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Modeling feed intake in lactating sows during summer considering temperature and humidity covariates
Qianqian Huang1, Maria V Souza1, Hyatt Frobose2
1Department of Animal Sciences, Purdue University, West Lafayette, IN 47907, United States.
Translational Animal Science
|July 9, 2026
Summary
A cubic polynomial model best describes sow feed intake during lactation, outperforming other models. Incorporating environmental factors like temperature and humidity improves accuracy, aiding precision feeding strategies for better sow productivity.
Area of Science:
- Animal Science
- Reproductive Physiology
- Environmental Management in Swine Production
Background:
- Heat stress during lactation negatively impacts sow feed intake (FI) and milk production, consequently limiting piglet growth.
- Accurate modeling of sow FI is crucial for optimizing nutrition and management strategies, especially under varying environmental conditions.
- Previous models may not fully capture the dynamic changes in FI throughout the 22-day lactation period or the complex effects of environmental stressors.
Purpose of the Study:
- To compare alternative mathematical models for describing daily feed intake (FI) in lactating sows over a 22-day period.
- To evaluate the impact of temperature and humidity-related environmental factors on sow FI under commercial farming conditions.
- To identify the most effective modeling approach for incorporating environmental covariates to predict sow FI dynamics.
Main Methods:
- Analyzed daily FI records from 898 lactating sows using mixed-effects models.
- Compared a generalized Michaelis-Menten (GMM) function with a third-order orthogonal polynomial function using diagnostic metrics and cross-validation.
- Incorporated environmental variables (maximum temperature, maximum dew point, degree-hours above 24°C) as linear covariates, interactions, or proportional modifiers.
Main Results:
- The cubic polynomial mixed-effects model (R² = 0.85) showed superior predictive performance over the GMM (R² = 0.82), effectively modeling late-lactation FI declines.
- Parity significantly influenced FI dynamics; multiparous sows had higher FI and steeper early lactation increases than primiparous sows.
- Modeling environmental variables as interactions with lactation day improved fit, indicating day-dependent sensitivity; maximum dew point and its interaction with maximum temperature provided the best fit.
Conclusions:
- Flexible polynomial models combined with multidimensional environmental indicators offer an improved framework for describing lactation FI dynamics in sows.
- Accounting for sow parity and environmental factors, particularly moisture-related heat load, is essential for precise feeding and management.
- These findings support enhanced precision feeding and environmental management strategies in modern sow production systems for improved efficiency and animal welfare.
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