Abstract
In this study, the antagonistic effect of Cryptococcus albidus SAS157 against the growth of Penicillium expansum on Fuji apple fruit was modeled using Artificial Neural Networks (ANN) under various storage conditions. The apples (punctured holes on the surface) were inoculated respectively with C. albidus (6, 9, or 11 log CFU/ml) and P. expansum (6 log CFU/ml) and stored at 4, 10, 15, and 25 °C with 85% or 95% RH for 14 days. The growth of P. expansum significantly decreased as the temperature, humidity, or yeast inoculum level increased (p < 0.05). The diameter of spoilage was decreased by 91.39% at 95% RH by the treatment of 9 log CFU/g yeast culture at 15 °C. A high correlation was found (R2 ∼ 0.97) between the model predictions using ANN and actual values for the growth of P. expansum within the limits of the given conditions. Thus, blue rot spoilage in apples can be prevented by C. albidus application at the predicted conditions in this model.
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