Integrating physiological indicators and Precision Livestock Farming to support European animal welfare frameworks: a systematic review

Animal welfare assessment in livestock production is increasingly supported by Precision Livestock Farming (PLF) technologies integrated with physiological monitoring. This Scopus-based systematic literature review, conducted according to PRISMA guidelines and synthesised using a narrative approach, examined physiological parameters relevant to animal welfare assessment and their integration into PLF across major livestock species, including cattle, pigs, poultry, sheep, and goats. Following the screening and eligibility assessment, 144 studies were selected from an initial dataset of 1386 records. Body surface temperature, heart rate, and respiratory rate were the most frequently investigated physiological parameters, while computer vision, wearable sensors, environmental sensing, and machine learning were the predominant technologies enabling continuous, non-invasive monitoring. The reviewed studies primarily addressed animal-based welfare indicators within European welfare assessment frameworks, whereas resource- and management-based indicators were comparatively underrepresented. No studies explicitly investigated antimicrobial use or the human-animal relationship using PLF technologies, highlighting important research gaps. Overall, the evidence indicates that physiological parameters provide complementary biological information that enhances the interpretation of animal-based welfare indicators, particularly when integrated with behavioural and environmental monitoring. Future research should prioritise multimodal approaches integrating physiological, behavioural, environmental, and management-related data to support more comprehensive and operationally feasible animal welfare assessment.