Abstract: Fresh-cut vegetables are exposed to the risk of Salmonella contamination. Effective non-thermal sterilization methods and early warning systems play important roles in ensuring food safety of fresh-cut products. The effects of thermosonication (TS) combined with tea polyphonels (TP) on the population of Salmonella enterica in fresh-cut wax gourd during storage at 25, 10 and 4 °C were evaluated. Adaptive neuro-fuzzy inference system (ANFIS) based models with 8 types of membership functions (MFs) were developed and estimated for predicting S. enterica population. The combined treatment of TS and TP significantly reduced the Salmonella population in fresh-cut melon by about 2.20 lg CFU/g. During storage at 25 ℃, 10 ℃ and 4 ℃, samples in treatment group had lower Salmonella population levels than that in control group. ANFIS model with 2 ‘gaussmf’ type input MFs and 8 if-then rules had the best performance at both training and prediction phases in present study. The root mean squared errors (RMSEs) were less than 0.2 and the R2 for experimental populations and predicted data were greater than 0.99, indicating that ANFIS system performed well in predicting the population of Salmonella in fresh-cut wax gourd. It could be easily applied to various situations and provide a powerful tool for modelling and predicting microbe population and shelf life of food products.
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