Predictive mycology as a tool for controlling and preventing aflatoxins risk in postharvest.

Aflatoxins are potent carcinogens that pose a significant threat to human health. Incidence of these mycotoxins in foodstuffs is high, thus their control and prevention is mandatory in the food industry. The development of appropriate predictive models that allow us to predict fungal growth and mycotoxin production will be a valuable tool to monitor, predict and prevent the mycotoxin risk. To develop accurate predictive models it is important to account for the real conditions that we will encounter through the food chain. Such conditions include: suboptimal conditions for growth and mycotoxin production, even distribution of spores across the food matrix, presence of different strains of the same species or dynamic environmental conditions. Given the scope and complexity of the problem the present work provides the basis for scientifically proven models, which can be applied in the food industry in order to improve postharvest control of commodities.

Full-text available at: https://www.tdx.cat/handle/10803/418806#page=1