Modeling of Button Mushroom Drying Process by Infrared System

Document Type : Research Article

Authors

1 Ph.D. Student, Faculty of Food Science and Technology, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran

2 Associate Professor, Faculty of Food Science and Technology, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran

Abstract

Button mushroom (Agaricus bisporus) as a food with high nutritional value, among the 25 species of edible mushroom, is allocated the about 40% of the market share. In this study, to drying and increased shelf life of the product, infrared radiation (IR) method was used. Thus the effects of infrared lamp power (150, 250 and 375 watts), the distance of sample from lamp (5, 10, 15 and 20 cm), samples thickness (0.5 and 1 cm) and time of 120 minute on drying of button mushroom were examined. The results of infrared drying of button mushroom showed that with increasing in lamp power and decreases in sample distance from the heat source, the drying rate increases. With increase in infrared power from 150 to 375 watts, drying rate 104.9% increased. By reducing the sample thickness from 1 to 0.5 cm, drying rate 15.8% increased. By increasing in drying process time, the samples weight loss was increased. In this study also, process modeling was done with the genetic algorithm–artificial neural network (GA-ANN) method with 4 inputs (power and lamp distance, sample thickness and drying time) and 1 output for prediction of weight reduction. The GA-ANN modeling results showed a network with 11 neurons in one hidden layer with using hyperbolic tangent activation function can be well predict the weight loss in button mushroom drying by infrared system (R=0.99). Sensitivity analysis results by optimum ANN showed the infrared lamp distance from mushroom slides was the most sensitive factor to controlling the weight loss of samples.

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References

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Innovative Food Technologies
Volume 2, Issue 4
July 2015
Pages 39-47

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History

  • Receive Date: 16 July 2014
  • Revise Date: 31 July 2014
  • Accept Date: 24 January 2016

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