- Challenges
Present datasets available have great but unexploited potential for monitoring animal health and welfare, identifying risks, and establishing good production practices. However, these data tend to remain at the disposal of selected value chain partners only. While sensor technologies can detect welfare and health issues, they operate in isolation, lacking integration with broader datasets and failing to enhance transparency.
- Solution
- Outcomes
The culmination of this endeavour is a data-centric Welfare Quality (WQ) framework tailored for pig and broiler production systems. This framework showcases the transformative potential of integrating and standardizing welfare and health data, including inputs from sensors, and market-oriented solutions. Its implementation foster enables industry-wide advancements in quality assurance, branding, and on-parm practices and benchmarking, empowers regulatory bodies to monitor welfare and health trends, pinpoint potential hazards. Moreover, it is a beacon for enhanced transparency throughout the production process.
- Replicability
The methodology pioneered here, emphasizing the integration of diverse data sources, including sensor data, can be replicated across species and geographical regions.