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

Abstract

In this study, the effect of infrared (IR) on decontamination of <em>Bacillus cereus</em> 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 <em>B. cereus</em> 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 <em>B. cereus</em> in cardamom by artificial neural network (ANN) model. The developed genetic algorithm-ANN (GA-ANN), which included 12 hidden neurons, could predict <em>B. cereus</em> population with <em>R</em>² = 0.908. The results indicated that GA-ANN model could give good prediction for the population of <em>B. cereus</em>. Sensitivity analysis results showed that IR irradiation time was the most sensitive factor for the prediction of <em>B. cereus</em> population.