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

Abstract

Abstract 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.