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Development of genomic evaluation for methane efficiency in Canadian Holsteins.

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Reducing methane emissions in dairy cows is crucial for mitigating climate change. A new genomic evaluation predicts methane production from milk, enabling genetic selection for methane efficiency without impacting milk yield.

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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.