LAUSR

The effects of parboiling indicators (soaking temperature and steaming time) on the degree of starch gelatinization (DSG) and several rice quality properties [head rice yield (HRY), color value, lightness, and hardness] of parboiled rice were investigated. A mathematical model was used to predict DSG and rice quality from the parboiling conditions, which were varied as follows: 60, 65, and 70 °C for the soaking temperature and 2, 6, and 10 min for the steaming time (at 96 °C). A central composite design was applied and a total of 13 experimental runs were generated for each step. An ANOVA test showed the all models were significant (p < 0.01) and there was no significant lack of fit in any of the response variables. The most appropriate model for prediction the amount of DSG, HRY, color value, lightness, and hardness of samples was linear (R2 = 0.87), quadratic (R2 = 0.92), quadratic (R2 = 0.97), quadratic (R2 = 0.86), and linear (R2 = 0.94) model, respectively. The DSG and hardness increased with increasing soaking temperature and steaming time, while the HRY and lightness showed a maximum at a steaming time of 6 min. The statistical model was used to predict the optimal parboiling conditions for global optimization of the quality properties. Practical applications Parboiled rice enjoys high popularity because of its high nutritional content. The most important effect of parboiling is rice gelatinization. The degree of starch gelatinization (DSG) and quality properties (head rice yield, color value, lightness, and hardness) of parboiled rice are determined by the parboiling indicators (PI): soaking temperature and steaming time. These properties can be predicted based on PI using mathematical models. Increasing the parboiling indicators increases the cost of parboiling process. For the parboiling industry, it will help to determine the soaking temperature and steaming time of rice to yield the desired product quality. For this reason, optimizing the parboiling process is economically important for the rice industry.