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Intraspecies variability in fungal growth and mycotoxin production has important implications for food safety. Using the Bioscreen C we have examined spectrophotometrically intraspecies variability of A. flavus using 10 isolates under different environments, including temperature shifts, in terms of growth and aflatoxin B 1 (AFB 1 ) production. Five high and five low AFB 1 producers were examined. The study was conducted at 5 isothermal conditions (from 15 to 37 °C) and 4 dynamic scenarios (between 15 and 30 °C). The experiments were carried out in a semisolid YES medium at 0.92 a w and two inoculum levels, 10 2 and 10 3  spores/mL. The Time to Detection (TTD) of growth initiation was determined and modelled as a function of temperature through a polynomial equation and the model was used to predict TTD under temperature upshifts conditions using a novel approach. The results obtained in this study have shown that a model can be developed to describe the effect of temperature upshifts on the TTD for all the studied isolates and inoculum levels. Isolate variability increased as the growth conditions became more stressful and with a lower inoculum level. Inoculum level affected the intraspecies variability but not the repeatability of the experiments. In dynamic conditions, isolate responses depended both on the temperature shift and, predominantly, the final temperature level. AFB 1 production was highly variable among the isolates and greatly depended on temperature (optimum temperature at 30-35 °C) and inoculum levels, with often higher production with lower inoculum. This suggests that, from an ecological point of view, the potential isolate variability and interaction with dynamic conditions should be taken into account in developing strategies to control growth and predicting mycotoxin risks by mycotoxigenic fungi., (Copyright © 2018 Elsevier B.V. All rights reserved.)

The objective of the present study was to assess the differences in modeled growth/AFB1 production probability and kinetic growth parameters for Aspergillus flavus inoculated as single spores or in a concentrated inoculation point (~500 spores). The experiment was carried out at 25°C and at two water activities (0.85 and 0.87) on pistachio extract agar (3%). Binary data obtained from growth and AFB1 studies were modeled using linear logistic regression analysis. The radial growth curve for each colony was fitted to a linear model for the estimation of the lag phase for growth and the mycelial growth rate. In general, radial growth rate and lag phase for growth were not normally distributed and both of them were affected by the inoculation type, with the lag phase for growth being more affected. Changing from the multiple spore to the single spore inoculation led to a delay of approximately 3-5days on the lag phase and higher growth rates for the multiple spore experiment were found. The same trend was observed on the probability models, with lower predicted probabilities when colonies came up from single spores, for both growth and AFB1 production probabilities. Comparing both types of models, it was concluded that a clear overestimation of the lag phase for growth occurred using the linear model, but only in the multiple spore experiment. Multiple spore inoculum gave very similar estimated time to reach some set probabilities (t10, t50 and t100) for growth or AFB1 production due to the abruptness of the logistic curve developed. The observed differences suggest that inoculum concentration greatly affects the outcome of the predictive models, the estimated times to growth/AFB1 production being much earlier for the concentrated inoculum than for a single spore colony (up to 9days). Thus the number of spores used to generate data in predictive mycology experiments should be carefully controlled in order to predict as accurately as possible the fungal behavior in a foodstuff., (Copyright © 2016 Elsevier B.V. All rights reserved.)