Development of genomic evaluation for methane efficiency in Canadian Holsteins

Area of Science:

• Animal Genetics and Breeding
• Environmental Science
• Dairy Science

Background:

• Methane (CH4) emissions from agriculture contribute significantly to global warming.
• Genetic selection offers a permanent strategy to reduce methane emissions in ruminants.
• Canadian Holstein dairy industry implemented a genomic evaluation for methane efficiency (MEF) in April 2023.

Purpose of the Study:

• To implement a single-step genomic evaluation for methane efficiency (MEF) in Canadian Holsteins.
• To reduce methane emissions without compromising milk production traits.
• To utilize milk mid-infrared (MIR) spectral data for predicting individual cow methane production.

Main Methods:

• A single-step, 4-trait animal model was fitted using MiX99 software.
• The model included milk MIR predicted CH4 (CH4MIR), milk yield (MY), fat yield (FY), and protein yield (PY).
• Genomic breeding values for CH4MIR were re-parameterized using genetic linear regression coefficients on production traits to derive MEF.

Main Results:

• Genomic breeding values for CH4MIR were obtained, allowing for the calculation of MEF.
• MEF is genetically independent of production traits (MY, FY, PY).
• Estimated breeding values were expressed as relative breeding values (mean=100, SD=5), with higher values indicating lower predicted CH4 production.

Conclusions:

• The national genomic evaluation for MEF provides a tool to reduce the dairy industry's carbon footprint.
• This approach allows for targeted genetic selection to lower methane emissions without negatively affecting production.
• Continued genetic selection for MEF will contribute to sustainable dairy farming practices.