Software Development to Measure Ultrasonic Images in Beef Cattle

Abstract Ultrasound imaging has been a critical tool in beef cattle genetic selection for over 30 years, enabling producers to evaluate carcass traits in live animals. The goal of this study was to develop and test software capable of measuring ribeye area (REA) and predicting intramuscular fat (IMF) from ultrasound images using artificial intelligence (AI), reducing variability among laboratories and technicians. Data were collected annually from 2021 to 2024 (n = 267) during the Ultrasound Guidelines Council (UGC) Field Certification events hosted by West Texas A 0.001) of actual REA. Pearson’s correlation between actual and AI-predicted values was 0.638, while Spearman’s rank correlation was 0.622, indicating a moderately strong and consistent association between the two variables. AI-derived software is considered to be an accurate predictor of final carcass ribeye size.