GreenTrace project: Integration of Eco-Sustainable Analytical Methods, Machine Learning, and Data Management for the Authenticity and Quality of Food

Ensuring the quality and authenticity of food through advanced analytical methodologies is crucial for consumer trust, safety, and the fight against fraud. At the same time, scientific research must minimize environmental impact while maintaining high accuracy and reliability in authentication methods. The GreenTrace project aims to develop authenticity models through innovative and eco-friendly analytical techniques combined with machine learning algorithms and robust data management systems. Incorporating the principles of green chemistry, the developed models will be based on data from spectroscopic analyses (UV-VIS, Fluorescence, RAMAN) and volatilomic analyses (GC-IMS), which do not require the use of solvents or pre-treatment of samples. The achievement of these models will be ensured through machine learning methods, known for their ability to handle large and diverse datasets and uncover hidden patterns by identifying subtle anomalies indicative of fraud or quality deviations. The performances will be tested on three case studies: Balsamic Vinegar of Modena PDO and PGI, two valuable products of significant economic and cultural importance in the Modena district, and Italian honey, one of the most frequently defrauded products worldwide. For the first time, all data from spectroscopic and volatilomic analyses will be archived and integrated into a single database, managed by a robust data management system serving as the backbone of the project. This will lay the groundwork for creating a green digital passport for the analyzed products, representing the first step toward establishing a system that can be extended in the future to track product evolution over time and strengthen the authenticity models developed in this research project. These results will also be incorporated into QR codes placed on product labels, raising consumer awareness of the scientific investigations conducted and fostering trust in the global food market. The project is supported by the Consortia for the Protection of Balsamic Vinegar PGI and PDO and the Central Inspectorate for the Protection of Quality and the Repression of Fraud in Agro-Food Products (ICQRF), one of Europe's leading agri-food control bodies. Additionally, the project has garnered significant interest from several vinegar producers in the area. To ensure reliable results, representative sampling will be carried out in cooperation with the Consortia and ICQRF, considering factors such as aging for vinegars and geographical and floral origins for honeys. Continuous model validation will involve splitting samples into calibration and validation sets, including samples from different project phases. To facilitate the adoption and integration of the GreenTrace methodology, another aim is to establish clear and standardized guidelines: one for vinegars and one for honeys