Transforming Pork Production: Advancing Pig Resilience through Genomics and Machine Learning

Dr. Younes Miar, Assistant Professor of Animal Genomics and Bioinformatics at Dalhousie University, along with his team, is spearheading an innovative research initiative focused on enhancing the resilience and robustness of pigs through advanced genomics and machine learning.

Pork production faces significant challenges in balancing high productivity with animal welfare standards and sustainable environmental practices. Dr. Miar’s work, within Swine Cluster 4, aims to tackle these challenges head-on. By improving key traits such as survival rates and feeding behaviours, this research aims to breed healthier and more resilient pigs that can thrive in changing environments.

Through the application of advanced genomic tools and machine learning, Dr. Miar’s team is identifying and predicting resilience traits in pigs. These traits will help improve survival rates as well as address animal welfare concerns and reduce economic losses caused by high mortality rates. In fact, the Canadian pork sector loses between $240 to $300 million annually due to mortality between weaning and market weight, a significant issue that underscores the need for innovative solutions.

With the goals of reducing mortality, reducing antibiotic use, and ensuring that pigs are raised in more humane and sustainable conditions, this research is set to change the future of pork production in Canada. The use of advanced genomic and machine learning tools could set a new standard for the industry, improving both animal welfare and productivity while meeting the growing demand for sustainable food production.

“By developing genomic tools and machine learning tools and protocols to select resilient pigs, we can increase survival rates, reduce antibiotic use, and meet the public demands for humane and sustainable practices.”

-Dr. Younes Miar

To learn more about this research project, click here.