Investigating rumination and eating time as proxies for identifying dairy cows with low methane-emitting potential

Abstract

Identifying cows with low CH₄-emitting potential can greatly contribute to CH₄ abatement in dairy herds. However, this process has been cumbersome and labor-intensive. Ear tags and collar-based accelerometers measure rumination and chewing behaviors, potentially identifying novel phenotypes in cows. This study aimed to determine whether rumination and eating time are linked to enteric CH₄ emissions and serve as proxies to identify CH₄ yield phenotype in lactating dairy cows. We applied the dynamic time warping model to rumination and eating time datasets to classify cows differing in these phenotypes. We calculated the distances between cows differing in rumination and eating times and depicted them in a principal component analysis plot. From 49 cows in early to mid lactation, 10 low-rumination, and 10 high-rumination cows were selected to test the relationship between rumination and eating time with CH₄ yield phenotype over 7 wk. Enteric CH₄ emissions were measured using the GreenFeed System. The dynamic time warping model identified cows with distinct rumination and eating patterns. High-rumination cows had higher DMI and milk yield, and lower enteric CH₄ emissions than low-rumination cows. High-rumination cows also had lower CH₄ intensity and higher production efficiency than low-rumination cows. Overall, rumination and eating time can be suitable proxies for identifying CH₄ yield phenotype in dairy cows. Further studies, including larger dairy herds, different dietary regimens, and stages of lactation in dairy cattle and other ruminant species to validate rumination and eating time as proxies for identifying CH₄ yield phenotype, are required.