Estimation of genetic parameters for milk mid-infrared-predicted methane production in Holstein dairy cattle

Livestock methane emissions contribute to 18% of global greenhouse gas emissions. Integrating methane production into breeding goals has the potential to mitigate methane emissions and contribute to more sustainable livestock systems. To achieve this through genetic selection, large datasets of phenotypic records are required, making the use of direct measurement of methane emissions limited on a broad scale. Consequently, alternative approaches, such as using predicted methane emissions derived from more easily measured traits, have been proposed. The objective of this study was to estimate the genetic parameters of weekly average milk mid-infrared-predicted methane production (PCH₄) and its genetic correlation with milk yield (MY), fat yield (FY), and protein yield (PY) in Canadian Holstein dairy cows. We analyzed a total of 37,202 PCH₄ records and corresponding test-day records for MY, FY, and PY collected between 119 and 179 DIM from 18,505 first-lactation Canadian Holstein cows distributed over 100 herds. Several statistical models were evaluated to estimate the genetic parameters of PCH₄. These included a single-trait model and 3 separate 2-trait random regression models that employed fifth-degree Legendre polynomials on weeks of lactation. The estimated heritability of PCH₄ ranged from 0.37 (SE = 0.06) to 0.45 (SE = 0.02), indicating a moderate genetic influence on predicted methane production. The genetic correlations between PCH₄ and test-day MY, FY, and PY ranged from -0.23 (SE = 0.06) to -0.13 (SE = 0.06), 0.3 (SE = 0.06) to 0.48 (SE = 0.08), -0.17 (SE = 0.07) to -0.09 (SE = 0.06), respectively, suggesting low to moderate associations between PCH₄ and the production traits. These results suggest that PCH₄ is moderately heritable and can be used for genetic selection to mitigate methane emissions in dairy cows. However, the positive unfavorable genetic correlation with FY should be considered when selecting animals for lower PCH₄ to avoid potential negative impacts on fat yield. These findings contribute to the ongoing efforts to improve the environmental sustainability of the livestock industry while maintaining productivity.