Geographical Origin Discrimination of White Rice Based on Image Pixel Size Using Hyperspectral Fluorescence Imaging Analysis

Abstract

Geographical origin discrimination of white rice is an important endeavor in preventing illegal distribution of white rice and regulating and standardizing food safety and quality assurance. The aim of this study was to develop a method for geographical origin discrimination between South Korean and Chinese rice using a hyperspectral fluorescence imaging technique and multivariate analysis. Hyperspectral fluorescence images of South Korean and Chinese rice samples were obtained in the wavelength range of 420 nm to 780 nm with intervals of 4.8 nm using 365 nm wavelength ultraviolet-A excitation light. Partial least squares discriminant analysis models were developed and applied to the acquired image to determine the geographical origins of the rice samples. In addition, various pre-processing techniques were applied to improve the discrimination accuracy. Accordingly, the pixel size of the hyperspectral image was determined. The results revealed that the optimum pixel size of the hyperspectral image that was above 7 mm × 7 mm showed a high discrimination accuracy. Moreover, the geographical origin discrimination model that applied the first-order derivative achieved a high discrimination accuracy of 98.89%. The results of this study showed that hyperspectral fluorescence imaging technology can be used to quickly and accurately discriminate the geographical origins of white rice.

Keywords

• hyperspectral imaging
• geographical origin
• white rice
• partial least squares analysis
• fluorescence imaging
• pixel dimension