Aims: Mathematical models were employed to predict the growth kinetic parameters of Fusarium graminearum and the accumulation of deoxynivalenol (DON) during wheat storage as a function of different moisture contents (MCs) and temperatures.
Methods and results: The colony counting method was used to quantify F. graminearum growth under different environmental conditions, and kinetic and probability models were developed to describe the effect of different MCs and temperatures on fungal growth and DON production during wheat storage. Among the employed secondary models (Arrhenius-Davey, Gibson and Cardinal), the general polynomial best predicted the fungal growth rate under varying temperature and MC during wheat storage. According to the logistic model, DON contamination was correctly predicted in 96.5% of cases.
Conclusions: The maximum growth rate of fungi was 0.4889 ± 0.092 Log CFU g-1 day-1 at 25°C and 30% moisture according to the polynomial model. At below 17°C and ≤15% moisture, no fungal growth was observed. The probability model of toxin production showed no toxin production at less than 15% moisture (aw ≤0.76) and below 15°C.
Significance and impact of the study: This is the first application of a probability model of DON production during wheat storage, providing a reference for preventing fungal growth and mycotoxin accumulation by F. graminearum during wheat storage and guaranteeing food product safety.
Keywords: Fusarium graminearum; deoxynivalenol; food safety; predictive modelling; wheat storage.
© 2022 Society for Applied Microbiology.