The presence of natural food contaminants, such as mycotoxins, poses a persistent global health risk. Current occurrence databases are static and often lack the granularity or interactivity needed for in-depth analysis.
This project aims to develop a data-driven, open-access web platform that dynamically compiles and visualizes the global (co-)occurrence of mycotoxins in food. Leveraging automated literature mining and advanced natural language processing (NLP) techniques, the platform will continuously extract data from peer-reviewed publications, identifying several parameters and contamination statistics benchmarked against regulatory limits.
The project is aligned to UN's SGD:
