Modeling of strawberry drying process using infrared dryer by genetic algorithm- artificial neural network method

Due to low energy efficiency and prolonged drying time of agricultural products by conventional methods, application of the new techniques such as infrared radiation, must be investigated. In this study, to drying and increased shelf life of the strawberry, infrared radiation (IR) method was used. The effect of infrared lamp power (150, 250 and 375 watts), the distance of sample from lamp (5, 7.5 and 10 cm) and time of 110 minute on drying of strawberry were examined. The results of infrared drying of strawberry showed that with increasing in lamp power and decreases in sample distance from the heat source, the drying rate was increased. With increase in infrared power from 150 to 375 watts, drying rate 69.24% increased. By increasing in sample distance from 5 to 10 cm, drying rate 23.55% decreased. Modeling of process was done with the genetic algorithm–artificial neural network (GA-ANN) method with 3 inputs (lamp power, distance and time) and 1 output (weight loss). The GA-ANN modeling results showed a network with 9 neurons in 1 hidden layer with using hyperbolic tangent activation function can be predict the weight loss in strawberry drying by infrared method (R2=0.999). Sensitivity analysis results by optimum ANN showed the infrared power was the most sensitive factor to controlling the weight loss of strawberry slides.