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Integrating genomic approaches to improve dairy cattle resilience: A comprehensive goal to enhance Canadian dairy industry sustainability

PROJECT LEAD(S)/CO-LEAD(S) Christine Baes (University of Guelph), Marc-Andre Sirard (Universite Laval), Paul Stothard (University of Alberta), & Ronaldo Cerri (University of British Columbia)
COMPETITION/ FUNDING OPPORTUNITY Genome Canada 2018 Large-Scale Applied Research Competition
PROJECT START DATE January 1, 2020
PROJECT END DATE June 30, 2025
ALBERTA’S ROLE Lead
Why is this research important to Alberta?
  • Dairy is vital to Canada’s economy, generating $7.13B in net farm cash receipts and contributing $20B to GDP in 2020.
  • Alberta is the fourth largest milk producing province in Canada with over 500 dairy farms.
  • Despite this success, the dairy industry is also facing a number of emerging issues important to governments and consumers, related to human and animal health, environmental impacts, sustainability and social acceptability.

This project has delivered multiple impactful new genomic tools to benefit Alberta and the Canadian dairy sector, including:

  • Evaluations for fertility disorders
  • Feed efficiency
  • Methane efficiency
  • Body maintenance requirements
  • Calf health; a revised selection index including overall health,
  • Environmental impact subindexes,
  • First and only country in the world to include a methane trait in its breeding goal.
What is the goal of this work? How will genomics be used?
  • The objective is to develop genomic tools to enable implementation of selection to increase dairy cow resilience (capacity of the animal to adapt rapidly to changing environmental conditions, without compromising its productivity, health or fertility while becoming more resource-efficient and reducing its environmental burden).
  • New evaluations for health and environmental efficiency, and relative indexes have been developed and implemented by the industry.
  • Machine learning was key to developing a prediction of methane using milk spectral data.
  • We worked with i
  • Genomics is being used to predict resilience, which cows are more likely to stay fertile, stay healthy, and produce efficiently.
  • Those signals are combined with herd records to create an index, so breeders can select the best animals earlier and accurately, accelerating progress toward lower costs and a smaller environmental footprint.
What are the expected benefits, and how will the research findings be shared?
  • The availability of feed efficiency evaluations has yielded a savings of ~$100/cow/year.
  • Furthermore, selection for feed efficiency is expected to result in a concomitant decrease in methane emissions of about 13kg per cow per lactation, i.e. from 120kg to 107 kg average per cow per lactation.
  • This decrease, originating from feed efficiency selection, will decrease average methane emission by 11% after direct selection for low methane emissions, with an additional reduction of 20% by 2050.
  • Thus, the full impact on the Canadian dairy industry will be ~$97M/year (~$24M for western Canada, including ~$8M annual savings for Alberta).
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