Prediction model of rice eating quality using physicochemical properties and sensory quality evaluation

Abstract The objective of this study was to develop a prediction model for rice eating quality, which is one of the main factors considered by customers at the time of milled rice (MR) purchase. The overall sensory quality (OSQ) of 533 samples of MR on the market was analyzed by a trained panel from the Korea Food Research Institute (KFRI). Among the quality characteristics of MR, the moisture content ( r = .375) and damaged kernels (DA) ( r = .446) showed a correlation with the OSQ. In the case of cooked rice (CR), the a ‐value (.438) and hardness (HA; .443) presented correlations with the OSQ. Each quality factor for MR and CR was not appropriate for estimating OSQ by itself. Three eating quality prediction models were developed using the MR and CR quality factors for 400 rice samples. The prediction model from a combination of MR and CR quality parameters had higher coefficients of determination ( R 2 = .657) than the models developed from MR ( R 2 = .358) or CR ( R 2 = .555). The model validations with 133 rice samples showed similar coefficients of determination for these prediction models. Practical applications Developed models is an appropriate to be a basic method for install sensory evaluation machinery for rice. The results will cover various rice cultivars and freshness because models were derived from properties of milled rice and cooked rice together. This study will be more useful with study of rough rice freshness according to storage conditions.