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Prediction of enteric methane emissions from Holstein dairy cows fed various forage sources

Published online by Cambridge University Press:  24 September 2015

D. E. Rico
Affiliation:
Département des sciences animales, Université Laval, 2425 rue de l’Agriculture, Québec, QC, Canada, G1V 0A6
P. Y. Chouinard
Affiliation:
Département des sciences animales, Université Laval, 2425 rue de l’Agriculture, Québec, QC, Canada, G1V 0A6
F. Hassanat
Affiliation:
Agriculture and Agri-Food Canada, Dairy and Swine Research and Development Centre, 2000 College Street, Sherbrooke, QC, Canada, J1M 0C8
C. Benchaar
Affiliation:
Agriculture and Agri-Food Canada, Dairy and Swine Research and Development Centre, 2000 College Street, Sherbrooke, QC, Canada, J1M 0C8
R. Gervais*
Affiliation:
Département des sciences animales, Université Laval, 2425 rue de l’Agriculture, Québec, QC, Canada, G1V 0A6
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Abstract

Milk fatty acid (FA) profile has been previously used as a predictor of enteric CH4 output in dairy cows fed diets supplemented with plant oils, which can potentially impact ruminal fermentation. The objective of this study was to investigate the relationships between milk FA and enteric CH4 emissions in lactating dairy cows fed different types of forages in the context of commonly fed diets. A total of 81 observations from three separate 3×3 Latin square design (32-day periods) experiments including a total of 27 lactating cows (96±27 days in milk; mean±SD) were used. Dietary forages were included at 60% of ration dry matter and were as follows: (1) 100% corn silage, (2) 100% alfalfa silage, (3) 100% barley silage, (4) 100% timothy silage, (5) 50 : 50 mix of corn and alfalfa silages, (6) 50 : 50 mix of barley and corn silages and (7) 50 : 50 mix of timothy and alfalfa silages. Enteric CH4 output was measured using respiration chambers during 3 consecutive days. Milk was sampled during the last 7 days of each period and analyzed for components and FA profile. Test variables included dry matter intake (DMI; kg/day), NDF (%), ether extract (%), milk yield (kg/day), milk components (%) and individual milk FA (% of total FA). Candidate multivariate models were obtained using the Least Absolute Shrinkage and Selection Operator and Least-Angle Regression methods based on the Schwarz Bayesian Criterion. Data were then fitted into a random regression using the MIXED procedure including the random effects of cow, period and study. A positive correlation was observed between CH4 and DMI (r=0.59, P<0.001), whereas negative associations were observed between CH4 and cis9-17:1 (r=−0.58, P<0.001), and trans8, cis13-18:2 (r=−0.51, P<0.001). Three different candidate models were selected and the best fit candidate model predicted CH4 with a coefficient of determination of 0.84 after correction for cow, period and study effects and was: CH4 (g/day)=319.7−57.4×15:0−13.8×cis9-17:1−39.5×trans10-18:1−59.9×cis11-18:1−253.1×trans8, cis12-18:2−642.7×trans8, cis13-18:2−195.7×trans11, cis15-18:2+16.5×DMI. Overall and linear prediction biases of all models were not significant (P>0.19). Milk FA profile and DMI can be used to predict CH4 emissions in dairy cows across a wide range of dietary forage sources.

Type
Research Article
Copyright
© The Animal Consortium 2015 

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