Rapid authentication of Pseudostellaria heterophylla (Taizishen) from different regions by Raman spectroscopy coupled with chemometric methods

The quality of Pseudostellaria heterophylla depends on the growing area of the plants greatly. Compared with near infrared spectroscopy employed to discriminate the geographic regions before, the Raman signal is more obvious. So far, discrimination of P. heterophylla from different regions by Raman spectroscopy has not yet been realized. Hence, Raman spectroscopy coupled with chemometric methods to rapidly and effectively discriminate P. heterophylla from different regions was studied. Original spectra of P. heterophylla in wavenumber range of 4000–100 cm−1 were acquired. Then, a steady and exact model, partial least squares discriminant analysis (PLS-DA), was constructed. And competitive adaptive reweighted sampling (CARS) was further used to extract effective wavelength spectral characteristic variables. Results show that CARS-PLS-DA model is an appropriate model to discriminate the P. heterophylla, with determination coefficient of calibration (R2C), root mean square error of cross validation (RMSECV), determination coefficient of prediction (R2P), and root mean squared error of prediction (RMSEP) are 0.9468, 0.1979, 0.9665, and 0.1120, respectively. These results demonstrated that the built method is useful and effective to discriminate P. heterophylla from different regions, which provide a new idea in the application of rapid field test.