Imagine having a weather forecast, but for food contamination and safety risks. This project uses AI to spot danger signs in food production before they become crises. It looks at the big picture, from climate change to economics, to keep our food supply steady and safe.
Food producers face unpredictable safety risks due to climate change and new environmental regulations. Current risk analysis is often reactive rather than predictive, leading to waste and safety failures.
AI-driven early warning systems and a digital knowledge sharing platform for monitoring food safety risks in maize, lentils, and poultry.
If you are a software provider dealing with unpredictable crop safety due to climate change — this project developed AI tools that predict emerging risks for maize and lentils. This allows you to offer proactive safety alerts to farmers.
If you are a poultry producer dealing with sudden microbiological hazards — this project developed targeted and non-targeted detection methods that identify risks early. This reduces the chance of costly product recalls.
If you are a platform provider dealing with a lack of real-time safety data — this project developed an electronic data and knowledge sharing platform. This enables full digitalization of safety systems for better transparency.
Based on available project data, specific pricing or implementation costs are not provided as this is a research project.
The project tests innovations in Living Labs with producers and authorities, and focuses on three major supply chains (maize, lentils, poultry), suggesting a path toward industrial application.
Based on available project data, the specific licensing terms are not mentioned, though the project aims to integrate outputs into legal frameworks.
Yes, the project is specifically designed to meet challenges arising from Green Deal policy-driven transitions and climate-driven changes.
Integration is achieved through an electronic data and knowledge sharing platform and a multi-actor approach involving producers and authorities.
The consortium is research-heavy with 15 academic and research entities (7 universities, 8 research institutes) and a modest industrial presence of 2 companies and 3 SMEs. This 11% industry ratio indicates the project is primarily focused on developing new methodologies and AI tools rather than immediate commercial rollout, though the inclusion of 11 countries ensures broad European validation.
Contact Stichting Wageningen Research in the Netherlands
Contact us to explore licensing opportunities for the AI risk-prediction tools.
