Scenarios for sustainable, healthy consumer protection of the future by exchanging and quantitatively analysing quality and safety information on food along the supply chain all the way to the consumer thanks to innovative measurement methods and continuously updating AI.
Sponsored by: Federal Ministry of Food and Agriculture (BMEL)
Project Manager: Federal Office for Agriculture and Food (BLE)
Duration: 10/2021 – 10/2024
Consortium: benelog, BfR (Bundesinstitut für Risikobewertung), Bayrisches Landesamt für Gesundheit und Lebensmittelsicherheit, Fraunhofer IVV, Max-Rubner-Institut (Bundesforschungsinstitut für Ernährung und Lebensmittel), Technische Hochschule Deggendorf, tsenso GmbH, Universtiät Bayreuth
The FutureLab2030 (ZL2030) aims to develop the basis for a continuous forecast of food hygiene, quality and safety using artificial intelligence (AI) methods, innovative supply chain monitoring technologies and non-targeted analytical methods. This will both make an important contribution to increasing consumer protection and enable food companies to take their HACCP concepts for ensuring hygienic food production to a new level. A higher level of information about the current shelf life of products leads to greater efficiency in the supply chain and at the same time to a reduction in food waste.
The central element of ZL2030 is the digital twin. A digital twin of a food product is a digital resource that describes the key properties of the product, including the microbiota.