Stage-specific prediction of body weight in Hanwoo steers using body measurements and nutrient intake variables

Objective: Accurate body weight (BW) prediction is important for growth management and nutrient utilization in Hanwoo steers.However, prediction performance may vary across growth stages and input variables.Therefore, this study evaluated stage-specific machine learning models for BW prediction using body measurements and nutrient intake variables.This study investigated stage-dependent factors associated with body weight (BW) and average daily gain (ADG) and evaluated the predictive performance of machine learning (ML) models using body size traits and nutrient intake variables in Hanwoo steers.Methods: Data from 136 Hanwoo steers were collected during the growing (6-12 months), early fattening (13-21 months), and late fattening (22-31 months) periods.Body size traits and nutrient intake variables were used to develop prediction models using Random Forest (RF), Linear Regression (LR), K-Nearest Neighbors (KNN), and Artificial Neural Networks (ANN).To minimize repeatedmeasurement bias, datasets were divided into training and testing sets based on individual animal identification.Prediction performance was evaluated using coefficient of determination (R²), root mean square error (RMSE), and mean absolute error (MAE).Results: BW showed strong associations with skeletal-related body traits during the growing period, whereas nutrient intake variables became more strongly associated with average daily gain (ADG) during the fattening periods.Among the evaluated ML models, RF generally demonstrated robust predictive performance across growth stages.For BW prediction, RF achieved the highest prediction accuracy during the growing period (R² = 0.952), whereas LR achieved the highest prediction accuracy during the early-fattening period (R² = 0.947).Prediction performance for ADG was generally lower than that for BW.Variable importance analysis indicated that skeletal-related body traits contributed most to BW prediction, whereas nutrient intake variables contributed more to ADG prediction during fattening.Conclusion: Factors associated with BW and ADG in Hanwoo steers differed according to production stage.Skeletal-related body traits were more strongly associated with BW during the growing period, whereas nutrient intake variables became increasingly important during the fattening stages.The present findings suggest that integrating body measurements and nutritional information may contribute to stage-specific growth monitoring and provide preliminary information for developing nutritional management strategies in Hanwoo production systems. 메모 포함[u1]:Response: Revised accordingly.The rationale and necessity of the study were added to the Objective section of the Abstract to clarify the need for stage-specific prediction of body weight and average daily gain using body measurements and nutrient intake variables in Hanwoo steers.