H2020
Europeo
ExpectedOutcome:In line with the European Green Deal priorities and the farm to fork strategy for a fair, healthy and environmentally friendly food system, the successful proposal will support R&I in improving traceability and combating food fraud along the food supply chain. It will contribute to the transformation of food systems to deliver co-benefits for climate (mitigation and adaptation), environmental sustainability and circularity, dietary shifts, sustainable healthy nutrition and safe food, food poverty reduction and empowerment of communities, and thriving businesses.
Project results are expected to contribute to all of the following outcomes:
A robust knowledge base of the underlying reasons for/drivers of food fraud (e.g. economic and social) and the extent of food fraud.Innovative strategies and solutions (tools and devices) to prevent fraudulent practices by improving traceability and safeguarding authenticity, and fostering solutions for fraud prevention.Improved assistance to control bodies and authorities in fraud prevention.Improved transparency through digital solutions (such as IoT, artificial intelligence, blockchain and distri...
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ExpectedOutcome:In line with the European Green Deal priorities and the farm to fork strategy for a fair, healthy and environmentally friendly food system, the successful proposal will support R&I in improving traceability and combating food fraud along the food supply chain. It will contribute to the transformation of food systems to deliver co-benefits for climate (mitigation and adaptation), environmental sustainability and circularity, dietary shifts, sustainable healthy nutrition and safe food, food poverty reduction and empowerment of communities, and thriving businesses.
Project results are expected to contribute to all of the following outcomes:
A robust knowledge base of the underlying reasons for/drivers of food fraud (e.g. economic and social) and the extent of food fraud.Innovative strategies and solutions (tools and devices) to prevent fraudulent practices by improving traceability and safeguarding authenticity, and fostering solutions for fraud prevention.Improved assistance to control bodies and authorities in fraud prevention.Improved transparency through digital solutions (such as IoT, artificial intelligence, blockchain and distributed ledger technologies) that meet consumer demand for food transparency, with a focus on demonstrating authenticity of food as a way to reduce food fraud and boost consumer confidence in food origin and quality.Contribution to further development of policies for food authentication and traceability and for fighting food fraud/food crime.Support official control by providing guidance on detection and mitigation of fraudulent practices.
Scope:To contribute to the goals of the farm to fork strategy, the EU will scale up its fight against food fraud to create a level playing field for operators and strengthen the powers of control and enforcement authorities. The new EU Official Controls Regulation (Regulation (EU) 2017/625) includes key provisions in relation to food fraud. Recently, the issue of food fraud has been thrust into the spotlight and is of increasing concern to society and to the food industry. It can have very different impacts on consumers, ranging from direct health threats (e.g. consumption of toxic adulterants and contaminants) to violation of consumer rights (e.g. mislabelling). With the complexity of the global market and the addition of e-commerce, the safety risks of food fraud are likely to increase. Therefore, there is a constant need for sensitive and accurate authentication methods and innovative traceability methods to prevent food fraud and help the industry and official control authorities. Maintaining the integrity of European foods is vital to protect both consumers and the legitimate producers, industry and retail, and foster consumer confidence in the authenticity of all food products.
Successful proposals are expected to address both areas (area A and area B):
Area A:
Take stock and determine the current state-of-the-art, identify gaps, and suggest short-, medium- and long-term strategies for closing gaps in research addressing various aspects of fraud such as societal and economic drivers, fraud opportunities, mitigation and prevention measures.Quantify the economic dimension of the food fraud problem and understand the behaviour of food criminals perpetrating food fraud.Carry out translational research on fraud detection methods to provide the required evidence base for harmonisation and standardisation of methods and harmonisation of strategies for regulatory use.Develop and validate rapid food fraud detection tools and real-time in-situ/on-line analytical methods for testing authenticity and quality.Develop and implement new food fraud detection models (based on data, by applying artificial intelligence techniques) and tracing methods through the use of new and emerging technologies, such as blockchain and smart labelling tools.Build common platforms and tools for sharing information among stakeholders. Area B:
Support the development of an early warning system (EWS) for detection and possible further prevention of fraudulent practices and an efficient use of artificial intelligence, taking into consideration the data protection rules in place.Evaluate the utility of different food-authenticity-related databases existing in Member States and the EU institutions, and create a central database/data portal for further use of these data by authorised users to improve fraud detection and enforcement actions by the competent authorities.Develop tools that increase consumers’ confidence in the authenticity and quality of the food supply, in line with the relevant legal frameworks.Investigate food chain stakeholders’ attitudes towards adulterated food to understand better their motivation to commit fraud and trade-in inferior quality goods. The required multi-actor approach (see the eligibility conditions) must be implemented by involving a wide diversity of food system actors and conducting inter-disciplinary research. Proposals should bring together major stakeholders and scientific expertise to protect consumers and industry from food fraud.
Projects relevant to this topic should support policymaking and implementation relevant to fighting food fraud.
Proposals should explain how they will contribute to achieving the objectives of the farm to fork strategy and deliver co-benefits to the four Food 2030 priorities.
Proposals should involve a wide diversity of actors and implement an inter- and trans-disciplinary approach. They are encouraged to build on past and ongoing EU-funded research, and are strongly encouraged to cluster with upcoming projects under the HORIZON-CL6-2022-FARM2FORK-01-04 topic: Innovative solutions to prevent adulteration of food bearing quality labels: focus on organic food and geographical indications. They are also strongly encouraged to work with existing research infrastructure and collaborate with relevant initiatives, including specifically 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. The possible participation of the JRC in the project will ensure that the project deliverables are compatible with and/or improve existing databases and tools used at the European Commission and foster open access to project results via dissemination through the European Commission Knowledge Centre for Food Fraud and Quality, particularly to the competent authorities of the EU Member States.
Proposals should set out a clear plan on how they will work with other projects selected under this and any other relevant topic, by participating in joint activities and running common communication and dissemination activities. Applicants should plan the necessary budget to cover these activities.
In this topic the integration of the gender dimension (sex and gender analysis) in research and innovation content is not a mandatory requirement.
This topic should involve the effective contribution of SSH disciplines.
Specific Topic Conditions:Actions developing tools and models are expected to reach TRL 7 by the end of the project – see General Annex B.
Cross-cutting Priorities:Social sciences and humanitiesDigital AgendaArtificial IntelligenceSocial Innovation
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