Design, implement, and evaluate a precision-fed livestock feeding protocol for dairy cattle welfare and productivity

Thesis Abstract

The precision-fed livestock feeding protocol for dairy cattle addresses the persistent challenge of balancing welfare with productivity by enabling individualized nutrient delivery aligned with physiological states, production goals, and environmental constraints. Despite advances in precision agriculture, practical implementation for dairy cattle remains fragmented, with gaps in real-time feeding adjustments, welfare indicators, and cost-effective productivity gains. This study aims to design, implement, and evaluate a precision-fed feeding regimen that optimizes welfare indicators and milk production while reducing enteric disorders and feed wastage. Specific objectives are (1) to develop a sensor-enabled feeding system that dynamically adjusts concentrate and forage offerings based on rumination, body condition, milk yield, and feed intake; (2) to evaluate the impact of the protocol on welfare indicators (rumination time, ear-tag-based activity, spinal comfort scores) and health outcomes (metabolic profiles, incidence of subclinical ketosis) compared with standard fixed rations; (3) to quantify effects on productivity metrics (fat-and-protein-corrected milk yield, feed efficiency, maintenance costs) and environmental performance (daily feed conversion ratio, methane emissions proxy via surrogate indices); (4) to assess farmer acceptability, economic viability, and scalability under commercial dairy farm conditions. A mixed-methods, quasi-experimental design will be employed over a 12-month period on two commercial dairy farms with similar herd characteristics in a temperate climate. The population comprises lactating Holstein-Friesian cows (n ? 320 per farm). A random subset of 200 cows per farm will be allocated to the precision-fed protocol (treatment) and 120 per farm to conventional feeding (control), matched by parity, days in milk, and baseline production. Data collection will utilize (i) automated sensors for feed intake, bolus-based rumen pH proxies, temperature, activity, and rumination; (ii) on-farm milk recording for daily yields and composition; (iii) periodic veterinary health assessments and bloodmetabolite panels (glucose, NEFA, beta-hydroxybutyrate) every four weeks; (iv) economic records for feed costs, labor, and veterinary interventions. Instruments will include validated welfare scoring systems, calibrated feed analyzers, and a digital data-logging platform integrated with an adaptive control algorithm. Validity and reliability will be established through cross-validation of sensor data against manual observations and laboratory assays, as well as pilot testing to ensure consistent calibration across farms. Data analysis will proceed in three strands. First, descriptive statistics will characterize baseline equivalence and temporal trends. Second, inferential analyses will compare treatment and control groups using linear mixed models for continuous outcomes (milk yield, feed efficiency, metabolic markers) and generalized linear models for binary health outcomes, with farm and parity as random effects and time as a repeated measure. Third, mediation analyses will examine whether welfare indicators mediate the relationship between feeding precision and productivity. The analytical framework will be informed by the Biopsychosocial Welfare Theory and the Nutritional Ecology Theory, integrating animal welfare science with precision nutrition. A cost-benefit analysis will be conducted to determine break-even points, employing Markov decision processes to model long-term profitability under varying milk prices and feed costs. Sensitivity analyses will test robustness to sensor error rates and adherence deviations. Expected findings include (i) improved welfare indicators and metabolic health in the treatment group, evidenced by stable rumination, higher activity congruent with positive welfare, and lower NEFA and ketone body concentrations; (ii) enhanced productivity with greater feed efficiency and stable or increased milk components, without proportional increases in feed costs; (iii) reduced environmental impact signals through improved feed utilization and lower methane emission proxies; (iv) favorable farmer receptivity to the system, with a positive net present value under conservative price scenarios. The study will contribute to knowledge by bridging precision feeding technology with welfare-centric production economics, providing empirical evidence on the systemic benefits and barriers to adoption in commercial dairy operations, and offering a validated protocol and analytical framework for scalable deployment. The conclusion will emphasize that precision-fed protocols, when grounded in real-time welfare and production signals and underpinned by rigorous economic analysis, can simultaneously advance dairy cattle welfare and farm profitability. Recommendations will include guidelines for sensor selection and data governance, phased implementation strategies for farms of varying sizes, and policy implications for incentivizing welfare-aligned precision feeding practices.