Dynamic model of energy requirements for growing-finishing pigs from meta-analysis and its validation

Abstract

Developing accurate, dynamic feeding formulas for growing-finishing pigs via meta-analysis of large datasets can effectively reduce feed waste from ad libitum feeding and curb environmental pollution from nutrient excretion in feces and urine. This study aims to obtain a dynamic feed formula suitable for growing-finishing pigs through model fitting and to verify its effectiveness. We utilized data from 523 treatments across 112 studies to establish the relationship between daily digestible energy intake and body weight in growing-finishing pigs using three fitting models: linear mixed-effects (LME), Bayesian ridge regression (BRR) and random forest regression (RFR) models. After analysis, LME is the optimized dynamic model. To verify its validity, we selected 16 healthy Duroc × Landrace × Yorkshire crossbred castrated male pigs with an average initial body weight of about 85 kg and randomly assigned them to two groups. The Con group was allowed ad libitum feeding, while the Meta group used the LME model to restrict feeding. After 42 days, the growth performance between the two groups were no significant difference. The Meta group exhibited significantly lower feed-to-gain and average daily feed intake ( P  < 0.05), serum low-density lipoprotein cholesterol and aspartate aminotransferase levels ( P  < 0.05), and an increased abundance of beneficial gut microbial communities. The LME model, a precise and dynamic feeding formula derived from meta-analysis, effectively curbs feed intake while enhancing nutrient utilization and feed efficiency. It also mitigates environmental pollution and positively modulates gut microbiota composition.