7 6

5 4

3 2

1 0 0.0

0.5

1.0

1.5

Dietary NDFI (% BW)

2.0

2.5


CNCPS - SRNS ⇑ requirements " ⇑ DM and NDF intake " ⇑ feed passage rate " ⇓ digestibility −  much stronger decrease in slowly fermented fractions (e.g. fiber or insoluble N) than fastly fermented fractions (e.g. starch or soluble protein) −  no decrease in digestibility in the feed fractions with very high degradation rate (e.g. sugar or NPN) −  certain feed fractions are not digested at all (lingin and lingin bound substances)


Energy value: forages NEL System CP, % DM Ash , % DM NDF, % DM ADL , % DM

Ray-grass 2 14.7 10.5 52.7 4.5

Ray-grass 4

Ray-grass 5

10.6 8.7 63.4 5.0

9.4 9.2 70.6 8.0

Alfalfa 1 18.7 11.4 43.6 7.5

Alfalfa 3 15.0 10.7 56.0 9.0

1.173 1.360 1.343 1.302 1.278

1.071 1.150 1.345 1.265 1.230

NEL, Mcal/kg DM INRA NRC (2001) SRNS F70, 1.0M SRNS F70, 2.4M SRNS F30, 3.1M

1.258 1.390 1.437 1.370 1.346

1.156 1.290 1.345 1.261 1.236

1.122 1.320 1.085 1.003 0.980

F70 and F30 = percentage of forage in the diet; 1M, 2.4 M and 3.1 M = levels of feeding in multiples of maintenance. NRC (2001) = dairy cattle


Protein value: concentrates System

Units

Maiz USA

Pulpa de remolacha 11.3 0.9 47.7

Hna. Soja 44 50.1 1.9 14.2

Hna. Girasol

CP Ash NDF

% DM % DM % DM

9.4 4.2 10.2

INRA SRNS F70, 1.0M SRNS F70, 2.4M SRNS F30, 3.1M

DIP, % CP DIP, % CP DIP, % CP DIP, % CP

45 51 43 43

55 44 41 41

65 68 60 60

76 69 62 62

INRA SRNS F70, 1.0M SRNS F70, 2.4M SRNS F30, 3.1M

PDIA * MP escape * MP escape * MP escape *

52 40 47 47

49 42 45 45

185 144 184 185

78 85 110 110

* g/kg of DM F70 and F30 = percentage of forage in the diet; 1M, 2.4 M and 3.1 M = levels of feeding in multiples of maintenance.

34.2 2.7 44.8


Protein value: concentrates

INRA INRA SRNS F70, 1.0M SRNS F70, 2.4M SRNS F30, 3.1M

PDIME PDIMN MP microb. MP microb. MP microb.

43 21 121 110 99

Pulpa de remolacha 11.3 0.9 47.7 g/kg DM 63 33 103 94 84

INRA INRA SRNS F70, 1.0M SRNS F70, 2.4M SRNS F30, 3.1M

PDIE PDIN MP total MP total MP total

95 73 161 157 146

112 82 145 139 129

System CP Ash NDF

Units % DM % DM % DM

Maiz USA 9.4 4.2 10.2

* g/kg of DM F70 and F30 = percentage of forage in the diet; 1M, 2.4 M and 3.1 M = levels of feeding in multiples of maintenance.

Hna. Soja 44 Hna. Girasol 30 50.1 34.2 1.9 2.7 14.2 44.8 58 176 54 49 44

40 145 36 32 29

243 361 198 233 229

118 223 121 142 139


Protein value: whole diets System

Units

Ray-grass 2

Ray-grass 4

Ray-grass 5

Alfalfa 1

Alfalfa 3

Diet F70, 1.0 M INRA INRA SRNS

PDIE, g/d PDIN, g/d MP total, g/d

87 102 106

80 100 97

78 101 90

90 104 102

84 104 100

Diet F70, 2.4 M INRA INRA SRNS

PDIE, g/d PDIN, g/d MP total, g/d

217 256 269

200 250 243

194 252 226

225 260 267

210 260 256

Diet F30, 3.1 M INRA INRA SRNS

PDIE, g/d PDIN, g/d MP total, g/d

337 351 370

328 346 366

325 346 364

341 367 361

333 366 365

INRA suggests to use the lowest between PDIE and PDIN


Outline §  The development of the SRNS §  Prediction of requirements with the SRNS §  SRNS prediction of feed nutritive value §  SRNS nutritive values

§  SRNS evaluation §  SRNS application §  NDF and other CHO optimal values


SRNS evaluations Pred MB = RMS r2 References (P) O – P PE SHEEP 1 All OMd, g/100 g 19 60.2 61.3 -­‐1.1 3.6 0.83 Cannas et al. (2004) Cannas et al. (2004) All 2 OMd, g/100 g 12 56.6 53.3 3.3 6.5 1 Lact. SBW var., g/d 15 22 28 -­‐5.8 30 0.73 Cannas et al. (2004) 2 14 -­‐57 110 53.4 84.1 0.84 Cannas et al. (2004) Lact. SBW var., g/d 19 -­‐-­‐ -­‐-­‐ 0.174 -­‐-­‐ 0.82 NRC (2007) Lact. NEL, Mcal/d Grow.3 ADG, g/d 42 198 180 18 41 0.84 Cannas et al. (2006a,b) 3 156 189 179 10 -­‐-­‐ 0.70 NRC (2007) Grow. ADG, g/d 3 8 285 282 2.4 21.4 0.76 Linsky (2008) Grow. ADG, g/d 8 275 295 19.8 59.2 0.30 Linsky (2008) Grow.3 Fat, g/kg EBG 3 146 152 5.8 19.3 0.10 Linsky (2008) Grow. Prot., g/kg EBG 8 48 -­‐-­‐ -­‐-­‐ 0.9 -­‐-­‐ 0.88 NRC (2007) Grow. MP for gain, g 8 1.33 1.29 0.04 0.05 0.95 Linsky (2008) Grow. DMI, kg/d GOATS Lact. MEI, Mcal/d 21 4.04 4 0.04 0.23 0.99 Cannas et al. (2007b) 6 -­‐ 0.10 0.99 Cannas et al. (2007b) Lact. NE milk, Mcal/d 21 1.664 1.746 3 0.082 0.20 2 0.87 Cannas et al. (2007b) Lact. NE bal., Mcal/d 21 0.361 0.286 0.075 3 1 Grow. ADG, g/d 31 136.1 142.5 -­‐6.4 32.5 0.85 Cannas et al. (2007a) 1 2 3 rumen N balance positive; rumen N balance negative; (0.09 x MEI) correction of MEm not Stage Variable, units

used

N

Obs (O)


Outline §  The development of the SRNS §  Prediction of requirements with the SRNS §  SRNS prediction of feed nutritive value §  SRNS nutritive values

§  SRNS evaluation §  SRNS application §  NDF and other CHO optimal values




SRNS report


SRNS report


SRNS report


Ruminant Nutri2on System (Tedeschi, 2018) Include caGle, sheep, goats Methane predic2ons


Nuraghe (Sardinia) 1800-1300 year B.C. About 8000 of them in the whole Island


Outline §  The development of the SRNS §  Prediction of requirements with the SRNS §  SRNS prediction of feed nutritive value §  SRNS nutritive values

§  SRNS evaluation §  SRNS application §  NDF and other CHO optimal values


CHO during pregnancy and lactation of sheep and goats

§  Well defined reference values for NDF, starch, sugars, fiber particle size in dairy cattle

§  No feeding systems suggest optimal, max and min NDF and NSC (or NFC) values during the pregnancy and lactation of ewes and goats Serious limitation when balancing the diets of small ruminants


Pregnancy


Energy and NDF during pregnancy of sheep and goats §  Sheep and goats are prolific and have short pregnancy: high requirements in a short period §  Common to observe subclinical ketosis and pregnancy toxemia §  Strong association between negative energy balance, increased ketone bodies and diseases in the transition period (end of pregnancy, early lactation) §  Marked negative energy balance during pregnancy reduces milk production §  Proper nutrition during pregnancy necessary for optimal milk production and health during the lactation


Ewes (BW 92 kg) fed silages plus concentrates (Olsen, 2016)

Mean: 1.0% NDFi intake as % BW

Database on pregnant ewes (mean -30 d to lambing) Mean St.dev. Min. Max.

DMI, BW %BW 73.1 2.7 23.4 0.4 39.4 2.0 100.0 3.3

DMI, kg/d 1.9 0.6 1.2 2.9

NDFI, %BW NDF% DIP, d 1.2 43.2 117.4 0.3 9.1 13.0 0.8 31.0 90.0 1.7 61.6 130.0

Litter size 1.9 0.7 1.0 3.2

Total litter BW 10.4 5.2 3.3 16.8

ME int, Mcal/d 4.9 1.9 2.7 8.1

ME req, Mcal/d 4.0 1.4 2.1 5.6


NDFI, % bw DMI, % BW

3,5

Diet NDF during pregnancy(mean= 30 d from lambing)

3 NDFi or DMI , % BW

2,5 2

1,5 1

MEI

0,5

ME balance

MEI intake or balance, Mcal/d

10,0 8,0

0 20

30

40 50 NDF, % DM

60

70

6,0 4,0 2,0 0,0

-2,0

20

30

40 50 NDF, % DM

60

70


Diet NDF concentration during the pregnancy of sheep

NDFI, % BW = 0.646 + 0.02086 x NDF% - 0.2032 x litter size DMI, %BW = 4.392 - 0.01731 x NDF% - 0.5011 x litter size

R2 adj = 92.6% R2 adj = 80.6%

ME int, Mcal/d = 3.05 - 0.0582 NDF% - 1.450 x litter size + 0.09746 BW R2 adj= 93.7%


Diet NDF during pregnancy (Cannas, 2016) (70 kg BW) 4,5 4,0 3,5 3,0 2,5 2,0 1,5 1,0 0,5 0,0

Litter size

DMI, kg/d NEL int, Mcal/d NEL req, Mcal/d

1

1

1

35

50

65

2

2

2

3

3

3

35NDF (% 50 DM) 65 Diet

35

50

65

Max diet NDF around 40-45%; lower values in small body size sheep


Diet NDF during pregnancy

NDF intake, % BW

2,5 Sheep

2,0

Cattle

y = 0.0004x2 - 0.0125x + 0.874 R² = 0.72

1,5 1,0 0,5

y = 0.0006x2 - 0.0414x + 1.3791 R² = 0.84

0,0 20

30

40 50 NDF, % DM

60

70


Energy and NDF during pregnancy of sheep and goats

In late pregnancy: §  diet NDF concentration < 40% is suggested, especially with twins §  energy and NDF concentrations should be similar to those of lactation §  High quality (immature, low NDF and lignin) forage sources are needed §  Chopping the forages helps to keep high the intake


Lactation


Meeting of the Animal Science Modellers’ Group -2016

Prediction of optimal NDF intake in Antonello Cannas

sheep

Antonello Cannas1, L. O. Tedeschi2, G. Molle3, A. S. Atzori1, C. Dimauro1, M. F. Lunesu1 1Department

of Agricultural Sciences, University of Sassari, Sardinia, Italy

2Department

of Animal Science, Texas A&M University, College Station, TX

3Dipartimento

di Ricerca nelle Produzioni Animali, Agris Olmedo, Sardinia, Italy

59


Intake models for sheep §  Intake models for sheep (and goats..) mostly based on energy requirements, do not account for diet filling effect (Pulina et al., 2013) §  Little reference values for optimal, minum or maximum dietary or forage NDF concentration or intake, forage and NDF particle size §  Mostly empirical observations and suggestions

OBJECTIVES §  to develop a model to predict optimal dietary NDF concentration and intake for sheep. Current focus: lactating ewes §  The approach developed by of Mertens (1985; 1987) for dairy cattle was used and adapted to sheep


Dairy cows Max DMI with NDFI equal to 1.1-1.2% PV

Intake (% BW)

Ie = C/F

Ie = R/E

Diet NDF, % DM

BW

DMI % BW

DMI kg/d

Diet NDF % DM

NDF intake kg/d

NDF intake % BW

600

2.90

17.4

38.0

6.61

1.10

600

3.35

20.1

33.0

6.63

1.11

600

4.00

24.0

27.5

6.60

1.10


Adapatation of the model of Mertens to sheep §  Sheep have a lower fermentative capacity (rumen volume / Mcal maintenance energy) than cattle. To compensate, sheep: §  are more selective §  eat more per day (as % of BW) than cows: •  lactating ewe : 3.5-7.0% of its BW •  lactating cow : 2.0-4.0% of its BW §  have higher feed passage rate à lower fiber digestibility §  NDFIC = NDF intake capacity (kg of NDF/d), considered constant and equal to 1.1% ± 0.1 of BW §  is this valid for sheep? §  is this valid, since the level of intake of intake of sheep is higher than that of cattle, the diet of sheep would have too low NDF concentrations


Diet DM and NDF during lactation

DMI%BW sheep DMI%BW cow

DMI%BW sheep DMI%BW cow

y = -0.0714x + 8.7298 R² = 0.33

8

3,5

7

3,0 y = 0.0287x + 1.1758 R² = 0.31 2,5

5

NDFI, % BW

DMI, % BW

6

2,0

4

1,5

3

1,0

2 y = -0.0183x + 4.1611 R² = 0.048

1

0,5

0 20

25

30

35

40

NDF, % DM

45

50

y = 0.0284x + 0.2327 R² = 0.53

55

0,0 20

25

30

35 40 NDF, % DM

45

50

55


Adapta2on of the model of Mertens to sheep §  The 1.1% NDFI%bw of a 600 kg cow Mertens (1985, 1987) was used as reference value: § NDFIC was 6.6 kg of NDF, which is also equal to 5.444% of BW0.75 (i.e. 6.6/6000.75= 0.544)

§  The NDFIC capacity for other BW was es@mated as 5.444% of BW0.75 MW, kg

NDFI, % BW

50 100 200 400 600 800 1000

18.8 31.6 53.2 89.4 121.2 150.4 177.8

2.05 1.72 1.45 1.22 1.10 1.02 0.97

NDFI, % NDFI capacity, kg MW 1.02 1.72 2.90 4.87 6.60 8.19 9.68

5.444 5.444 5.444 5.444 5.444 5.444 5.444

2,0

y = 5.444 x-­‐0.25

1,5

NDFI, % BW

BW, kg

2,5

1,0 0,5 0,0 0

200

400 600 BW, kg

800

1000


Adapta2on of the model of Mertens to sheep

Thus, the NDFIC of Mertens (1987) was scaled to sheep BW assuming it varied as a func2on of BW-­‐0.25

By using 1.1% NDFI%bw à NDFIC, % BW = 5.444 x BW-­‐0.25

§ The predic@ons are consistent with the values of Molle et al. (2014, 2016) (Obs = 2.38%, Pred = 2.30%) and Nielsen (2016) (Obs = 1.92%, Pred = 1.76%) if 1.2% NDFI%bw is used §  the equa@ons of Mertens (1987) were then used to es@mate DMI and NDF op@mal concentra@on in sheep of different milk yield y using variable NDFIC, % BW


Maximum dietary NDF (% of DM) and corresponding DMI (% BW) on lactating ewes fed forages and concentrates (Cannas et al., 2016) Grass-Legume forage: 58% NDF, 1.20 NEL kg-1 Concentrate: 12% NDF, 1.90 NEL kg-1

Milk, kg/d 6.5% fat, 5.8% P 1.0 2.0 3.0 4.0 Milk, kg/d 6.5% fat, 5.8% P 1.0 2.0 3.0 4.0

45 kg BW (2.10 NDFI%bw )

60 kg BW (1.96 NDFI%bw )

NDF %

DMI % BW

Forage %

DMI kg/d

NDF %

DMI % BW

Forage %

DMI kg/d

54.7 41.7 33.7 28.3

3.8 5.0 6.2 7.4

93 65 47 35

1.7 2.3 2.8 3.3

58.0 45.9 37.9 32.3

3.4 4.3 5.2 6.1

100 74 56 44

2.0 2.6 3.1 3.7

75 kg BW (1.85% NDFI%bw)

90 kg BW (1.77% NDFI%bw)

NDF %

DMI % BW

Forage %

DMI kg/d

NDF %

DMI % BW

Forage %

DMI kg/d

58.0 49.1 41.2 35.5

3.2 3.8 4.5 5.2

100 81 64 51

2.4 2.9 3.4 3.9

58.0 51.6 43.9 38.2

3.0 3.4 4.0 4.6

100 86 69 57

2.7 3.1 3.6 4.1

Italics = it would cause weight gain.


Starch in lactating sheep and goats In ewes: •  Positive effect of starch in early lactation (Cannas et al., 2002; Bovera et al., 2004; Cannas et al., 2007; Cannas et al., 2013) •  Positive effects of highly digestible fiber (e.g. beet pulps, soybean hulls and immature forage) in mid-late lactation (Cannas et al., 2002; Cannas et al., 2004; Bovera et al., 2004)

In goats: •  Positive effect of starch both in early and in late lactation (Cannas et al., 2007)


Milk production in ewes fed different % of NSC and starch (Bovera et al., 2004) L = 20.7% starch 1600

H = 26.1% starch

*

Milk yield (g/d)

1400 1200 1000

L H

800 600 400 200 0 0

* = P < 0.05

1

2

3

4

Months of lactation

5

6

7


Modulation of dietary energy partitioning between milk production and body reserves in sheep and goats Ph.D. Project of Mondina Lunesu Chair: Antonello Cannas


Diets

Pellets HS

LS

Pellet (HS or LS)

65.7

65.7

Dehyd chopped alfalfa

28.0

28.0

Whole corn grains

2.4

2.4

Mature ryegrass hay

3.9

3.9

100.0

100.0

Ingredients, % as fed

TOTAL

Chemical composi2on CP, % DM

15.4

15.4

Ash, % DM

11.8

12.3

NDF, % DM

36.4

46.8

NFC, %DM

37.3

26.6

Starch, % NFC

64.6

39.62

Starch, % DM

24.1

10.5

Ingredients, % AF

HS

LS

Dehydrated alfalfa Corn meal Barley meal Wheat bran Soybean hulls Soybean meal 44 Sugarcane molasses Sodium bicarbonate Bentonite Magnesium oxide Minerals and vitamins

30.0 21.1 13.4 10.1 9.0 5.0 4.6 3.0 2.0 1.5 0.3

30.0 3.0 0.0 5.0 43.2 7.4 4.6 3.0 2.0 1.5 0.3

Appe@zer TOTAL

0.03 100.0

0.03 100.0


LS HS

LS HS

3,3 3,1 2,9 2,7 2,5

6.5% fat corrected milk produc2on, kg/d(P<0.01)

LS HS

i Prelim

SHEEP 3,8

27-­‐

y 6-­‐Ma

22-­‐

e 4-­‐Jun

BCS (P< 0.013)

3,6 3,4

BCS

2,1 1,9 1,7 1,5 1,3 1,1 0,9 0,7

BCS (P> 0.05)

BCS

3,4 3,2 3 2,8 2,6 2,4 2,2 2

GOATS 3,5

4.0% fat corrected milk yield, kg/d (P<0.02)

3,2

LS

3,0

HS

2,8


0,8 0,7 0,6 0,5 0,4 0,3 0,2 0,1 0,0

Ewes Goat

Insulin

Insulin (µg/L)

(µg/L)

20

40

60 80 DIM

100 120 140 15

Ew es

12

GH (ng/ml)

0

9

Growth Hormone (ng/ml)

6 3 0 0

20

40

60DIM80

100

120

140


NDF and STARCH during lactation

§  DMI and NDFI as % of BW higher in small size sheep and goats §  Optimal NDF dietary concentration lower in small size sheep and goats §  In early lactation the diet should be rich of starch, both in ewes and goats: 20-30% of DM §  In mid-late lactation the diet should be rich of starch in goats (20-30% of DM) but low in starch (10-15% of DM) and rich in digestible fiber in sheep


CONCLUSIONS §  Economical importance of sheep and goats is growing •  should not be more the little brother §  Better predictions are needed to account for the different environments and production systems §  to improve sheep and goats’ performances and profitability §  to reduce nutrient use and environmental impact §  to reduce more food for humans

§  Much more effort is needed to develop feeding systems for sheep and goats


Alghero

Thank you for your attention !


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