Imagine if every single step of a food's journey—from the farm to your plate—was recorded in a shared digital diary that everyone trusted. This project builds the tools to connect those scattered notes using smart AI, making it easy to spot waste or fraud. It's like creating a universal translator for food data so companies and shoppers can make healthier, greener choices.
Food supply chains suffer from fragmented data and a lack of trust, making it hard to prove sustainability or reduce waste. This disconnect leads to inefficient operations and a gap between sustainable production and consumer choices.
A trusted AI-enabled data integration system and a reusable blueprint. It includes four specific tools for DNA-traceability, hospital food optimization, climate-neutral chain insights, and consumer communication.
If you are a supply chain auditor dealing with fraud and lack of transparency — this project developed a DNA-based, AI-driven system that improves food sustainability and traceability. This allows for precise verification of origin and quality.
If you are a facility manager dealing with high food waste and poor nutrition in patient meals — this project developed data-driven optimization for food services. This helps in providing healthier diets while reducing waste.
If you are a brand manager dealing with low consumer awareness of your green credentials — this project developed AI-enabled communication tools. These tools enhance consumer awareness of sustainable choices at the point of purchase.
Based on available project data, specific pricing or licensing costs for the resulting tools are not provided.
The project tests its solutions through four real-world use cases, including food services in hospitals and DNA-based traceability, indicating a design intended for industrial application.
Based on available project data, the specific IP and licensing agreements are not detailed, though the project aims to deliver a reusable blueprint.
The project integrates legal and ethical analysis to ensure data sharing respects privacy, ethics, and regulatory requirements.
The project focuses on interoperability and the creation of data spaces to overcome technical barriers that currently keep food data fragmented.
The consortium is strongly geared toward commercial application, with a 47% industry ratio comprising 7 industrial partners, including 5 SMEs. This balance between 5 research/university entities and 7 industry players suggests the project is focused on practical market adoption rather than pure academic research.
Contact the Institute for Agricultural and Fisheries Research (BE)
Contact SciTransfer to connect with the FoodDataQuest consortium for pilot integration.
