Pseudostellaria heterophylla is a very popular traditional Chinese medicine herb, also called "Taizishen." Discrimination of P. heterophylla from different regions is critical for ensuring the effectiveness of drug use, because the drug effects of P. heterophylla from different regions are diversity of each other. To discriminate P. heterophylla from different regions rapidly and effectively, a model extracted by competitive adaptive reweighted sampling (CARS) was established. Original spectra of P. heterophylla in wave number range of 10,000 to 4,000 cm-1 were acquired. Orthogonal partial least squares discriminant analysis (OPLS-DA) was also used to establish a suitable model. CARS was performed for extracting key wave number variables. We found that the near-infrared spectrum of a series of samples analyzed by Row-center-SG, CARS, and OPLS-DA can effectively distinguish the P. heterophylla from different regions, and the accuracy of OPLS-DA model is also satisfactory in terms of good discrimination rate. These results show that the Row-center-SG, CARS, and OPLS-DA model can be used to identify the P. heterophylla from different regions. PRACTICAL APPLICATION: According to our research results, we can draw a conclusion that our research results may be used to distinguish the traditional Chinese medicine from those from different places of origin and the powder with similar appearance.
Keywords: Pseudostellaria heterophylla; FT-NIR spectroscopy; competitive adaptive reweighted sampling; orthogonal partial least squares discriminant analysis.
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