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Use of accelerometers and AI to predict woody breast in broilers

USPOULTRY and the USPOULTRY Foundation announce the completion of a funded research project at the University of Arkansas. Researchers used accelerometers and artificial intelligence (AI) to predict the presence of woody breast (WB) in broilers.

The research was made possible in part by an endowing Foundation gift from George’s Inc. and is part of the Association’s Comprehensive Research Program encompassing all phases of poultry and egg production and processing.

Project #721, entitled: The Use of Accelerometers and Artificial Intelligence to Predict Presence of Woody Breast in Live Broilers Throughout Growout and Broiler Fillets, was led by Dr. Casey Owens, Department of Poultry Science, University of Arkansas.

Research introduction:

The broiler industry has been challenged with a condition called “woody breast” for the past 8-10 years, which can affect a significant proportion of products produced.

Objective

To evaluate the use of accelerometers on live broilers to identify birds exhibiting WB characteristics and to evaluate vibration patterns of deboned fillets with varying degrees of woody breast severity.

Summary of the research:

In order to refine the methodology and improve the performance of detection, multiple trials were conducted on raw breast fillets. The accuracy of detection methods utilized varied between 60% and 85%.

As with other candidate detection methods, breast fillets labeled to be in the mild category of the woody breast often lowered accuracy.

In the live bird accelerometer studies, detection accuracy was generally lower than with fillets alone. While, at times, accelerometer patterns (i.e., vibration) showed some differences between normal, moderate, and severe woody breasts, it was not always consistent.

Because the accelerometer is

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