Location: Poultry Research
Project Number: 6064-32630-010-008-A
Project Type: Cooperative Agreement
Start Date: Jul 1, 2026
End Date: Jun 30, 2028
Objective:
Conduct research to apply advanced machine learning, computer vision, and artificial intelligence techniques toward developing precision poultry management tools aimed at reducing fertility and hatchability losses in broiler breeder eggs. Specific research objectives include: 1) Developing a sampling system capable of detecting bacterial contamination in breeder eggs. 2) Characterizing storage conditions that influence the likelihood or severity of bacterial contamination in breeder eggs.
Approach:
This project aims to reduce bacterial contamination in fertile broiler breeder eggs by developing rapid detection tools and identifying key storage factors that influence contamination risk. The research will create a non destructive imaging system using advanced machine learning to quickly identify contaminated eggs during early incubation. In parallel, controlled studies of temperature, humidity, and air exchange will clarify how storage conditions affect bacterial growth and penetration. Together, these efforts will provide science based guidance and new technology to improve fertility, hatchability, and overall flock health.