Smart In-Ovo Sexing: Enhancing Performance of the Hyper-Eye System

Project Lead

MatrixSpec Solutions Inc., Baie-Durfé, QC

Project Partners

Egg Farmers of Ontario, Mississauga, ON

McKinley Hatchery Ltd., St. Marys, ON

Project Description

The proposed project will advance the Hyper-Eye system towards commercialisation by enhancing its performance. The project partners will identify and remove egg samples that are incorrectly positioned or that are of low quality. The detection protocols will be integrated into the Hyper-Eye technology to achieve consistent, high-performance operation, making it increasingly compatible for hatchery use. When operational, the system will solve serious welfare issues in the layer sector and will significantly improve the operational efficiency and sustainability of the poultry industry.

Project Innovation

• Use computer vision, machine learning, and deep learning to develop a positioning protocol to identify eggs with incorrect imaging position (small end up).
• Use spectral image processing, pattern recognition, machine learning, and deep learning to create a quality assessment protocol to identify poor quality (i.e., cracked) eggs.
• Build automated egg sexing quality assurance software based on the positioning and quality assessment protocols, and enhance performance by integrating the software into the Hyper-Eye system for automatic pre-classification sample screening.

Project Investment

CAAIN Contribution
$506,960

Total Project Value
$1,449,656

Project Contact

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