Preliminary study on classification of rice and detection of paraffin in the adulterated samples by Raman spectroscopy combined with multivariate analysis.

Rice has played an important role in staple food supply of over approximately one-half of the world population. In this study, Raman spectroscopy and several multivariate data analysis methods were applied for discrimination of rice samples from different districts of China. A total of 42 samples were examined. It is shown that the representative Raman spectra in each group are different according to geographical origin after baseline correction to enhance spectral features. Moreover, adulteration of rice is a serious problem for consumers. In addition to the obvious effect on producer profits, adulteration can also cause severe health and safety problems. Paraffin was added to give the rice a desirable translucent appearance and increase its marketability. Detection of paraffin in the adulterated rice samples was preliminarily investigated as well. The results showed that Raman spectroscopy data with chemometric techniques can be applied to rapid detecting rice adulteration with paraffin.