01/01/2021 – 30/06/2024
Grant agreement ID: 101007448
Cyprus Research and innovation center LTD (CyRIC), Cyprus
Consiglio Nazionale delle Ricerche (CNR), Italy
Technoalimenti SCPA (TCA), Italy
Easy Global Market SAS (EGM), France
Bialoom LTD (bialoom), Cyprus
Centre national de la recherche scientifique (CNRS), France
Sous les fraises (SLF), France
Aristotelio Panepistimio Thessalonikis (AUTH), Greece
Pour une agriculture du vivant (PADV), France
AMO GmbH (AMO), Germany
Pilze-Nagy LTD (PILZE), Hungary
ISS BioSense SRL, Italy
Lumensia Sensors SRL, Spain
Ultra-compact, low-cost plasmo-photonic bimoal multiplexing sensor platforms as part of a holistic solution for food quality monitoring
As consumer demand for fresh fruits and vegetables (F&V) continues to increase, so does the risk of microbiological and chemical contamination. Currently, inspections for F&V are carried out at the production site or the food processing facility, based also on regulatory requirements. In most cases these are inspections of random batches using laboratory techniques, which may require up to two or more days before getting results. The time and cost per analysis leads to reduced checks and thus elevated risks, even in countries with very efficient control mechanisms. Furthermore, such analysis cannot take place in all parts of the value chain (due to time requirements, but also due to associated cost), including supermarkets or restaurants, which are critical points since this is where the consumer will get the products from.
GRACED considers the aforementioned need and the limitations of current techniques and proposes a novel solution for contaminants detection at all the stages of the F&V industry value chains. The heart of the proposed solution is a novel plasmo-photonic bimodal interferometric sensor, combined with low cost on-chip light generation, capable of simultaneously and quickly detecting different analytes of interest. The sensor will be part of holistic, modular solution that exploits unique engineering designs, IoT concepts and advanced data analytics, for the early detection of contaminations in the F&V value chains.
The approach will be validated in different production & distribution systems: a) a conventional farming system in open-air farms and the follow-up steps of food processing for preparing cooked meals and frozen vegetable packages, b) a novel, urban farming ecosystem, producing F&V locally and using them in in-situ restaurants, c) a short value chain based on agroecology and direct distribution from farmers to consumers & restaurants, d) a semi-automatic farm producing mushrooms and distributing them to supermarkets & wholesalers.