Modeling feed intake in lactating sows during summer considering temperature and humidity covariates

Abstract Heat stress during lactation reduces voluntary feed intake (FI) and milk production in sows, thereby limiting piglet growth. In this context, the main objectives of this study were to compare alternative models for describing daily FI over a 22-d lactation and to evaluate temperature- and humidity-related environmental covariates under commercial conditions. Daily FI records from 898 lactating sows (parity 1: 503, parity 2: 138, parity 3 and higher: 257) were analyzed using mixed-effects models. The generalized Michaelis–Menten (GMM) function was compared against a third-order orthogonal polynomial function using model diagnostic metrics and a sow-level cross-validation. To account for thermal stress, we incorporated daily maximum air temperature (MT), daily maximum dew point (MD), and degree-hours above 24 °C (DGH24) into the models. These environmental indicators were evaluated as fixed linear covariates, as interactions with lactation time components, or as proportional modifiers to the base intake curve. The cubic polynomial mixed-effects model (R2 = 0.85) demonstrated superior out-of-sample predictive performance relative to the GMM (R2 = 0.82) by accommodating late-lactation declines in FI. Parity significantly affected FI dynamics, with multiparous sows exhibiting greater overall FI and steeper early lactation increases than primiparous sows. Modeling environmental variables as interactions with lactation day improved model fit in comparison to fixed linear covariates and proportional modifiers, indicating lactation-day–dependent environmental sensitivity. Among single covariates, MD provided the best fit (AIC = 49,829), and a joint MT + MD interaction model achieved the strongest overall performance (AIC = 49,793). These findings demonstrate that flexible polynomial models combined with multidimensional environmental indicators provide an improved framework for describing lactation FI dynamics. Accounting for parity and moisture-related heat load may enhance precision feeding and environmental management strategies in modern sow production systems.