Instant Controlled Pressure Drop (DIC) Treatment for Improving Process Performance and Milled Rice Quality
By: Chakraborty, S
.
Contributor(s): Gautam, S. P.
Publisher: New York Springer 2019Edition: Vol.100(4), Dec.Description: 683-696p.Subject(s): Construction Engineering and Management (CEM)Online resources: Click here
In:
Journal of the institution of engineers (India): Series ASummary: In this study, instant controlled pressure drop (DIC) treatment was applied for enhancing both process and IR-20 rice quality. This treatment was integrated with soaking and hot air drying (soaking–DIC–hot air drying) in order to improve process performance and quality attributes of the rice. For the optimization, the effect of treatment pressure (TP), treatment time (TT) and decompressed state duration (DD) was investigated on hot air drying time (DT) and head rice yield (HRY). Optimized results were obtained by applying an integrated approach of artificial neural network (ANN) and particle swarm optimization (PSO). With values of TP, TT and DD as the inputs, 3-6-2 was found as the best ANN architecture in order to predict DT and HRY of the DIC-treated parboiled rice. Optimum process conditions as obtained from hybrid ANN–PSO approach were TP of 0.6 MPa, TT of 39 s and DD of 14 s with maximum HRY and minimum DT. The results reveal that IR-20 milled rice produced by DIC-treated parboiling method stands better than conventional method in terms of shorter drying time (DT of 200 min against 1140 min for conventional method), higher degree of gelatinization, higher percent of HRY (70% against 55% of total paddy rice for conventional method), lower broken ratio, ease of cooking and improved pasting and texture properties.
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In this study, instant controlled pressure drop (DIC) treatment was applied for enhancing both process and IR-20 rice quality. This treatment was integrated with soaking and hot air drying (soaking–DIC–hot air drying) in order to improve process performance and quality attributes of the rice. For the optimization, the effect of treatment pressure (TP), treatment time (TT) and decompressed state duration (DD) was investigated on hot air drying time (DT) and head rice yield (HRY). Optimized results were obtained by applying an integrated approach of artificial neural network (ANN) and particle swarm optimization (PSO). With values of TP, TT and DD as the inputs, 3-6-2 was found as the best ANN architecture in order to predict DT and HRY of the DIC-treated parboiled rice. Optimum process conditions as obtained from hybrid ANN–PSO approach were TP of 0.6 MPa, TT of 39 s and DD of 14 s with maximum HRY and minimum DT. The results reveal that IR-20 milled rice produced by DIC-treated parboiling method stands better than conventional method in terms of shorter drying time (DT of 200 min against 1140 min for conventional method), higher degree of gelatinization, higher percent of HRY (70% against 55% of total paddy rice for conventional method), lower broken ratio, ease of cooking and improved pasting and texture properties.
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