Predicting methane emissions from dairy cattle using milk fatty acid profile

Relationship between enteric methane yield and milk fatty acid (FA) profile, as indicated previously with small databases, has now been confirmed with a large database.
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Researchers from the Animal Nutrition Group of Wageningen University and of the University of Reading (UK) published an extensive meta-analysis of relationships between enteric methane yield and milk fatty acid (FA) profile in dairy cattle in the Journal of Dairy Science.

 

The meta-analysis was performed with a dataset that consisted of 8 different studies. Forage proportion in these studies varied between 50 and 80% of total diet, with forage consisting of grass silage and corn silage in ratios ranging from 0:100 to 100:0. Data of treatments with lipid supplements and other ingredients with a potential to reduce CH4 yield were included in the database as well. The prediction equations obtained from this meta-analysis are thus based on a significantly larger variety of diets than used for prediction equations developed previously.
Methane yield per unit of feed was best predicted (R2 = 0.54) using multiple regression with milk fat concentrations of C16:0-iso, trans-10+11-C18:1 and cis-9,12-C18:2. Methane yield per unit of fat and protein corrected milk was best predicted (R2 = 0.47) with milk fat concentrations of C4:0, C16:0-iso, cis-9-C18:1 and trans-10+11-C18:1. Evaluating concentrations of single FA indicated various even-chain FA to be positively related to methane yield, while several unsaturated long-chain FA concentrations appeared to be negatively related to methane yield. Relationships between concentrations of odd- and branched-chain FA in milk and CH4 yield were weak or absent, and also less than expected based on theory of rumen fermentation products and CH4 yield. The results of this meta-analysis indicate moderate potential for using milk FA profile to predict CH4 yield per unit of feed and per unit of milk.
The review has been published in Journal of Dairy Science and is available via the this link.
The project is partly funded by TI Food and Nutrition, a public-private partnership on precompetitive research in food and nutrition. The public partners are responsible for the study design, data collection and analysis, decision to publish, and preparation of the manuscript. The private partners have contributed to the project through regular discussion. The financial support of UK Defra projects LS3656 and AC0209 and Marks and Spencer is gratefully acknowledged for studies at the University of Reading. Authors acknowledge financial support of SenterNovem, an agency of the Dutch Ministry of Economic Affairs, to obtain part of the data on DMI, milk production and CH4 production.

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