Milk Fatty Acids as Potential Biomarkers of Enteric Methane Emissions in Dairy Cattle: A Review.

Measuring methane (CH) emissions from dairy systems is crucial for advancing sustainable agricultural practices aimed at mitigating climate change. However, current CH 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 CH emissions. This review examines the relationship between enteric CH emissions and milk fatty acid (FA) composition, highlights key FA groups with potential as biomarkers for indirect CH estimation, and outlines critical factors of predictive model development. Several milk FAs exhibit strong and consistent correlations to CH emissions, supporting their utility as predictive biomarkers. Saturated and branched-chain FAs are generally positively associated with CH 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 CH 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.