Food Chain Information (FCI) is a critical component of risk-based meat safety assurance systems. However, its potential is not fully exploited, and it is mostly underused. We evaluated the potential of precision livestock farming (PLF) technologies, including computer vision systems (CVS), sensors, and microphones, to enhance the value of FCI by enabling automated monitoring of broiler health, welfare, and food safety indicators. A scoping review was conducted, identifying 47 relevant studies and 28 studies with potential future applicability. Technologies were categorized by sense: vision, sound, smell, and feeling; and analyzed for their potential to detect key indicators such as disease signs, mortality, gait abnormalities, thermal stress, and harmful gas concentrations. Vision and sound-based systems dominated the current applications, with several demonstrating high accuracy in monitoring syndromic signs of diseases, as well as detecting dead birds. However, precise pathogen identification still requires laboratory follow-up. Environmental monitoring showed potential in detecting welfare-related factors such as high ammonia levels and heat stress. The implementation of these technologies into broiler production and data sharing could enable real-time, continuous monitoring of health and welfare status. However, the use of new technologies to automatically detect food safety hazards still raises doubts and requires further research. Currently the data generated could be used to inform FCI, which would allow for risk-categorization of flocks and batches and informed decision-making in the abattoirs, with beneficial effects of improving health and welfare of broilers.
Majewski et al. (Sun,) studied this question.