A novel model for estimating the body weight of Pelibuey sheep through Gray Wolf Optimizer algorithm

Weight prediction in live animals remains challenging. Several studies have been carried out trying to predict the body weight in livestock through morphometric measurements, the Schaeffer's model is one of them. However, the fit of those studies in small ruminants is not well covered. Therefore, a novel model to predict the weight of Pelibuey sheep through morphometric measurements and the Gray Wolf Optimizer algorithm is presented. The model involves calculating the volume of the specimen through a truncated cone and leaving density as an estimation parameter of the algorithm. Also, two alternative models were made where the original Schaeffer's model was optimized. The modified models from the original Schaeffer's formula showed improvements up to 22.61% in R-squared and decreases up to 33.48% in RMSE. However, the truncated cone model had the best estimates, with an RMSE of 2.57, R-squared of 89.02%, and the lowest AIC. This represented a 25.13% improvement in R-squared and a 38.31% reduction in the RMSE. The model is expected to improve its efficiency if the cattle sample is larger, and it is also intended to be implemented in animals of other proportions.