Optimization of fluidized bed preconditioning for microwave puffed rice using integrated artificial neural network and genetic algorithm approach

Abstract

AbstractPreconditioning of rice is heat curing of salt infused moist parboiled rice prior to microwave puffing process. The sudden expansion of moisture present in the interstices of the starch granules caused by microwave heating of the preconditioned rice results in highly expanded smooth‐surface puffed rice. The expansion ratio (ER) and percentage of puffing (PP) of the microwave puffed rice preconditioned under different conditions were varied between 5.16–7.51 and 84.32–93.12%, respectively. Optimum temperature, air velocity, and salt concentration for fluidized bed preconditioning obtained by using integrated artificial neural network and genetic algorithm approach were estimated to be 70°C, 2.9 m s−1, and 4%, respectively. The predicted values of ER and PP at optimum combination of independent variables were 7.5 and 92.82%, respectively. Scanning electron microscopy revealed that preconditioning transformed the compact polyhedral structure of starch granules to fused mass with interlocking and overlapping structure.Practical applicationsPreconditioning with fluidized bed drying of salt infused rice would be feasible as a substitute with traditional direct heat curing process with saving of time, labor, and energy. This study would enhance understanding of the effects of preconditioning process on the mechanisms of puffing. Artificial neural network and genetic algorithm integrated optimization can be applied for prediction and control of mechanization of the preconditioning and puffing process. Preconditioned rice can be puffed directly by using a microwave oven that will make the puffing process convenient to consumers.