In recent years, very many incidences of contamination with aflatoxin B1 (AFB1) in pistachio nuts have been reported as a major global problem for the crop. In Europe, legislation is in force and 12 μg/kg of AFB1 is the maximum limit set for pistachios to be subjected to physical treatment before human consumption. The goal of the current study was to develop a mechanistic, weather-driven model to predict Aspergillus flavus growth and the AFB1 contamination of pistachios on a daily basis from nut setting until harvest. The planned steps were to: (i) build a phenology model to predict the pistachio growth stages, (ii) develop a prototype model named AFLA-pistachio (model transfer from AFLA-maize), (iii) collect the meteorological and AFB1 contamination data from pistachio orchards, (iv) run the model and elaborate a probability function to estimate the likelihood of overcoming the legal limit, and (v) manage a preliminary validation. The internal validation of AFLA-pistachio indicated that 75% of the predictions were correct. In the external validation with an independent three-year dataset, 95.6% of the samples were correctly predicted. According to the results, AFLA-pistachio seems to be a reliable tool to follow the dynamic of AFB1 contamination risk throughout the pistachio growing season.
Keywords: Aspergillus flavus; aflatoxin B1; model transfer; preharvest; probability; weather.