AFLA-MAIZE, a mechanistic model to predict the risk of aflatoxin production in maize.

Maize is one of the principal crops grown destined to food and feed worldwide, after wheat and rice, with more than 600 million tons produced annually (FAO, 2003). Unfortunately, maize is susceptible to mycotoxin producing fungi as Aspergillus flavus, which can contaminate the ripening kernels with aflatoxins. Aflatoxin B1 is reported as the most toxic natural compound, causing chronic and acute toxicity on human and animal health. EU legal limits in raw maize are fixed at 5 µg/kg for products destined to humans and dairy animals and 20 µg/kg for other animal species (Commission Regulation 1181/2006, 165/2010 and Directive 100/2003). No mechanistic models for A. flavus–maize pathosystem are available in literature. In this work, the relational diagram of A. flavus infection cycle has been developed following the principles of “system analysis”; state variables, rates and driving variables were determined and linked in a coherent framework. Quantitative data for each steps of the cycle were collected from literature and mathematical equations were elaborated to connect driving variables to rates; an algorithm was also developed to finalize the model. The model predicts fungal development and toxin production (output) based on weather conditions (air temperature, relative humidity and rain). After a proper validation, the model may support stakeholders in order to: a) describe the dynamic of the contamination risk during the maize-growing season and at harvest, to rationalise harvest and post-harvest logistic; b) draw different scenarios based on real and simulated (climate change) meteorological data.