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Genetic and phenotypic parameters for feed and water efficiency in Senepol cattle Gilberto Menezes Researcher
Genetic and phenotypic parameters forfeed and water efficiency in Senepol cattle
Gilberto MenezesResearcher
Distribution of Research Units in Brazil
42 Units~ 10,000 employees~ 2,500 researchers
Genetic and phenotypic parameters forfeed and water efficiency in Senepol cattle
“Preliminary results”G.R.O. Menezes, R.C. Gomes, M.N. Ribas, R.A.A. Torres Junior, J.A. Fernandes
Junior, G.M. Pereira, R. Fávero & L.O.C. Silva
2018
IntroductionIntroduction
Feeding an increasing human population with limited resources
(in a sustainable way)
Feeding an increasing human population with limited resources
(in a sustainable way)
Challenge for livestock productionChallenge for livestock production
IntroductionIntroduction
Selecting for efficient animals that can produce more product with fewer inputs (Ahlberg et al., 2017)
Selecting for efficient animals that can produce more product with fewer inputs (Ahlberg et al., 2017)
Producing with greater efficiency (Berry & Crowley, 2013) Producing with greater efficiency (Berry & Crowley, 2013)
One way of doing
this:
IntroductionIntroduction
Water, traditionally, considered an inexpensive, readily available, and renewable natural resource
(Brew et al., 2011)
Water, traditionally, considered an inexpensive, readily available, and renewable natural resource
(Brew et al., 2011)
Feed has a great impact in costs of beef cattle system ~ 50-70%
Feed has a great impact in costs of beef cattle system ~ 50-70%
Water efficiency will be necessary to achieve sustainability of animal agriculture in expectation of increasing water
scarcity and worsening quality (Nardone et al., 2010)
Water efficiency will be necessary to achieve sustainability of animal agriculture in expectation of increasing water
scarcity and worsening quality(Nardone et al., 2010)
ObjectiveObjective
To estimate genetic and phenotypic parameters for feed and water efficiency in Senepol cattle in order to evaluate their use as selection criteria.
To estimate genetic and phenotypic parameters for feed and water efficiency in Senepol cattle in order to evaluate their use as selection criteria.
Senepol in Brazil
Material & MethodsMaterial & Methods
Tropically adapted taurineFirst animals: year 2000
Present in 85% of the Brazil’s states
592 breeders
Material & MethodsMaterial & Methods
A performance test for evaluating and selecting purebred Senepol heifers to be “donors”.
Around 85% of Senepol in Brazil come from ET/IVF
A performance test for evaluating and selecting purebred Senepol heifers to be “donors”.
Around 85% of Senepol in Brazil come from ET/IVF
Data:
Material & MethodsMaterial & Methods
Data:Located in Pirajuí, Sao Paulo State, Brazil (21º 59’ S; 49º 27’ W)Total Capacity: ~ 380 animals/test
48 electronic feed bunks (24 per pen)12 electronic water bunks (6 per pen)
Located in Pirajuí, Sao Paulo State, Brazil (21º 59’ S; 49º 27’ W)Total Capacity: ~ 380 animals/test
48 electronic feed bunks (24 per pen)12 electronic water bunks (6 per pen)
Pen #1
Pen #2
FeedbunksFeedbunks
WaterbunksWaterbunks
Material & MethodsMaterial & Methods
www.intergado.com.brChizzotti, M.L. et al. J. Dairy Sci., 2015
Electronic feed bunk (up to 8 animals/bunk):
Material & MethodsMaterial & Methods
Electronic water bunk (up to 35 animals/bunk):
www.intergado.com.brOliveira Jr, B. R. et al. Animal, 2017
Material & MethodsMaterial & Methods
Data:
Material & MethodsMaterial & Methods
5 traits were studied:Trait Abbreviation Unit
Average daily gain ADG kg d-1
Average daily feed intake ADFI kg d-1
Residual feed intake RFI kg d-1
Average daily water intake ADWI L d-1
Residual water intake RWI L d-1
RFI = ADFI – eADFI (Koch et al., 1963)eADFI = b0 + b1 *ADG + b2 * MMWT (within contemporary group)
RFI = ADFI – eADFI (Koch et al., 1963)eADFI = b0 + b1 *ADG + b2 * MMWT (within contemporary group)
RWI = ADWI – eADWIeADWI = b0 + b1 *ADG + b2 * MMWT (within contemporary group)
RWI = ADWI – eADWIeADWI = b0 + b1 *ADG + b2 * MMWT (within contemporary group)
Material & MethodsMaterial & Methods
Description of the final data set Trait1 Mean ± SD Number of
animals with records
Number of contemporary
groupsADG (kg d-1) 0.87 ± 0.21 587 51ADFI (kg d-1) 7.49 ± 1.16 587 51ADWI (L d-1) 24.68 ± 3.99 587 51RFI (kg d-1) 0.00 ± 0.79 587 51RWI (L d-1) 0.00 ± 2.96 587 51
Average weight of 397 ± 52 kg and age of 520 ± 59 days (in the beginning)
Average weight of 397 ± 52 kg and age of 520 ± 59 days (in the beginning)
Contemporary group: test edition and farm of origin of the heifer
Contemporary group: test edition and farm of origin of the heifer
Diet: 2.64 Mcal ME & 14% Crude Protein
Diet: 2.64 Mcal ME & 14% Crude Protein
Material & MethodsMaterial & Methods
2-trait animal model (REML):
Contemporary group (CG) -> fixed effectAge of the animal nested in CG -> linear covariateDirect additive genetic -> random effectResidual -> random effect
2-trait animal model (REML):
Contemporary group (CG) -> fixed effectAge of the animal nested in CG -> linear covariateDirect additive genetic -> random effectResidual -> random effect
AIREMLF90 program (Misztal et al., 2002)AIREMLF90 program (Misztal et al., 2002)
Results & DiscussionResults & Discussion
Heritability estimates:(averaged across 2-trait analyses)
Trait h2 ± seADG 0.15 ± 0.09ADFI 0.23 ± 0.11ADWI 0.47 ± 0.12RFI 0.12 ± 0.10RWI 0.39 ± 0.12
Selection can be used for increasing feed and water efficiency in Senepol.
Selection can be used for increasing feed and water efficiency in Senepol.
Genetics gains for water traits are expected to be quite superior to those for feed traits.
Genetics gains for water traits are expected to be quite superior to those for feed traits.
Pooled heritabilities of 0.40 ± 0.01 for ADFI and 0.33 ± 0.01 for RFI (Berry & Crowley, 2013).
Pooled heritabilities of 0.40 ± 0.01 for ADFI and 0.33 ± 0.01 for RFI (Berry & Crowley, 2013).
Genetic (green) and phenotypic (blue) correlations estimates:
Traits1 ADG ADFI ADWI RFI RWIADG - 0.61 ± 0.772 0.70 ± 0.69 0.06 ± 1.12 0.45 ± 0.79ADFI 0.28 ± 0.04 - 0.75 ± 0.41 0.68 ± 0.91 0.57 ± 0.40ADWI 0.29 ± 0.04 0.57 ± 0.03 - 0.39 ± 0.90 0.90 ± 0.11RFI -0.11 ± 0.05 0.78 ± 0.02 0.30 ± 0.04 - 0.50 ± 0.65RWI -0.09 ± 0.05 0.29 ± 0.02 0.84 ± 0.01 0.37 ± 0.04 -
1 ADG, average daily gain; ADFI, average daily feed intake; ADWI, average daily water intake; RFI, residual feed intake; RWI, residual water intake.2 standard error.
Berry & Crowley (2013): rp (-0.06 to +0.04); rg (-0.15 to +0.53)
Berry & Crowley (2013):
rp (-0.06 to +0.04); rg (-0.15 to +0.53)
Results & DiscussionResults & Discussion
Genetic (green) and phenotypic (blue) correlations estimates:
Traits1 ADG ADFI ADWI RFI RWIADG - 0.61 ± 0.772 0.70 ± 0.69 0.06 ± 1.12 0.45 ± 0.79
ADFI 0.28 ± 0.04 - 0.75 ± 0.410.68 ± 0.91 0.57 ± 0.40
ADWI 0.29 ± 0.04 0.57 ± 0.03- 0.39 ± 0.90 0.90 ± 0.11
RFI -0.11 ± 0.05 0.78 ± 0.02 0.30 ± 0.04 - 0.50 ± 0.65
RWI -0.09 ± 0.05 0.29 ± 0.02 0.84 ± 0.01 0.37 ± 0.04 -
It suggests that water intake could be used as an indicator for feed intake (and vice-versa).
It suggests that water intake could be used as an indicator for feed intake (and vice-versa).
Results & DiscussionResults & Discussion
Genetic (green) and phenotypic (blue) correlations estimates:
Traits1 ADG ADFI ADWI RFI RWIADG - 0.61 ± 0.772 0.70 ± 0.69 0.06 ± 1.12 0.45 ± 0.79
ADFI 0.28 ± 0.04 - 0.75 ± 0.41 0.68 ± 0.91 0.57 ± 0.40
ADWI 0.29 ± 0.04 0.57 ± 0.03 - 0.39 ± 0.90 0.90 ± 0.11
RFI -0.11 ± 0.05 0.78 ± 0.02 0.30 ± 0.04 - 0.50 ± 0.65RWI -0.09 ± 0.05 0.29 ± 0.02 0.84 ± 0.01 0.37 ± 0.04 -
It suggests that selection for water efficiency would improve feed efficiency (and vice-versa).
It suggests that selection for water efficiency would improve feed efficiency (and vice-versa).
Results & DiscussionResults & Discussion
ConclusionsConclusions
Genetic progress for water efficiency is expected to be superior to the one for feed efficiency.
Genetic progress for water efficiency is expected to be superior to the one for feed efficiency.
Feed intake and efficiency can be genetically improved by selecting animals for water intake and efficiency.
Feed intake and efficiency can be genetically improved by selecting animals for water intake and efficiency.
Genetic improvement for feed and water efficiency in Senepol cattle can be achieved through selection.
Genetic improvement for feed and water efficiency in Senepol cattle can be achieved through selection.
Next StepsNext Steps
Keep recording -> to increase database
Keep recording -> to increase database
Record feed and water intake in grazing systems
Record feed and water intake in grazing systems
Incorporate genomics data -> all animals have DNA samples for genotyping (in 50k soon)
Incorporate genomics data -> all animals have DNA samples for genotyping (in 50k soon)
Study associations of feed and water intake/efficiencywith other relevant traits (and with adaptation)
Study associations of feed and water intake/efficiencywith other relevant traits (and with adaptation)
AcknowledgementsAcknowledgements
• For providing data and/or financial support:
• For providing guidance in data analysis and/or edition:
– Shogo Tsuruta (UGA)
– Daniela Lourenço (UGA)
– Andrea Gondo (Embrapa)
– Paulo Nobre (Geneplus)
– Renato Peixoto (Geneplus)
