Prediction Equation Development for Methane‐Related Traits Accounting for Physiological Traits in Japanese Black Cattle

Reducing enteric methane (CH₄) emissions from cattle is a priority in the agricultural sector. The total amount of CH₄ emissions from beef cattle is larger than that from dairy cattle in Japan, and thus, it is important to quantify CH₄ emission from beef cattle. The objective of this study was to investigate the physiological traits associated with methane-related traits and to develop a prediction equation that accounts for these physiological traits in Japanese Black cattle. Enteric CH₄ emission (L/day) was predicted from the concentration of CH₄ to carbon dioxide (CO₂) ratio obtained by the Sniffer method in 156 Japanese Black cattle (111 heifers and 45 steers). In regression tree analysis, methane-related traits, including CH₄, were used as dependent variables, and physiological traits were used as independent variables. Main physiological traits such as ruminal ammonia, propionate, butyrate, beta-hydroxybutyrate, creatine kinase, urea, and valine, which are associated with methane-related traits, were selected through regression tree analysis. The newly developed equations, which include not only feed intake and growth traits but also physiological traits, demonstrate improved prediction accuracy in Japanese Black cattle. These findings indicate that physiological traits can be utilized to develop accurate prediction equations for methane-related traits in Japanese Black cattle.