Abstract
Mathematical models have been developed to predict the probability of growth of spoilage moulds in response to various preservative systems in ready to drink beverages. A Box-Behnken experimental design included five variables, each at three levels: pH (2·8, 3·3, 3·8), titratable acidity (0·20%, 0·40%, 0·60%), sugar content (8·0, 12·0, 16·0 °Brix), and preservative concentrations (sodium benzoate and potassium sorbate, each 100, 225, 350 ppm). Duplicate samples were inoculated with a mould cocktail consisting of equal proportions of Aspergillus niger and Penicillium spinulosum spores (5·0×104spores/ml). The inoculated samples were plated on malt extract agar after 0, 1, 2, 4, 6, and 8 weeks. Logistic regression was used to create predictive models. The pH, titratable acidity, sugar content, sodium benzoate, and potassium sorbate levels were all found to be significant factors in predicting the probability of mould growth over time. Interactions between pH and sodium benzoate, pH and potassium sorbate, and pH and sugar content were also statistically significant. This logistic model was validated against 14 new conditions and predicted the growth of mould after 8 weeks with over 96% accuracy. Product developers can use these models to predict mould growth in ready to drink beverages.
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