Phenotypic and genetic variability of methane
emissions and milk fatty acid contents
of Walloon Holstein dairy cows
M.-L. Vanrobays
1, P.B. Kandel
1, H. Soyeurt
1, A. Vanlierde
2, F. Dehareng
2, E. Froidmont
2, & N. Gengler
11 University of Liege, Gembloux Agro-Bio Tech, Department of Agricultural Science – Gembloux, Belgium 2 Walloon Agricultural Research Centre – Gembloux, Belgium
Contact: mlvanrobays@ulg.ac.be
The Ministry of Agriculture of the Walloon Region of Belgium (Service Public de Wallonie – Direction générale de l’Agriculture, des Ressources naturelles et de l’Environnement, Direction de la Recherche) is acknowledged for its financial support through the research project D31-1304. The authors gratefully acknowledge funding from the European Commission, “GreenHouseMilk” project (FP7 Marie Curie ITN).
GEMBLOUX AGRO
-BIO
TECH
19th National Symposium on Applied Biological Sciences, Gembloux, Belgium, February 7th 2014
Background
Enteric methane (CH4) emissions of cows
• Losses of dietary energy
• Contribution to climate change Growing interest in reducing CH4
emissions
Milk fatty acid (FA) profile is influenced by rumen fermentations
Objective: Estimation of phenotypic and
genetic variability of CH
4
emissions & FA
contents of milk
Conclusions
SFA & SCFA are higher genetically & phenotypically
correlated with MIR CH
4emissions than UFA & LCFA
These correlations reflected indirect link between
milk FA & CH
4emissions through rumen metabolism
Results
Material & Methods
Data
Prediction of CH4 emissions & milk FA
contents from milk mid-infrared (MIR) spectra
Vanlierde et al., 2013. Advances in Animal Biosciences, 4(2), 433. Soyeurt et al., 2011. Journal of Dairy Science, 94(4), 1657-1667.
≥ 5 records/cow ≥ 20 cows/herd
161,681 MIR spectra collected between
January 2007 and June 2013
From 5 to 305 days in milk (DIM)
22,642 first-parity Walloon Holstein cows
from 489 herds
Pedigree file
• 79,736 animals
Model
Bivariate random regression test-day
models
• Resolved using REMLF90 (Misztal, 2012)
• MIR CH4 (g/d) & 1 FA trait
y = Xb + Q (Wh + Zp + Za) + e
where y = Vector of observations
where b = Vector of fixed effects
Herd x test-day
Classes of days in milk
Gestation stage x lactation stage
Lactation stage x age at calving x season of calving h = Vector of herd x year of calving random effects
where p = Vector of permanent environmental random effects
where a = Vector of additive genetic random effects
where Q = Covariate matrix for 2nd order Legendre polynomials
where X, W & Z = Incidence matrices
where e= Error
Heritabilities of FA and MIR CH4 emissions
Abbreviations: SFA = Saturated FA ; MUFA = Monounsaturated FA ; PUFA = Polyunsaturated FA ; UFA = Unsaturated FA ; SCFA = Short chain FA ; MCFA = Medium chain FA ; LCFA = Long chain FA
Trait h² Trait h²
MIR CH4 (g/d) 0.11 C18:0 (g/dL of milk) 0.19 C4:0 (g/dL of milk) 0.34 C18:1 cis-9 (g/dL of milk) 0.15 C6:0 (g/dL of milk) 0.41 SFA (g/dL of milk) 0.42 C8:0 (g/dL of milk) 0.41 MUFA (g/dL of milk) 0.19 C10:0 (g/dL of milk) 0.40 PUFA (g/dL of milk) 0.30 C12:0 (g/dL of milk) 0.41 UFA (g/dL of milk) 0.20 C14:0 (g/dL of milk) 0.43 SCFA (g/dL of milk) 0.42 C16:0 (g/dL of milk) 0.40 MCFA (g/dL of milk) 0.42 C17:0 (g/dL of milk) 0.36 LCFA (g/dL of milk) 0.17
Evolution of genetic and phenotypic correlations between MIR CH4 (g/d) and individual FA or groups of FA
High & decreasing correlations between MIR
CH4 and SFA &
SCFA through lactation Low & increasing correlations between MIR
CH4 and UFA &
LCFA through lactation -0,8 -0,6 -0,4 -0,2 0 0,2 0,4 0,6 0,8 0 50 100 150 200 250 300 Ge netic corr elati on wi th MIR CH 4 (g/d) Days in milk
Daily genetic correlations between MIR CH4 (g/d) and groups of fatty acids
SFA MUFA PUFA UFA SCFA MCFA LCFA -0,4 -0,3 -0,2 -0,1 0 0,1 0,2 0,3 0,4 0 50 100 150 200 250 300 Pheno typic corr elati on wi th MIR CH 4 (g/d) Days in milk
Daily phenotypic correlations between MIR CH4 (g/d) and groups of fatty acids
SFA MUFA PUFA UFA SCFA MCFA LCFA Emphasizing rumen metabolism related to energy status of cows
