Near-Infrared Spectroscopy and Chemometric Approaches for Discrimination of Brown and Milled Rice Based on Nutritional and Functional Properties

Introduction
Rice (Oryza sativa) is a major staple food worldwide, providing over one-fifth of global caloric intake. Milling brown rice (BR) into white rice (WR) removes the bran layer, reducing nutrients, dietary fiber, minerals, vitamins, and bioactive compounds. As a result, BR retains a superior nutritional profile and potential health benefits compared with refined WR. This study aimed to compare the chemical composition, starch functional properties, and near-infrared (NIR) spectral characteristics of BR and WR, and to develop chemometric models for distinguishing rice samples based on their degree of polishing.

Methods
Brown and milled rice samples were analyzed for chemical composition, starch functional properties, and NIR spectra. Student’s t-test (p < 0.05) assessed significant differences between groups, while Principal Component Analysis (PCA) identified compositional patterns. Classification models using Partial Least Squares Discriminant Analysis (PLS-DA) and Support Vector Machine (SVM) were developed from NIR data to distinguish rice based on polishing degree.

Results
Significant differences were found between BR and WR in ash, lipid, fiber, and protein contents. BR was richer in these components due to the bran layer, while WR showed higher starch and amylose levels from the endosperm. These differences affected starch thermal behavior, including gelatinization and setback. NIR spectroscopy identified key regions related to moisture, starch, proteins, lipids, and fiber, enabling clear discrimination of the two rice types. PCA showed effective separation, while PLS-DA and SVM models achieved accurate classification based on polishing degree.

Conclusion
The milling process alters rice composition and functionality. NIR combined with chemometric methods (PCA, PLS-DA, SVM) offers a fast, non-destructive, and reliable approach for rice classification, supporting quality control, authenticity testing, and real-time processing decisions.