Modeling postharvest mycotoxins in foods: recent research

Aldars García, Laila; Ramos Girona, Antonio J.; Sanchís Almenar, Vicente; Marín Sillué, Sònia

doi:https://doi.org/10.1016/j.cofs.2016.09.005

View/Open

Postprint (220.4Kb)

Issue date

2016

Author

Aldars García, Laila

Ramos Girona, Antonio J.

Sanchís Almenar, Vicente

Marín Sillué, Sònia

Suggested citation

Aldars García, Laila; Ramos Girona, Antonio J.; Sanchís Almenar, Vicente; Marín Sillué, Sònia; . (2016) . Modeling postharvest mycotoxins in foods: recent research. Current Opinion in Food Science, 2016, vol. 11, p. 46-50. https://doi.org/10.1016/j.cofs.2016.09.005.

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.

URI

http://hdl.handle.net/10459.1/60289

DOI

https://doi.org/10.1016/j.cofs.2016.09.005

Is part of

Current Opinion in Food Science, 2016, vol. 11, p. 46-50

Collections

The following license files are associated with this item:

Creative Commons

Except where otherwise noted, this item's license is described as cc-by-nc-nd, (c) Elsevier, 2016