AI-Enabled Salmon Morphometry Model for the Freshwater Breeding Program

This project will develop an AI-enabled system to help Cooke Inc. automatically measure important physical traits of Atlantic Salmon from standardized images. Today, these measurements, such as weight, length, and body shape, often require manual review or separate scripts, which takes time and can be difficult to scale. The project will create a more efficient and consistent workflow by training machine learning models to extract these measurements and by integrating the process into Cooke’s Snowflake cloud environment for batch processing. This will help Cooke reduce manual effort, improve consistency in data collection and analysis, and support more timely breeding decisions for its freshwater breeding program ahead of the October 2026 spawning season. The project will also create a foundation for future expansion of the same workflow to other species and broader operational use.

Faculty Supervisor:

Andrew Fisher;Stijn De Baerdemacker

Student:

Partner:

Cooke Inc.

Discipline:

Computer science

Sector:

Agriculture

University:

University of New Brunswick

Program:

Business Strategy Internship

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Mitacs — Return on Innovation

Mitacs is funded by the Government of Canada, the Government of Alberta, the Government of British Columbia, Research Manitoba, the Government of New Brunswick, the Government of Newfoundland and Labrador, the Government of Nova Scotia, the Government of Ontario, Innovation PEI, the Government of Quebec, the Government of Saskatchewan, and the Government of Yukon.