Parboiled Paddy Drying with Different Dryers: Thermodynamic and Quality Properties, Mathematical Modeling Using ANNs Assessment

Ebrahim Taghinezhad; Antoni Szumny; Mohammad Kaveh; Vali Rasooli Sharabiani; Anil Kumar; Naoto Shimizu

doi:10.3390/foods9010086

Parboiled Paddy Drying with Different Dryers: Thermodynamic and Quality Properties, Mathematical Modeling Using ANNs Assessment

Foods. 2020 Jan 13;9(1):86. doi: 10.3390/foods9010086.

Authors

Ebrahim Taghinezhad¹, Antoni Szumny², Mohammad Kaveh³, Vali Rasooli Sharabiani³, Anil Kumar⁴, Naoto Shimizu⁵

Affiliations

¹ Department of Agricultural Technology Engineering, Moghan College of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil 56199-11367, Iran.
² Department of Chemistry, Wroclaw University of Environmental and Life Science, CK Norwida 25, 50-375 Wrocław, Poland.
³ Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil 56199-11367, Iran.
⁴ Department of Mechanical Engineering, Delhi Technological University, Delhi 110042, India.
⁵ Research Faculty of Agriculture, Hokkaido University, Hokkaido 064-8589, Sapporo, Japan.

Abstract

The effect of hybrid infrared-convective (IRC), microwave (MIC) and infrared-convective-microwave (IRCM) drying methods on thermodynamic (drying kinetics, effective moisture diffusivity coefficient (D_eff), specific energy consumption (SEC)) and quality (head rice yield (HRY), color value and lightness) characteristics of parboiled rice samples were investigated in this study. Experimental data were fitted into empirical drying models to explain moisture ratio (MR) variations during drying. The Artificial Neural Network (ANN) method was applied to predict MR. The IRCM method provided shorter drying time (reduce percentage = 71%) than IRC (41%) and microwave (69%) methods. The D_eff of MIC drying (6.85 × 10^-11-4.32 × 10^-10 m²/s) was found to be more than the observed in IRC (1.32 × 10^-10-1.87 × 10^-10 m²/s) and IRCM methods (1.58 × 10^-11-2.31 × 10^-11 m²/s). SEC decreased during drying. Microwave drying had the lowest SEC (0.457 MJ/kg) compared to other drying methods (with mean 28 MJ/kg). Aghbashlo's model was found to be the best for MR prediction. According to the ANN results, the highest determination coefficient (R²) values for MR prediction in IRC, IRCM and MIC drying methods were 0.9993, 0.9995 and 0.9990, respectively. The HRY (from 60.2 to 74.07%) and the color value (from 18.08 to 19.63) increased with the drying process severity, thereby decreasing the lightness (from 57.74 to 62.17). The results of this research can be recommended for the selection of the best dryer for parboiled paddy. Best drying conditions in the study is related to the lowest dryer SEC and sample color value and the highest HRY and sample lightness.

Keywords: Artificial Neural Network; mathematical modeling; parboiled paddy; quality; thermodynamic.