| Abstract: | The purpose of this study was to develop highly accurate regression models with texture parameters of cooked milled rice grains for predicting pasting properties in terms of quality index of rice flour. Two methods were adopted as the texture measurement to acquire predictors for the models. In the calibration set, all the multiple regression models by a single‐grain method exhibited a higher R2 than those by a three‐grain method. Each of the former models also showed a lower SEP and a higher RPD in the validation set. The prediction performance was best for consistency (RPD = 2.4). The single‐grain method was more advantageous for the pasting prediction. These results suggest that the models based on grain texture could predict rice flour quality. |
