Evaluation of sample pretreatment method for geographic authentication of rice using Raman spectroscopy

Abstract

The constituents of rice are heterogeneously distributed in a grain, collection of Raman spectra providing a better compositional representation of rice is an essential requirement for accurate discrimination of rice samples according to geographical origin. Homogeneity of rice flour with four different particle sizes was investigated by relative standard deviation (RSD) analysis and hierarchical clustering analysis (HCA) of Raman spectra. RSDs of Raman spectra of rice flour at 100–140 mesh were the smallest while HCA showed the highest similarities. Besides, Raman spectra of rice flour at 100–140 mesh were similar to those of rice flour with diameter below 0.6 mm. In addition, the experimental results were universally applicable for different batches and geographical origins of rice. The discrimination accuracy performed by support vector machine was obviously improved when using the Raman data of rice flour at the size of 100–140 mesh, hence, the recorded Raman spectra could provide reproducible and reliable data for discrimination the geographical origin of rice.