ClosedAgriculture & Agri-food

Using machine learning to identify pigs with superior disease resilience to improve animal health and the sustainability of pork production

PROJECT LEAD(S)/CO-LEAD(S) Graham Plastow & Paul Stothard (University of Alberta)
COMPETITION/ FUNDING OPPORTUNITY Genome Alberta - Alberta Applied Agriculture Genomics Program (A3GP)
PROJECT START DATE January 1, 2019
PROJECT END DATE December 31, 2021

Animal resilience directly affects the profitability of livestock production. The goal of this project was to develop tools and methods for selection of pigs that are resilient in the face of multiple natural infections. Analysis of detailed physiology, genomics, and health data of pigs will be analyzed using machine learning technologies. This will allow the accurate prediction of which animals will remain healthy despite exposure to bacterial and viral pathogens and selection for genetic improvement. The omics data assembled through this work will allow for additional models and approaches to be tested relatively quickly with potential for meaningful improvements in the predictability of resilience through the creation of novel tools for pig breeding programs.


Related Projects

Scroll to Top
Copy Link