Examination of the Heating Condition Based on the Quality Prediction of the Processed Food Product Using Raw Okara

Abstract

This study focused on the processed food products, using raw okara (a food product developed to mitigate problems associated with mass disposal of soy waste). To examine the heating condition effectively, we simulated food qualities during heating. Color change was treated as a first-order reaction, and kinetic parameters (E_a = 61.6 kJ/mol，Z = 4.93×10⁵ 1/s) were calculated by Golden section method. Moisture content was calculated via mass transfer analysis, based on Fick’s laws of diffusion. Our simulation predicted values for color, moisture content, water activity, and texture that were in good agreement with experimental values. We determined that, to achieve an equivalent to a commercial product, it was suggested that about 1/2 could shorten heating time by changing surface temperature from 80℃ to 120℃. Thus, this simulation technique can contribute to the shortening of heating times for processed food products.