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Updated: Aug 28, 2026
The Use of an Automated System (GreenFeed) to Monitor Enteric Methane and Carbon Dioxide Emissions from Ruminant Animals
Published on: September 7, 2015
Disentangling the Interplay Among Genetics, Feeding and Production System Characteristics on Methane Emissions in
Laura Aufmhof1, Lena Fehmer1, Sven König1
1Institute of Animal Breeding and Genetics, Justus-Liebig-University Gießen, 35390 Gießen, Germany.
Abstract:
Methane (CH4) emissions from dairy cattle contribute substantially to agricultural greenhouse gas production and are influenced by genetic, physiological, environmental and management-related factors. The present study investigated CH4-related traits and genotype-system interactions in Holstein Friesian (HF) dairy cows using repeated laser methane detector (LMD)-based measurements. A total of 134 cows from one research herd reflecting a commercial production system were repeatedly recorded for CH4 traits (739 observations per trait) between 2020 and 2024 and linked with milk performance test-day data, behavioral observations, environmental measurements and genomic breeding values. CH4 traits were derived separately for respiration- and eructation-related emissions. Generalized linear mixed models revealed significant effects of wind speed, rumination behavior, interaction behavior and days in milk on several CH4 traits. Across lactation, respiration-related CH4 traits slightly decreased, whereas eructation-related traits increased toward later lactation stages. Correlations between CH4-related breeding values and production traits were generally low to moderately negative, ranging from -0.24 to 0.08, indicating that selection for reduced CH4 emissions may be achievable without major unfavorable effects on milk production traits. To evaluate the complex relationships among CH4 emissions, production, behavior, environment, diet and genetic background, a structural equation model (SEM) was applied. Environmental conditions, particularly temperature and humidity, showed the strongest positive association with CH4 emissions, while eructation-related CH4 traits contributed more strongly to the latent CH4 construct than respiration-related traits. Behavioral activity, especially rumination, indicated relevant associations with CH4 expressions. The SEM further suggested that CH4 emissions are shaped by interconnected environmental, physiological and genetic pathways rather than by a single dominant factor. Overall, the results highlight the importance of environmental sensitivity and longitudinal biological variation in CH4 phenotypes under commercial dairy production conditions. Repeated on-farm CH4 measurements, particularly eructation-associated traits, may provide valuable indicator traits for future genomic breeding and management strategies to reduce the environmental footprint of dairy cattle production.
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