TraceMyFish D2.3 Pilot Design and Piloting plan (v1.0)

The objective of WP2 “Tracking hazards and potential measures” is define and outline the piloting settings so as to track the potential hazards across the Bluebio value chain affecting food quality and safety along three crucial value chains in Europe, and more precisely: 1) the Atlantic salmon value chain, 2) the Atlantic whitefish value chain, and 3) the Mediterranean seabream/seabass value chain. In addition to tracking potential hazards, WP2 is targeting to map the critical parameters affecting the quality and also the safety, by employing non-invasive sensors (VideometerLab and VideometerLite), laboratory respectively portable multispectral imaging instruments; meaning the use of non-destructive measures to be included in the iFish Management System (iFMS) for hazard control, prevention and alerting mechanism to be developed within the project. In this report, we present the identified variables, as they stem out from the mapping of the needs of the related stakeholders in tandem with the potential/envisioned hazards inherent along the three value chains considered in the project; a work performed in Task 2.1 (please refer to D2.1 for more details). So, using the output from Task2.1 we are able to define and select the appropriate parameters, measures, and sensor strategies to be implemented into the first iFMS pilot. Since the selected, aforementioned, three value chains have their specific challenges, the three responsible research partners: NTNU, AUA, and UoI have focused their efforts on the value chain of Atlantic salmon, Gilthead seabream/European seabass, and Atlantic whitefish, respectively. This deliverable consists the first version of the pilots that will be performed during the project, mainly focusing to the feasibility of the proposed scheme of tracking and quality assessment along the food chain with the employed non-invasive instrument under real or close to real conditions. Additionally, the aim also is to populate a reference lake of appropriate datasets for model development. Models that will be able to predict, identify and report quality and tracking information along the food, fish “journey” from the initial production to the consumers’ hands.