Investigation of drying process of different Iranian rice cultivars by Ohmic pre-treatment in microwave dryer and modeling by response surface methodology and artificial neural network

Document Type : Research Article

Authors

1 Associate Professor, Department of Bio-system mechanical engineering, Faculty of Water and Soil, Gorgan University of Agricultural Sciences and Natural Resources.

2 Department of Bio-System Mechanical Engineering, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran.

3 Department of Bio-System Mechanical Engineering, Sari University of Agricultural Sciences and Natural Resources, Sari, Iran.

Abstract

In this research, investigation drying of four rice cultivars (Fajr, Taromi , Dom-siah and Neda) were done by microwave dryer and using ohmic pre-treatment. Three voltages of 125, 150, 175 volts were selected for the pre- treatment ohmic in three times 5, 10 and 15 min and the weight changing were measured and recorded. Finally, the samples placed in the microwave by power 600 watt and every two minutes until dry weight changes were measured. The results of the experiment were analyzed using response surface methodology and artificial neural network. Investigation on rice varieties in the ohmic process showed that Fajr variety had the highest water extraction and weight loss compared to other varieties (Taromi , Dom-siah and Neda) and during the pre-treatment process of ohmic and also during drying by the microwave, those had more moisture extracted. And after that, Tarom and Dom-Siah had the highest amount of moisture removal, Also the lowest moisture removal during the Ohmic heating and drying process were in Neda cultivar. In addition to weight loss in drying with a microwave dryer, Increasing voltage and ohmic time had higher moisture content than low voltage and low ohmic time and rice cultivar Fajr had more weight loss than other cultivars. Also, the predicted values of the response surface method (RSM) models and artificial neural network showed that the accuracy of the artificial neural network was 0.30 more than the predicted RSM numbers.

Graphical Abstract

Investigation of drying process of different Iranian rice cultivars by Ohmic pre-treatment in microwave dryer and modeling by response surface methodology and artificial neural network

Highlights

  • -The ohmic pretreatment process caused more moisture to be extracted from the samples.
  • Artificial neural network has better prediction in the field of rice drying than response surface method.
  • The ohmic processing time has a greater impact than the ohmic processing voltage.
  • The ohmic processing had a significant effect on the weight changes of rice cultivars and made a significant difference.

Keywords

Main Subjects

References

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Innovative Food Technologies
Volume 7, Issue 4
August 2020
Pages 497-515

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History

  • Receive Date: 08 November 2019
  • Revise Date: 03 February 2020
  • Accept Date: 10 June 2020

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