Achieving precision nutrition in pigs through the utilization of mathematical modeling as a fundamental tool: A review of recent work

The pig industry is entering a new era characterized by artificial intelligence (AI) and interdisciplinary integration, with numerous innovative techniques facilitating the achievement of precision nutrition. This review summarizes relevant research on precision pig nutrition based on mathematical modeling conducted at the Ministry of Agriculture and Rural Affairs Feed Industry Centre (MAFIC), China Agricultural University, and compares these findings with studies from other research groups. Previous studies have shown that mathematical modeling is an effective tool for data integration and prediction. However, models in animal nutrition face challenges such as insufficient data and outdated algorithms. Therefore, developing and applying new data-collection methodologies, advanced algorithms, and platforms are necessary to achieve precision nutrition. Two novel, non-invasive, cost-effective, portable, and reproducible techniques–heart rate monitoring and bioelectrical impedance analysis–facilitate real-time predictions of heat production and enable analysis of body composition in pigs. The newly developed algorithms, including classification algorithms, artificial neural networks, data augmentation algorithms, interpretable machine learning algorithms, and multi-objective formulation algorithms, are utilized to forecast the net energy values of feedstuffs, construct nutrient requirement tables, and predict the growth performance of pigs in the context of big data and numerous parameters. Additionally, introducing new software and hardware, such as establishing big data analysis platforms and AI feed formulation software based on large language model architecture, is also significant. Moreover, future advancements in precision feeding equipment are of great interest. Integrating mathematical models with these new methods, algorithms, and software will enable the precise formulation of personalized nutrition plans and optimal adjustment of dietary structures for pigs, providing robust theoretical and practical guidance for the successful implementation of precision nutrition in pig production.