In line with the farm to fork strategy the successful proposals will support increased authenticity, traceability and transparency in food systems. One of the strategy´s main priorities is to tackle food fraud along the food supply chain. The successful proposals should therefore facilitate progress to preventing food fraud by translating research and innovation knowledge into practical applications.
Project results are expected to contribute to all of the following expected outcomes:
- Widespread use of existing new knowledge and innovative solutions by end-users/practitioners (official control authorities, food businesses, etc.) on the ground ensuring that food fraud is tackled;
- Improved flow of knowledge and innovative solutions with end-users through more dynamic interactions and new collaboration methodologies to prevent food fraud in the food supply chain;
- Better incorporation of the needs of end-users into the activities of research and innovation communities, which would generate a better targeted and shared food fraud research agenda for innovation-driven research.
- Improved skills and long-term availability of training and education material and on-line communities for end-users on how to tackle food fraud.
Proposals are expected to contribute to the creation of a thematic network in the area of food fraud, including all of the following activities:
- Development of a community of practice to foster knowledge exchange between end-users and research and innovation ecosystems who will work together mapping existing food fraud practices. Traditional and local food products should be taken into consideration in this community of practice;
- Proposals must implement the 'multi-actor approach' and ensure adequate involvement of academia and research-technology organizations with end-users (official control authorities, food businesses, industrial clusters, etc.) and other relevant actors of the food chain;
- Compilation of a comprehensive description of the state of new knowledge, practices, procedures, systems and technologies tackling food fraud (including not only technologies for detection but also preventative approaches). Proposals should build on existing and new available knowledge and trends, data and models (including big data tools and/or artificial intelligence applied to food fraud). Proposals should focus on the cost/benefit aspects of the practices and innovations collected and build on existing and new available knowledge, data and models enabling the practical implementation of solutions;
- Creation of tailor-made communication materials summarizing, sharing and presenting, in a language easily understandable for end-users, existing best practices and innovations that are close to implementation into practice, but not sufficiently known by end-users;
- Identification and mapping of possible relations and synergies with other networks, projects, initiatives and policy and funding instruments at regional, national and European level, that could help disseminate and exploit knowledge and results, showing the added value of these inter-connections. Dissemination via public events, publication of case studies, dissemination papers and reports, and the creation of an on-line collaborative space that remain active in the long-term including the availability of materials for training and education;
- Proposals should include a dedicated task, appropriate resources and a plan on how they will collaborate with other projects funded under the topics HORIZON-CL6-2021-FARM2FORK-01-07, HORIZON-CL6-2021-FARM2FORK-01-17, HORIZON-CL6-2022-FARM2FORK-01-11 and HORIZON-CL6-2022-FARM2FORK-01-04.
- Proposals are encouraged to cooperate with actors such as the European Commission’s Joint Research Centre (JRC) Knowledge Centre for Food Fraud and Quality, which provides expertise in food science, authenticity and quality of food supplied in the EU. Proposals could also foresee the involvement of the European Network of GMO Laboratories (ENGL).
- Cross-articulation with the other data spaces, and notably with the European Open Science Cloud (EOSC) should be foreseen, exploiting synergies and complementarities of the different approaches. Efforts should be made to ensure that the data produced in the context of this topic is FAIR (Findable, Accessible, Interoperable and Re-usable)
- Proposals should run for minimum 3 years.