WATSON - A holistic frameWork with Anticounterfeit and inTelligence-based technologieS that will assist food chain stakehOlders in rapidly identifying and preveNting the spread of fraudulent practices
Facts
Food Chemistry
Nutritional Sciences
Information Systems, Process and Knowledge Management
Agricultural Economics, Agricultural Policy, Agricultural Sociology
Agriculture, Forestry and Veterinary Medicine
Horizon Europe: Research and Innovation Action (RIA)
Description
WATSON provides a methodological framework combined with aset of tools and systems that can detect and prevent fraudulent activities throughout the whole food chain thus accelerating the deployment of transparency solutions in the EU food systems. The proposed framework will improve sustainability of food chains by increasing food safety and reducing food fraud through systemic innovations that a) increase transparency in food supply chains through improved track-and-trace mechanisms containing accurate, time-relevant and untampered information for the food product throughout its whole journey, b) equip authorities and policy makers with data, knowledge and insights in order to have the complete situational awareness of the food chain and c) raise the consumer awareness on food safety and value, leading to the adoption of healthier lifestyles and the development of sustainable food ecosystems. WATSON implementsan intelligence-based risk calculation approach to address the phenomenon of food fraud in a holistic way. The project includes three distinct pillars, namely, a) the identification of data gaps in the food chain, b) the provision of methods, processes and tools to detect and counter food fraud and c) the effective cross border collaboration of public authorities through accurate and trustworthy information sharing. WATSON will rely upon emerging technologies (AI, IoT, DLT, etc.) enabling transparency within supply chains through the development of a rigorous, traceability regime, and novel tools for rapid, non-invasive, on-the-spot analysis of food products. The results will be demonstrated in 6 use cases: a) prevention of counterfeit alcoholic beverages, b) preservation of the authenticity of PGI honey, c) on-site authenticity check and traceability of olive oil, d) the identification of possible manipulations at all stages of the meat chain, e) the improved traceability of high-value products in cereal and dairy chain, f) combat of salmon counterfeiting
Project manager
- Person
Prof. Dr. Dagmar Mith?fer
- Lebenswissenschaftliche Fakult?t
- Albrecht Daniel Thaer-Institut für Agrar- und Gartenbauwissenschaften
Partners
- Cooperation partnerNon-university research institutionSpain
ASINCAR Meat Industry Association
- Cooperation partnerGermany
Bayerisches Landesamt für Gesundheit und Lebensmittelsicherheit (LGL)
- Cooperation partnerNon-university research institutionGreece
Centre for Research & Technology - Hellas
- Cooperation partnerNon-university research institutionHungary
Hungarian Food Safety Office
- Cooperation partnerNon-university research institutionPortugal
INESC TEC- Institute for Systems and Computer Engineering, Technology and Science
- Cooperation partnerNon-university research institutionGermany
Max Rubner-Institut
- Cooperation partnerItaly
National Research Council (Italy)
- Cooperation partnerNon-university research institutionFrance
National Research Institute for Agriculture, Food and Environment
- Cooperation partnerUniversityGreece
National Technical University of Athens (NTUA) ETHNICON METSOVION POLYTECHNION
- Cooperation partnerNon-university research institutionSwitzerland
Research Institute of Organic Agriculture
- Cooperation partnerNon-university research institutionNorway
SINTEF Nord AS
- Cooperation partnerNon-university research institutionFinland
Technical Research Centre of Finland Ltd
- Cooperation partnerNorway
The Norwegian Directorate of Fisheries
- Cooperation partnerUniversityIreland
University College Dublin
- Cooperation partnerUniversityGermany
University of Bayreuth