Wageningen University & Research (WUR) is searching for additional partners to participate in a multi-partner consortium project aiming to develop a digital tool to assist food producers in identification of relevant safety concerns resulting from the use of new food ingredients in the design phase including side streams from the food production chain.
Hazard identification of (circular) food systems
In Europe, the General Food Law Regulation serves to ensure that all food placed on the European market is safe. For food manufacturers, this implies that they should have a food safety plan to safeguard the consumer health. Food production chains are subject to continuous change driven by, among others, consumer demands, transitions towards more plant-based and other new protein sources and reintroduction of side streams in circular food production systems. This requires a continuous (re)-assessment of the safety a food production chain.
The project aims to provide a platform for automated support for hazard identification in a structured, transparent, and reproducible way at an early stage of product development. It will provide the user information on the relevant microbiological and chemical hazards to consider in their HACCP. The tool will integrate Artificial Intelligence (AI) algorithms to combine product characteristics (e.g., physical, chemical) and other factors to prioritize food safety issues for new food products from side streams at R&D and design phases.
To predict food safety in R&D
The aim of the project is to develop a Food Safety by Design Tool combining knowledge on chemical and microbiological hazards and (future) influencing factors that will help the experts in prioritizing the compounds for future research.
Wageningen University & Research (WUR) has performed extensive literature-based reviews on the microbiological and chemical hazards of a large number of food chains, of animal and plant-origin. This information is collected in hazard/ingredient databases and will be linked to knowledge rules for decision making based on steps in the chain that increase or reduce the hazard. The existing database will be extended to cover a wider range of product ingredients, including ingredients derived from circular food systems and processing and storage conditions. Furthermore, AI algorithms will be developed facilitating an automatic data collection and processing system of the parameters that are relevant for characterization of the occurrence and severity of a compound.
The project brings together WUR expertise on chemical and microbiological hazards and the integration on knowledge rules with a data driven approach using AI to develop a unique tool implemented in WUR cloud infrastructure.
We would like to invite proactive food industries that are willing to invest in safeguarding new products and processes including in valorization of side streams to participate in this consortium. We would be pleased to further discuss the opportunities within PPP Food Safety by Design with you.
The consortium is almost complete. We have four interesting companies already! As we will have a focus on ready meals of vegetables, potatoes and a protein source (vegetarian or with meat) we would like to specially attract the food industry with links in the prepared food products.
Unfortunately, we are not able to reply to applications from research institutes or enquiries from students related to this project.