Integrating Variability of Growing Pigs in Nutritional Requirement Modeling to Optimize Feeding Strategies

This work characterizes growth variability among pigs from ten crossbreeds using data from 1288 individuals to estimate variance and covariance parameters. A new virtual pig population generator was created to simulate the effects of feeding strategies on growth performance and nitrogen output. Simulation outcomes were closely aligned with results from an in vivo feeding trial, confirming the model’s accuracy. By integrating individual variability into nutritional requirement models, this approach supports the development of precision feeding tools aimed at reducing feed costs and minimizing environmental nitrogen losses in pig production.