Modeling postharvest mycotoxins in foods: recent research

Abstract

Available information on the prediction of postharvest production of mycotoxins in recent years is reviewed. Predictive mycology has been focused mainly on fungal growth whereas studies on prediction of mycotoxins in foods are scarce. Modeling mycotoxin production is challenging due to the high variability in mycotoxigenic potential among species and isolates. Besides mycotoxin biosynthesis pathways and factors influencing them are still poorly understood. Baranyi and Luedeking-Piret models have been recently used as primary models for mycotoxin prediction, while for secondary modeling, polynomial approaches have been used. Furthermore, probability models can be a different alternative. In any case, media for data generation, intraspecies variability, and microbial interactions should not be disregarded before model application in food safety management systems.

The authors are grateful to the Agència de Gestió d’Ajuts Universitaris i de Recerca de la Generalitat de Catalunya (AGAUR, grant 2014FI_B 00045), and to the Spanish Ministry of Economy and Competitiveness (MINECO, Project AGL2014-55379-P) for funding this work.