Rapid methods solve this problem, but they need to be proven to work as well as the standard microbiological methods that they replace. Proving these rapid methods work just as well, requires them to be tested in multiple food matrices. This is time-consuming, expensive and slows down adoption. AI can solve this problem. An algorithm comparing historical standard microbiological tests against the rapid method tests will be created and this will allow food companies to radically reduce the number of verifying tests they will need to do, to ensure the rapid method works in their food matrix of interest. Salmonella spp. will be targeted because it is poses a severe threat to multiple food products. In the following phase, we will compare the recommended test plan from the AI to a real-life ISO verification for 2 new products, done in the lab first and then in a food factory.
VITAL: Validation of Innovative Tools to Assess and to improve microbioLogical safety in the food chain
Conventional microbiological testing takes time to get results. This impacts the supply chain, causing delays to get to market whilst results come back on finished but not shipped goods.
Developing a sustainable, economically viable feed for bivalve shellfish
The starting point is the clear link between the dietary pattern of consumers and the environmental footprint of these patterns.
Making paper packaging more recyclable and versatile
Deadline extended! Ideation Awards of EIT xKIC New European Bauhaus looking for Climathon and hackathon participants
EU teams participating in the 2021 EIT Climate-KIC Climathon and hackathons of EIT Digital, EIT Food and EIT Urban Mobility can win prizes....
Four winners have been announced for the EIT Food Impact awards