Mathematical modeling for the prediction of some quality indices of white rice based on the bending test of grains using response surface methodology (RSM)

Investigating the properties of a rice single kernel is one of the methods used to determine the quality of grain bulk. In addition, one of the major problems in predicting the quality properties of rice is the high cost of conducting laboratory experiments in food industry. Therefore, the objective of this study was to predict some quality properties of white rice via the use of bending test in three varieties of white rice (Khazar, Dorfak and Kadus) at two levels of moisture content 9 and 14% w. b. In this study, the response surface methodology (RSM) (historical data design) was used to model and estimate quality properties (Amylose content (AC), Protein content (PC), Gelatinization Temperature (GT), Gel Consistency (GC), Minimum viscosity (Min. V), Peak Viscosity (PV), Final Viscosity (FV), Breakdown viscosity (BD.V), Setback Viscosity (SB.V), Peak Time (PT) and Pasting temperature (Pasting. T)) of white rice through analyzing independent variables (strength value of rice single kernel in deformation of 0.05 mm, maximum rupture force, maximum deformation, rupture energy, tangent modulus at deformation of 0.05 mm, maximum tangent modulus, secant modulus at deformation of 0.05 mm and maximum secant modulus). The results of ANOVA, showed that all models are significant at probably levels of (P < 0.05) and (P < 0.01). According to the results, the most appropriate model for prediction of the response variables was the linear-Interaction (2FL) model whit the coefficient of determination (R2 ≥ 0.95). In addition, Optimum conditions of independent variables were determined based on the maximum goal or the minimization of response variables. The desirability degree of the optimization was (R2 ≥ 0.82). The results indicated that the response surface methodology can be quite useful in optimizing the models developed for predicting the quality properties of white rice from the strength properties of a single kernel.