Acceleration of improvement in health and production of mink through genomics and machine learning

The project will examine of population genomics, application of genomic selection, and identification of genes underlying economically important traits which are vital steps for the development of selection program. Consequently, this will have an impact on the economic viability of mink producers due to targeted genomic breeding strategies and the use of biomarker-assisted selection. Such a selection over a period will significantly lower the cost of pelt production and hence increase efficiency. The selection for disease resistance (such as Aleutian Diseases) will also create the mink with better resilience. The project will generate results that can be directly implemented in the breeding programs of North American mink industry. These tools will enable the mink breeders to more effectively incorporate feed efficiency, health and reproduction traits as breeding objectives in their programs. Farmers will save money, while the international competitiveness of North America’s mink industry will increase. The environmental footprint of the mink industry will also be reduced because lower manure waste will be produced by more feed efficient or higher prolific animals.

Faculty Supervisor:

Younes Miar

Student:

Partner:

Canada Mink Breeders Association

Discipline:

Life Sciences

Sector:

Agriculture

University:

Dalhousie University

Program: