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Updated: Jun 23, 2026

The Use of an Automated System GreenFeed to Monitor Enteric Methane and Carbon Dioxide Emissions from Ruminant Animals
Published on: September 7, 2015
Milk Fatty Acids as Potential Biomarkers of Enteric Methane Emissions in Dairy Cattle: A Review
Emily C Youngmark1, Jana Kraft1,2,3
1Department of Animal and Veterinary Sciences, The University of Vermont, Burlington, VT 05405, USA.
Abstract:
Measuring methane (CH4) emissions from dairy systems is crucial for advancing sustainable agricultural practices aimed at mitigating climate change. However, current CH4 measurement techniques are primarily designed for controlled research settings and are not readily scalable to diverse production environments. Thus, there is a need to develop accessible, production-level methods for estimating CH4 emissions. This review examines the relationship between enteric CH4 emissions and milk fatty acid (FA) composition, highlights key FA groups with potential as biomarkers for indirect CH4 estimation, and outlines critical factors of predictive model development. Several milk FAs exhibit strong and consistent correlations to CH4 emissions, supporting their utility as predictive biomarkers. Saturated and branched-chain FAs are generally positively associated with CH4 emissions, while unsaturated FAs, including linolenic acid, conjugated linoleic acids, and odd-chain FAs, are typically negatively associated. Variability in the strength and direction of correlations across studies is often attributable to differences in diet or lactation stage. Similarly, differences in experimental design, data processing, and model development contribute to much of the variation observed in predictive equations across studies. Future research should aim to (1) identify milk FAs that consistently correlate with CH4 emissions regardless of diet, (2) develop robust and standardized prediction models, and (3) prioritize the external validation of prediction models across herds and production systems.

