Innovative Use of Feeding Behavior in Predicting Broiler Chicken Health

The Cobb R&D team has partnered with researchers from the University of Georgia and the University of Wisconsin-Madison to explore a groundbreaking approach to poultry health management. This collaboration seeks to understand whether feeding behavior can serve as an effective predictor of health issues in broiler chickens. Research has shown that animals, including chickens, often alter their eating patterns, social behaviors, and overall activity levels when they face illness or injury.

A New Experiment Design

With this knowledge in mind, Cobb R&D and their collaborators devised a comprehensive experiment to monitor the feeding behaviors of broiler chickens using advanced technology. The experiment involved fitting birds with radio-frequency identification (RFID) transponders on their wings. Feeding stations, equipped with antennas and specially designed by Cobb’s engineering team, limited access to one bird at a time. This innovative setup enabled researchers to track and analyze metrics on an individual level.

Extensive Data Collection

Over a 5-year span, the experiment followed more than 95,000 broiler chickens and culminated in the collection of an impressive dataset comprising nearly 100 million feeder visits. The data was categorized into various feeding traits, including:

• Feed intake
• Number of visits
• Time spent at the feeder
• Time intervals between feeder visits
• Number of feeders visited

Additionally, the feeders were equipped with scales to measure the feeding amount (in grams per meal) and feeding rate (in grams per hour), providing even deeper insights into the birds’ eating behaviors.

Leveraging Machine Learning

The collected data underwent analysis using five different machine learning models, each utilizing distinct classification systems aimed at identifying subtle behavioral patterns that could indicate illness. The results showed two models—Gradient Boosting Machine (GBM) and Support Vector Machine (SVM)—performed particularly well, enabling mortality predictions 1 to 3 days in advance of actual events.

Benefits of Early Intervention

Implementing such a predictive system on farms offers substantial benefits. Early intervention for ill or injured birds can significantly enhance animal welfare and mitigate economic losses. Moreover, this automated monitoring system can improve biosecurity by lessening the need for routine in-house flock inspections, thereby reducing potential stress on the birds.

Future Implications

This innovative system not only assists in current flock management but also accumulates valuable data that can inform future managerial decisions, making them more precise and strategic. With ongoing research and development, this technology holds the promise of transforming poultry health management, leading to better outcomes for both chickens and farmers alike.

For more details on this groundbreaking research, read the full article here.

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