Development and application of a predictive model of Aspergillus candidus growth as a tool to improve shelf life of bakery products

Abstract Molds are responsible for spoilage of bakery products during storage. A modeling approach to predict the effect of water activity ( a w ) and temperature on the appearance time of Aspergillus candidus was developed and validated on cakes. The gamma concept of Zwietering was adapted to model fungal growth, taking into account the impact of temperature and a w . We hypothesized that the same model could be used to calculate the time for mycelium to become visible ( t v ), by substituting the matrix parameter by t v . Cardinal values of A. candidus were determined on potato dextrose agar, and predicted t v were further validated by challenge-tests run on 51 pastries. Taking into account the a w dynamics recorded in pastries during reasonable conditions of storage, high correlation was shown between predicted and observed t v when the a w at equilibrium (after 14 days of storage) was used for modeling ( A f  = 1.072, B f  = 0.979). Validation studies on industrial cakes confirmed the experimental results and demonstrated the suitability of the model to predict t v in food as a function of a w and temperature.