Development of an Automatic Pork Quality Grading (APoG) System for Sustainable Pork Production

Project Lead

MatrixSpec Solutions Inc., Baie-Durfé, QC

Project Partners

Canadian Centre for Swine Improvement, Ottawa, ON

Motsai Research Inc., Saint-Bruno, QC

Project Description

This project seeks to develop an automatic pork quality grading (APoG) system using hyperspectral imaging, machine learning, and deep learning for online multidimensional pork quality trait assessment of entire pork loins. Sustainability of the technology will be assessed to enhance data-driven quality management. The proposed APoG technology will address a current automation hurdle in the industry by providing an innovative and intelligent solution for automatic and objective pork quality grading.

Project Innovation

• Design and develop an automatic pork quality grading (APoG) system based on computer vision, machine learning, and deep learning methods, as well as hyperspectral imaging technology to assess multidimensional traits (colour, marbling score, and firmness of the entire pork loin) automatically.
• Test and validate the performance of the APoG prototype in a pork processing environment to fine-tune and facilitate the technical advancement and maturity of the technology.

Project Investment

CAAIN Contribution
$325,707

Total Project Value
$846,839

Project Contact

Dr. Laura Liu
Chief Technology Officer
MatrixSpec Solutions Inc.
info@matrixspec.ai
514.457.4000