WATSON provides a methodological framework combined with a set 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 implements an 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.

ALLIANCE represents a paradigm shift in the Food Supply Chain Systems’ management for the combat against Food Fraud, distinguishing from the traditionally approaches that leverage monolithic digitalized logistic solutions and standalone FSC interoperability protocols. ALLIANCE aims to provide a holistic framework that safeguards data integrity and veracity, enhances traceability and transparency and reinforces interoperability in quality labelled supply chain of organic, PDO, PGI, and GI food, through innovative technology solutions and validated approaches (such as distributed ledger technologies supported by IoT sensing devices, providing extensible anchors to interoperability protocols and use of in-situ portable rapid testing devices to detect adulteration and verify food origin and authenticity) and fosters evidence-based decision making through AI and ML for preventative interventions and actionable planning. The proposed framework will improve social and economic sustainability of quality labelled food supply chains by ensuring quality & authenticity, increasing food safety, while also considering climatic and environmental impacts of food products. The technologies to be employed in this project will be described and demonstrated in detail to reach higher technology readiness levels (TRLs) and enable smooth and rapid adoption by all stakeholders.

DETECTIVE will develop and validate approaches to detect, identify, and quantify plant and animal products resulting from new genomic techniques (NGTs). NGT products are currently regulated as genetically modified organisms (GMOs) in the EU. This means that they are subject to authorisation procedures, which include event-specific methods for detection, identification, and quantification of the corresponding food and feed products. However, the analytical methods commonly used for transgenic GMOs are often not suitable for NGT products as these often do not contain genetic elements that allow unambiguous traceability. DETECTIVE will investigate the technical forefront for detection including the latest PCR-based and sequencing approaches for NGT products with known and unknown genetic alterations, and validate these in national enforcement laboratories. We will build a cluster of databases to enable Machine Learning-based screening. While technical detection may be limited, DETECTIVE will also look into non-technical approaches to traceability and authenticity to develop comprehensive solutions, including their respective economic and legal implications, to a wide range of NGT products. By taking a systemic and holistic approach, DETECTIVE will identify the boundary conditions that traceability approaches need to meet. The results will promote NGT research and innovation (R&I) that enable a resilient primary production (agriculture and animal husbandry) of highly nutritional food products and thereby contribute to a sustainable, healthy and inclusive food system in Europe that enables choice for both producers and consumers. DETECTIVE is a multi-disciplinary and multi-sectoral consortium and its links to relevant stakeholders through a Stakeholder Advisory Board will enable an improved understanding and awareness of the challenges related to traceability, authenticity and transparency of NGT-derived products.