Imagine trying to find a single specific typo in a giant library of books; that is what finding gene-edited plants is like. This project creates a high-tech 'digital fingerprint' and a smart search tool to spot these changes instantly. It also uses a digital ledger, like a secure receipt, to track these ingredients from the farm to your plate.
Current methods for detecting gene-edited (NGT) plants are often too specific or too slow, making it hard for companies to ensure regulatory compliance and transparency in the food supply chain.
A suite of DNA detection tools including AI-based genetic fingerprints, enhanced PCR methods, and a blockchain-backed Decision Support System for traceability.
If you are a testing lab dealing with the difficulty of identifying specific gene-edited crops — this project developed AI-driven genetic fingerprints and enhanced PCR methods that allow for unambiguous identification of NGT lines.
If you are a distributor dealing with strict EU labeling laws for GMOs and NGTs — this project developed blockchain and data space solutions that enable transparent and traceable detection along the food chain.
If you are a seed company dealing with the need to prove the purity and identity of your NGT rice or other crops — this project developed whole-genome sequencing and laser capture microdissection methods to characterize NGT products.
Based on available project data, specific pricing or implementation costs are not provided, though the project received an EU contribution of EUR 4,999,635 for development.
The project aims to reach TRL 4-5 through validation including transferability and full trials, suggesting it is moving toward industrial applicability but is not yet fully scaled.
Based on available project data, there is no specific mention of licensing terms or patent filings, only that the methodology for rice lines has been submitted in a scientific manuscript.
DARWIN provides technical validation procedures that contribute to policy and governance recommendations for more transparent food and GMO legislation.
The project period runs from 2024-01-01 to 2027-06-30, indicating that full validation and case studies will be completed by mid-2027.
The consortium is heavily weighted toward research and academic expertise, with 5 research organizations and 3 universities. However, it includes 16 partners across 11 countries, providing a broad geographical reach. The industrial presence is relatively low at 12% (2 industry partners), including 2 SMEs, suggesting the project is currently more focused on technical validation than immediate commercial mass-production.
Contact NORCE RESEARCH AS in Norway for technical transfer inquiries.
Contact us to explore licensing opportunities for NGT detection AI models.
