Impact of Precision Feeding on Growth and Welfare in Commercial Pigs: Design, Implementation, Evaluation

Thesis Abstract

Precision feeding has emerged as a potential strategy to optimize nutrient use, growth performance, and welfare outcomes in commercial pig production, yet empirical evidence linking specific feeding strategies to measurable welfare indicators under real-world conditions remains limited. This study addresses the problem of suboptimal feed efficiency and welfare compromises arising from conventional feeding regimes by evaluating a precision feeding system that dynamically adjusts nutrient supply based on individual behavioral and physiological signals. The aim is to design, implement, and evaluate a precision feeding protocol that integrates real-time feeding decisions with environmental monitoring to enhance growth performance while safeguarding welfare in market-weight pigs. The specific objectives are (i) to design a precision feeding regimen that employs real-time data on individual pig weight gain potential, activity levels, and feeding rate; (ii) to implement the regimen in a commercial farrow-to-finish operation using an experimental and a control group; (iii) to evaluate growth performance (average daily gain, feed conversion ratio, and final body weight) and welfare indicators (skin lesions, cortisol metabolites, tail/posture assessments, and incidence of stereotypies) over a 20-week period; (iv) to analyze the relationships between feeding precision, nutrient utilization efficiency, and welfare outcomes using mixed-effects models; and (v) to provide evidence-based recommendations for scalable integration of precision feeding into standard management practices. Methodologically, the study employs a quasi-experimental design in a commercial setting with two cohorts of 480 pigs each, starting at weaning (28 days) and followed through to market weight. The precision feeding group receives individualized rations calculated from a dynamic model that integrates body weight, growth trajectory, feed intake history, and ambient temperature, processed via a decision-support system built upon a hierarchical Bayesian framework. The control group continues to receive standard group-based ad libitum feeding. Data collection instruments include automated weighing scales and RFID-linked feeding stations for individual intake, high-resolution video cameras for behavioral analytics, saliva or fecal samples for cortisol metabolite analysis, and environmental sensors recording temperature, humidity, and ammonia levels. Data sources also encompass farm management records for mortality, medical treatments, and carcass traits at harvest. Data analysis will utilize a combination of descriptive statistics, linear and nonlinear mixed-effects models to assess growth and feed efficiency, and generalized linear models for welfare outcomes. Regression analyses will examine predictors of feed efficiency under precision feeding, while time-series analyses will capture dynamic changes in intake and welfare indicators. A multivariate approach, including principal component analysis, will summarize welfare-related metrics. The study will test the hypotheses that precision feeding improves average daily gain and feed conversion ratio without increasing physiological stress indicators, and that welfare measures (e.g., reduced skin lesions, lower cortisol metabolite levels, and fewer abnormal behaviors) are enhanced under the precision regime. Covariates such as parity, litter size, health status, and housing conditions will be controlled within the models. Ethical considerations will follow the institutional animal care and use guidelines, with continuous monitoring to minimize distress. Expected findings include (1) higher feed efficiency and comparable or improved growth rates in the precision-fed pigs; (2) reduced physiological stress markers and a lower incidence of welfare compromises, evidenced by behavioral and biomarker data; (3) a positive correlation between timely nutrient provisioning and fiber-rich diet adjustments with improved carcass quality and meat yield; and (4) scalable guidelines for implementing precision feeding in commercial operations, including cost-benefit analyses under typical market conditions. The study contributes to knowledge by integrating precision nutrition with welfare science in a real-world pig production system, advancing theories of optimal foraging and metabolic regulation under engineered feeding conditions, and providing a practical framework for data-driven management. The main conclusion is that precision feeding, when anchored in robust behavioral and physiological monitoring and implemented through a Bayesian decision-support framework, can simultaneously enhance growth performance and welfare in commercial pigs. Recommendations include adoption of sensor-enabled feeding infrastructure, routine welfare monitoring as a core KPI, training for farm personnel in data interpretation, and further research on long-term welfare effects across production cycles and cross-breed applicability.