Predicting beef carcass composition using tissue weights of a primal cut assessed by computed tomography

Area of Science:

• Animal Science
• Agricultural Technology
• Imaging Science

Background:

• Accurate assessment of beef carcass composition is crucial for livestock breeding and research.
• Traditional dissection methods are time-consuming and destructive.
• Non-invasive imaging techniques offer a potential alternative for rapid composition analysis.

Purpose of the Study:

• To evaluate the potential of X-ray computed tomography (CT) measurements of the forerib to predict overall carcass composition in beef cattle.
• To compare the accuracy of CT-based predictions with traditional dissection methods.
• To assess the utility of CT scanning for large-scale animal studies and breeding programs.

Main Methods:

• Computed tomography (CT) scanning was performed on 20 cuts from the left side of 73 beef carcasses (Aberdeen Angus and Limousin crossbreds).
• Carcasses and forerib sections were dissected to determine actual fat, muscle, and bone weights.
• CT data from the forerib was used in regression models to predict carcass composition, with and without breed and sex factors, and carcass/forerib weights.

Main Results:

• CT scanning of primal cuts accurately predicted carcass composition (adj-R2 = 0.97).
• Forerib CT measurements predicted forerib fat, muscle, and bone weights with high accuracy (adj-R2 = 0.95, 0.91, 0.75).
• Single forerib CT predictors estimated carcass fat, muscle, and bone with adj-R2 of 0.79, 0.60, and 0.52, respectively, improving with breed/sex data and carcass/forerib weights (up to 0.96 for muscle).

Conclusions:

• X-ray computed tomography (CT) is a highly accurate and rapid method for assessing beef carcass composition.
• CT scanning of the forerib shows significant potential for predicting carcass fat and muscle content.
• This technology can be a valuable tool for livestock breeding programs and research requiring efficient, non-destructive composition analysis.