Modeling the effect of different infrared treatment on B. cereus in cardamom seeds and using genetic algorithm-artificial neural network

Document Type: Original research

Authors

1 Department of Food Process Engineering, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran

2 Department of Food Science and Technology, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran

Abstract

In this study, the effect of infrared (IR) on decontamination of Bacillus cereus in cardamom seeds were determined at difference IR radiation powers (100, 200, and 300 W), different sample distances from radiation source (5, 10 and 15 cm) and various holding times. The most successful reduction in B. cereus numbers (5.11 log CFU/g) was achieved after a holding time of 8 min at 300 W IR power and 15 cm distance. Data were analyzed to predict antibacterial effects of IR against B. cereus in cardamom by artificial neural network (ANN) model. The developed genetic algorithm-ANN (GA-ANN), which included 12 hidden neurons, could predict B. cereus population with R2 = 0.908. The results indicated that GA-ANN model could give good prediction for the population of B. cereus. Sensitivity analysis results showed that IR irradiation time was the most sensitive factor for the prediction of B. cereus population.

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