Experimental study on brown rice processing parameters based on multiple factors

To explore the parameters of a rice milling machine on the head rice yield, whiteness, and temperature rise of brown rice. Based on the response surface optimization center point method experiment, a second-order polynomial model was applied for regression analysis to draw the influence curves of various factors on the head rice rate, whiteness, and temperature rise. The order of influence of roller speed, initial temperature of brown rice, and filling rate of the milling chamber on the whole and polished rice rate, whiteness, and temperature rise of brown rice were obtained. The quadratic polynomial regression model equation of the evaluation indicators and the optimal parameter combination of the rice mill were calculated for the three factors. The results showed that three regression model equations were obtained for evaluation indicators based on three factors, and the optimal combination parameters were obtained based on the regression model: roller rotation speed of 800 r/min, initial temperature of brown rice at 10 ℃, and filling rate of the milling chamber at 30%. The optimal combination parameters were experimentally verified, with a relative error of 0.5%-2.1%.