Design and development of innovative tools for the detection of ochratoxigenic fungi in wine and table grapes - FungalPrognosis
The aim of the present proposal is to apply advanced mathematical modelling to predict the growth responses and mycotoxin production of ochratoxigenic fungi isolated from wine and table grapes in Greece in an attempt to provide an early detection system for fungal growth and toxin production. The study will improve and expand the newly developed field of predictive mycology incorporating ecology factors, strengthening thus the impact of the present findings and contributing to more effective control of fungal growth and toxin production in wine and table grapes. This work will employ classical mathematical modelling as well as new modelling approaches based on expert systems (e.g. artificial neural networks, support vector machines) for the prediction of fungal growth and toxin presence in grapes under variable physicochemical and environmental conditions. Moreover, a Real Time PCR procedure will be developed for the rapid and specific detection and quantification of ochratoxin A producing fungal strains. The present proposal includes also the built up of a free accessible internet page, which apart from information on mycotoxigenic fungi, will give access to data and models generated in this work. Communication with international experts on modelling will be encouraged for exchange of views on predictive mycology, and in the future the development of a tertiary model – platform dedicated to mycotoxigenic fungi could be the outcome of this collaboration and data collection.