Genetic Parameters of Methane Emission, Feed Efficiency, Feeding Behaviour, and Growth Traits in Beef Cattle

Climate change has intensified the need to reduce greenhouse gas emissions, particularly methane (CH₄) from enteric fermentation. Genetic selection has emerged as a promising mitigation strategy; however, studies on Bos taurus indicus, especially Nellore cattle, remain limited. This study aimed to estimate heritabilities and genetic correlations for CH₄ emission traits and their relationships with feeding behaviour, feed efficiency, and performance, as well as to evaluate the direct and correlated responses to selection for lower CH₄ emissions. Data were from 2418 Nellore cattle evaluated in feed efficiency trials. Traits included dry matter intake (DMI), feeding time per day (FTd), feed events per day (FEd), and feeding rate (FR), residual feed intake (RFI), average daily gain (ADG), and mid-test body weight (MBW). Methane emissions were measured in 1153 animals using the SF₆ tracer technique, providing daily CH₄ emission (g/day), CH₄ per unit of DMI (CH₄DMI, g/day), and residual CH₄ (CH₄res). Variance components were estimated using the single-step genomic BLUP (ssGBLUP) method through Bayesian inference. Heritability estimates were moderate for CH₄ (0.25), CH₄DMI (0.14), CH₄res (0.14), and performance traits such as DMI (0.35), ADG (0.36), and MBW (0.40). Higher estimates were observed for feeding behaviour traits FTd (0.49) and FR (0.42). Genetic correlations between CH₄ and production traits were high, particularly with DMI (0.79), ADG (0.90), and MBW (0.91), indicating that selection for reduced CH₄ emissions may affect growth. Direct selection for CH₄ led to a modest annual reduction in emissions but also a correlated decline in MBW. These results demonstrate that while CH₄ emissions are heritable, their strong genetic association with productivity traits indicates that isolated selection for reduced emissions may lead to undesirable outcomes in feed intake and performance. Therefore, strategies aiming to reduce CH₄ emissions should consider the genetic relationships with growth and efficiency traits to avoid compromising animal productivity.