Data-Driven Livestock Welfare Assessment for Sustainable Environmental Management in Intensive Production Systems

Abstract

Integrated assessment systems which can deliver a measurement of animal welfare and environmental performance in a work-like environment are more and more becoming important in sustainable livestock production. In this research, we developed and used a scientific-based monitoring system on intensive pig housing that integrated standardised microclimatic observations with animal-based welfare outcomes to define essential factors regarding the loss of welfare and ecological efficiency. The environmental variables (air temperature, relative humidity, gaseous pollutants and particulate matter) were recorded continually with the seasons whereas welfare measurements entailed body lesion scoring, posture distribution, activity patterns, frequency of panting and growth performance. It was found through multivariate analysis that an increased Temperature Humidity Index and higher ammonia concentrations were best predictors of behavioural disturbances, greater lesion prevalence, and less gain in weight. These monitoring outputs resulted in targeted management interventions and major decreases in the thermal load, accumulation of pollutants as well as water and energy use. The results indicate the realistic usefulness of data-supported evaluation models in improving the welfare of animals and environmental sustainability despite production systems that lack high-tech automation and digitalisation. It is the evidence based scalable method to enhance management decision making in the contemporary intensive livestock systems.