Abstract #M102

# M102
Breeding strategies for mitigating enteric methane emissions of dairy cattle using ZPLAN+.
S. Beard*1, F. Miglior1,2, F. Schenkel1, B. Gredler3, P. Martin1, A. Fleming1, C. Baes1, 1Centre for Genetic Improvement of Livestock, University of Guelph, Guelph, ON, Canada, 2Canadian Dairy Network, Guelph, ON, Canada, 3Qualitas AG, Zug, Switzerland.

Mitigation of methane (CH4) emissions in dairy cattle production has become of particular concern in recent years, as it has been identified as being one of the most prevalent non-CO2 greenhouse gasses contributing to climate change. To date, there have been studies describing the reduction of enteric CH4 emissions through nutritional and microbial manipulation, though there is potential for greater and more permanent progress using genetic selection. It has been shown that there is sufficient genetic variation in enteric CH4 to be possible to reduce its emission through selection programs. Determining an optimal breeding strategy for mitigation of CH4 emissions would help reduce the environmental impact of the Canadian dairy industry. Enteric CH4 production itself is challenging to measure directly, so selection on correlated traits to indirectly reduce CH4 may be more cost effective and less labor intensive. Heritabilities along with genetic and phenotypic correlations between CH4 emission and other traits of interest will be compiled or estimated. ZPLAN+ will be used to simulate and analyze breeding strategies that include CH4 emission as a novel trait. ZPLAN+ is a software that allows the modeling and calculation of complex animal breeding scenarios using genomic information. The software will be used to model genetic gain, monetary returns, and costs associated with including this trait in the selection index for the Canadian Holstein population. Additionally, long-term effects of the proposed selection index and the correlations between CH4 emissions and other traits of interest included in the current breeding strategy will be analyzed. Outputs from this project will provide insight for the Canadian dairy industry as how to best include new information into the existing selection index to reduce CH4 emissions.

Key Words: methane, genomics, animal breeding