A Search Engine Concept to Improve Food Traceability and Transparency: Preliminary Results

Area of Science:

• Agrifood sector digitalization
• Smart data management in food supply chains
• Food traceability and transparency

Background:

• The agrifood sector is undergoing a digital revolution, but limited data management hinders technology adoption.
• Effective integration and utilization of smart data are crucial for intelligent food chain management systems.
• Challenges exist in managing data related to food quality, safety, traceability, transparency, and authenticity.

Purpose of the Study:

• To develop an EOSC-compatible (European Open Science Cloud) traceability search engine concept.
• To address data standardization, interoperability, knowledge extraction, and data reuse within the food supply chain.
• To integrate data on food quality, safety, traceability, transparency, and authenticity.

Main Methods:

• Development of a traceability search engine concept within the FNS-Cloud project.
• Examination of three specific food supply chains: olive oil, milk, and fishery products.
• Identification of key parameters and monitoring systems related to quality, safety, transparency, and authenticity at each supply chain step.

Main Results:

• A model was developed for collecting, integrating, organizing, and accessing data across food supply chains.
• Parameters influencing nutritional quality, food safety, transparency, and authenticity were identified for each supply chain step.
• The model facilitates graphical visualization and data searching/reusing for supply chain actors.

Conclusions:

• The developed traceability search engine concept enhances data management in the agrifood sector.
• Improved data integration and accessibility support better decision-making for food quality, safety, and transparency.
• The model offers significant benefits for all stakeholders involved in the food supply chain.