Video image analysis as a potential grading system for Uruguayan beef carcasses

Area of Science:

• Agricultural Science
• Animal Science
• Food Science

Background:

• Current Uruguayan beef carcass grading relies on subjective methods (INAC grades).
• Accurate prediction of fabrication yields and tenderness is crucial for value-based pricing systems.

Purpose of the Study:

• Evaluate VIA systems (VIAscan Beef Carcass System and CVS BeefCam) for predicting Uruguayan beef carcass fabrication yields.
• Assess the CVS BeefCam's ability to segregate carcasses based on tenderness (Warner-Bratzler shear force).

Main Methods:

• Two phases: carcass yield prediction and tenderness segregation.
• Utilized VIAscan Beef Carcass System (hot carcass) and CVS BeefCam (chilled carcass).
• Analyzed marbling and muscle color output variables for tenderness prediction.

Main Results:

• VIA systems provided similar or better yield predictions than USDA yield grades and significantly outperformed INAC grades.
• Dual-component VIA systems offer further improvements in yield prediction accuracy.
• CVS BeefCam marbling data did not effectively segregate carcasses by tenderness.
• Muscle color output variables were useful for segregating carcasses by tenderness (WBSF).

Conclusions:

• VIA technology offers a more objective and accurate method for predicting beef carcass fabrication yields compared to current INAC grades.
• Utilizing VIA for muscle color assessment can lead to more consistent beef tenderness, facilitating value-based marketing.
• Implementing VIA systems can improve accuracy, reduce subjectivity, and benefit cattle producers.