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.

中文翻译：

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利用拉曼光谱和多变量分析评价白米的食用品质

本研究使用拉曼光谱法（532 nm 激发光束）结合多变量校准评估生白米的食用品质。进行该分析是为了建立光谱特征与传统感官测试结果之间的相关性，目的是建立校准模型。每个模型的准确性根据相关的确定系数（R ²）、校准均方根误差和预测值均方根误差来确认。基于偏最小二乘回归的模型 为白米的食用品质提供了合理的预测（R ² > 0.8）。此外，利用投影技术中的变量重要性对影响总评价的成分进行了评估，结果表明淀粉、直链淀粉、氨基酸、葡聚糖、碳水化合物和蛋白质对于决定白米的品质至关重要。这种新开发的方法可能适用于大米品质的评估，原则上也可以应用于其他食品的评估。