Demonstrating the Impact of Genomics-Enhanced Whole Herd Genetic Management Platform on Reducing Beef GHG Emissions

Reducing beef cattle greenhouse gas emissions can be achieved through an effective and accessible genomic selection and whole herd genetic management program

More efficient cattle consume less feed and produce less GHG emissions than inefficient cattle. Additionally, cattle with enhanced retained hybrid vigour (more cross-breeding) have improved reproductive performance and reduced GHG emissions. Beef cattle GHG emissions can be reduced through genetic selection, but the industry lacks effective and science based tools to select and breed more efficient cattle with maximum hybrid vigour. This project aims to demonstrate the genomics enhanced whole herd management platform to the beef industry. The adoption of this tool can help the beef industry make genomic decisions for their herd more easily and contribute towards improved efficiency and sustainability.

Download the full project summary here.


For more information or to participate in the project contact Michael Vinsky:

michael.vinsky@ualberta.ca
https://www.beefgenomicprediction.ca/

Institution: Agriculture and Agri-Food Canada

Primary Investigator: Changxi Li

Co-Primary Investigator: John Basarab (UAlberta), Graham Plastow (UAlberta)

Term: 2021 - 2024

Funding: $487,370 Emissions Reduction Alberta (ERA)

Posted in Beef, Efficiency, Research Topic, Sustainability, Tech Adoption.