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Instant Controlled Pressure Drop (DIC) Treatment for Improving Process Performance and Milled Rice Quality

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Abstract

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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Abbreviations

ANN:

Artificial neural network

ANOVA:

Analysis of variance

ARD:

Average relative deviation (%)

c 1, c 2 :

Acceleration constants

DD:

Decompressed state duration (s)

DF:

Degree of freedom

DIC:

Instant controlled pressure drop treatment

DSC:

Differential scanning calorimetry

DT:

Drying time (min)

H ij :

Inputs to hidden layer

H oj :

Outputs of the hidden layer

HRY:

Head rice yield (%)

L I :

Input layer

L H :

Hidden layer

L o :

Output layer

MSE:

Mean square error

O j :

Final output of the output layer

p g :

Position of the best particle

p i :

Best fitness value of the ith particle

PSO:

Particle swarm optimization

R 2 :

Coefficient of determination

rand ():

Random values between 0 and 1

RSM:

Response surface methodology

RVA:

Rapid Visco-Analyzer

SPSO:

Standard particle swarm optimization

\(T_{\text{h}}\) :

Bias values of the hidden layer

T o :

Bias values of the output layer

TPA:

Texture profile analyzer

TP:

Treatment pressure (MPa)

TT:

Treatment time (s)

v id :

dth dimension velocity for the ith particle

w :

Inertia weight for balancing the global and local search ability

wb:

Wet basis (%)

W ih :

Interconnection weights of input and hidden layers

W ho :

Interconnection weights of hidden and output layers

x id :

dth dimension location for the ith particle

x 1 :

TP (MPa)

x 2 :

TT (s)

x 3 :

DD (s)

β 0 :

Constant term

β i :

Linear effects

β ii :

Quadratic effects

β ij :

Interaction effects

φ 1, φ 2 :

Random numbers distribution

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Authors and Affiliations

  1. Department of Food Engineering and Technology, Tezpur University, Tezpur, Assam, 784028, India

    Sourav Chakraborty, Swapnil Prashant Gautam & Manuj Kumar Hazarika

  2. Department of Chemical Engineering, IIT Guwahati, Guwahati, Assam, India

    Pranjal Pratim Das

Authors
  1. Sourav Chakraborty
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  2. Swapnil Prashant Gautam
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  3. Pranjal Pratim Das
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  4. Manuj Kumar Hazarika
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Correspondence to Manuj Kumar Hazarika.

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Chakraborty, S., Gautam, S.P., Das, P.P. et al. Instant Controlled Pressure Drop (DIC) Treatment for Improving Process Performance and Milled Rice Quality. J. Inst. Eng. India Ser. A 100, 683–695 (2019). https://doi.org/10.1007/s40030-019-00403-w

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