Evaluation of eating quality of white rice using Raman spectroscopy with multivariate analysis

Abstract

The present study evaluated the eating quality of uncooked white rice using Raman spectroscopy, operating with a 532 nm excitation beam, in conjunction with multivariate calibration. This analysis was performed to establish correlations between features of the spectra and the results of conventional sensory tests with the aim of establishing calibration models. The accuracy of each model was confirmed based on the associated coefficient of determination (R²), root-mean-square error of calibration and root mean square error of prediction values. Models based on partial least-squares regression provided reasonable predictions (R² > 0.8) for the eating quality of white rice. In addition, the components affecting total evaluation were evaluated using the variable importance in projection technique, and the results showed that starch, amylose, amino acids, glucans, carbohydrates, and proteins are all crucial in terms of determining the quality of white rice. This newly developed method is likely to be suitable for the evaluation of rice quality and, in principle, could also be applied to the assessment of other foods.