Genetic parameters for methane emission traits in Australian dairy cows

Area of Science:

• Animal Science
• Agricultural Science
• Environmental Science

Background:

• Enteric methane from dairy cattle is a significant greenhouse gas emission, contributing to environmental concerns and energy loss.
• Genetic selection presents a viable strategy to mitigate methane emissions and enhance energy efficiency in dairy cows.
• Standardized methods for calculating residual methane production are lacking, hindering effective genetic improvement strategies.

Purpose of the Study:

• To evaluate and compare nine different methods for calculating residual methane production in dairy cattle.
• To assess the heritability and genetic/phenotypic correlations among various residual methane production traits.
• To determine the most effective approach for genetic selection to reduce methane emissions without compromising economic traits.

Main Methods:

• Utilized SF6 tracer method for methane measurement and electronic feed recording for dry matter intake (DMI) in 379 cows over five years.
• Calculated residual methane production using nine distinct genetic and phenotypic regression methods incorporating DMI and energy-corrected milk (ECM).
• Employed univariate and bivariate models to estimate heritability and correlations, using direct genomic values (DGV) for FeedSaved as a proxy for DMI DGV.

Main Results:

• Residual methane production traits exhibited low to moderate heritability (0.10-0.21), with ECM-corrected residual methane showing the highest heritability.
• All nine definitions of residual methane were highly phenotypically (>0.87) and genetically (>0.79) correlated.
• Moderate to high correlations (>0.59) were observed between residual methane traits and other methane candidate traits, despite high standard errors.

Conclusions:

• Direct genetic selection for a residual methane trait is likely to yield favorable indirect improvements across all methane-related traits.
• The high correlations suggest that focusing on one well-defined residual methane trait could be effective for breeding programs.
• Expansion of data sets and international collaboration are crucial for reducing standard errors and refining genetic selection strategies for methane reduction in dairy cattle.