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Genetic parameters for predicted methane production and laser methane detector measurements
N K Pickering1, M G G Chagunda2, G Banos2
1Animal Genomics Team, Invermay Agricultural Centre, AgResearch Limited, Private Bag 50034, Mosgiel, New Zealand.
Journal of Animal Science
|November 19, 2014
Summary
Reducing enteric methane emissions in dairy cows through genetic selection is crucial for sustainable agriculture. This study developed a predicted methane emission (PME) trait, finding a high genetic correlation with dry matter intake (DMI), offering a promising avenue for breeding programs.
Area of Science:
- Agricultural Science
- Animal Genetics
- Environmental Science
Background:
- Enteric methane from ruminants is a major greenhouse gas in agriculture.
- Genetic improvement offers a permanent solution to reduce methane emissions.
- High-density SNP panels can accelerate genetic gain for livestock traits.
Purpose of the Study:
- To develop a predicted methane emission (PME) trait for dairy cows.
- To assess the heritability and genetic correlations of PME with other production traits.
- To explore the potential of genomic selection for reducing methane emissions.
Main Methods:
- Utilized a dataset of 1,726 dairy cows with data since 1990.
- Calculated PME based on feed intake, energy requirements, milk yield, live weight, and condition score.
- Incorporated laser methane detector (LMD) data from 57 cows for validation.
Main Results:
- Estimated heritability for PME was 0.13, with high heritability for live weight (0.92) and condition score (0.38).
- A high genetic correlation was observed between dry matter intake (DMI) and PME.
- Genomic prediction accuracies for PME ranged from 0.26 to 0.30, with no SNPs reaching Bonferroni significance.
Conclusions:
- Developing a PME trait is feasible and shows potential for genetic selection in dairy cattle.
- High genetic correlation with DMI suggests indirect selection may reduce methane emissions.
- Further research is needed to implement PME effectively in breeding programs.
