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OTA-Grapes: A Mechanistic Model to Predict Ochratoxin A Risk in Grapes, a Step beyond the Systems Approach

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Ochratoxin A (OTA) is a fungal metabolite dangerous for human and animal health due to its nephrotoxic, immunotoxic, mutagenic, teratogenic and carcinogenic effects, classified by the International Agency for Research on Cancer in group 2B, possible human carcinogen. This toxin has been stated as a wine contaminant since 1996. The aim of this study was to develop a conceptual model for the dynamic simulation of the A. carbonarius life cycle in grapes along the growing season, including OTA production in berries. Functions describing the role of weather parameters in each step of the infection cycle were developed and organized in a prototype model called OTA-grapes. Modelling the influence of temperature on OTA production, it emerged that fungal strains can be shared in two different clusters, based on the dynamic of OTA production and according to the optimal temperature. Therefore, two functions were developed, and based on statistical data analysis, it was assumed that the two types of strains contribute equally to the population. Model validation was not possible because of poor OTA contamination data, but relevant differences in OTA-I, the output index of the model, were noticed between low and high risk areas. To our knowledge, this is the first attempt to assess/model A. carbonarius in order to predict the risk of OTA contamination in grapes.
Title: OTA-Grapes: A Mechanistic Model to Predict Ochratoxin A Risk in Grapes, a Step beyond the Systems Approach
Description:
Ochratoxin A (OTA) is a fungal metabolite dangerous for human and animal health due to its nephrotoxic, immunotoxic, mutagenic, teratogenic and carcinogenic effects, classified by the International Agency for Research on Cancer in group 2B, possible human carcinogen.
This toxin has been stated as a wine contaminant since 1996.
The aim of this study was to develop a conceptual model for the dynamic simulation of the A.
carbonarius life cycle in grapes along the growing season, including OTA production in berries.
Functions describing the role of weather parameters in each step of the infection cycle were developed and organized in a prototype model called OTA-grapes.
Modelling the influence of temperature on OTA production, it emerged that fungal strains can be shared in two different clusters, based on the dynamic of OTA production and according to the optimal temperature.
Therefore, two functions were developed, and based on statistical data analysis, it was assumed that the two types of strains contribute equally to the population.
Model validation was not possible because of poor OTA contamination data, but relevant differences in OTA-I, the output index of the model, were noticed between low and high risk areas.
To our knowledge, this is the first attempt to assess/model A.
carbonarius in order to predict the risk of OTA contamination in grapes.

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