Prediction of Frozen Semen Doses Production in Dairy Studs using Machine Learning Algorithm

Chandrashekharaiah Jeevan, et.al. Prediction of Frozen Semen Doses Production in Dairy Studs using Machine Learning Algorithm. Indian Journal of Veterinary Sciences and Biotechnology, vol. 18, no. 3, 2022, pp. —.

This study aimed to develop a prediction model for frozen semen doses produced per ejaculate in dairy studs using machine learning techniques. Data from 157,532 ejaculates were modeled using multiple linear regression (MLR) and artificial neural networks (ANN) based on variables such as ejaculate volume, sperm concentration, and motility parameters. ANN outperformed MLR in terms of predictive efficiency, with a higher R² value of 90.66 compared to 73.52 for MLR, and a lower root mean squared error (33.89 vs. 57.31). These results suggest that ANN is a more effective tool for predicting frozen semen doses.