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.
Iodine (I) deficiency is the greatest single cause of preventable brain damage, resulting in impaired intellectual ability and reduced school/work performance globally.
In the fight against chronic diet-related diseases it is the EU food and health system organization’s aim to improve consumers’ food literacy. Food education in a form of professional personalised advice is more trusted and accepted by consumers.
Farmers increasingly generate 'big' data about their fields.
Startup Tilkal awarded with “EIT Food prize for Best Pitch” at ToastersLAB’s 2020 Demo Day.
More than ever, there is a growing awareness of the impact of food poverty, unequal access to nutritious food, and the vital role that delivery, factory and retail workers play....