Modeling postharvest mycotoxins in foods: recent research
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 vari...
| Autores: | , , , |
|---|---|
| Formato: | artículo |
| Estado: | Versión aceptada para publicación |
| Fecha de publicación: | 2016 |
| País: | España |
| Recursos: | Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya) |
| Repositorio: | Recercat. Dipósit de la Recerca de Catalunya |
| OAI Identifier: | oai:recercat.cat:10459.1/60289 |
| Acesso em linha: | https://doi.org/10.1016/j.cofs.2016.09.005 http://hdl.handle.net/10459.1/60289 |
| Access Level: | acceso abierto |
| Palavra-chave: | Aliments--Microbiologia Aliments--Conservació Micotoxines |
| Resumo: | 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. |
|---|