The overall objective of this work package is to keep track of the mycotoxicological risks in maize fields during the growing season in an accurate, on-line way at farm level.
This information will be communicated with the ICT dashboard (developed in WP7) that sends an advice to the farmer for intervention, to the collector for curation or re-routing of the commodity.
Specific objectives are:
development ofa user-friendly integrated prediction model for AFLA and FUM in maize and ofa prototype model for DON and ZEA contamination of maize (Task 2.1);
implementation of detection tools (kits) for toxigenic fungi for on-site detection and monitoring of novel genotypes of toxigenic fungi (Task 2.2);
translation of existing monitoring technologies (environmental sensors and drone systems) into on-site application tools for real-time monitoring at farm/field level (Task 2.3);
development of recommendations for farmers (Task 2.4);
development of risk maps for mycotoxins (Task 2.5).
(h-index 29; > 3500 citations) has a long standing experience on bacterial and fungal molecular biology. His research team focuses on genomics in fungi including functional genomics and bioinformatics. As such he is a member of the Fusarium International Genomics Initiative, who jointly published on the genome of F. graminearum. His research team developed multiplex PCR and real-time TaqMan quantitative detection for toxigenic fungi.