We measured Raman spectra in a cooking process of rice grains and applied principal component analysis (PCA) to confirm binary states of starch: ordered and disordered states of starch in the cooking process by analytically separating sharper and broader components for the bands around 870 and 940cm⁻¹ due to starch. These sharper and broader components were optimized by non-negative matrix factorization (NMF), based on the PCA. The ratio defined using these two components clearly distinguished before/after the cooking of rice grains. The ratio can be an effective indicator to estimate the degree of cooking.

中文翻译：

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使用主成分分析和非负矩阵分解对米粒进行生物拉曼研究：检测烹饪过程中淀粉的有序和无序状态

我们测量了米粒烹饪过程中的拉曼光谱，并应用主成分分析 (PCA) 来确认淀粉的二元状态：通过分析分离 870 和 940 厘米附近波段的更清晰和更宽的成分，在烹饪过程中淀粉的有序和无序状态^-1由于淀粉。这些更清晰和更广泛的组件通过基于 PCA 的非负矩阵分解 (NMF) 进行了优化。使用这两种成分定义的比例在米粒烹饪之前/之后清楚地区分。该比率可以作为估计烹饪程度的有效指标。