Bio-Raman Research Using Principal Component Analysis And Non-Negative Matrix Factorization On Rice Grains: Detections Of Ordered And Disordered States Of Starch In The Cooking Process

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 940 cm(-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.