Rapid Quality Identification of Decoction Pieces of Crude and Processed Corydalis Rhizoma by Near-Infrared Spectroscopy Coupled with Chemometrics.

In order to identify the quality of crude and processed Corydalis Rhizoma decoction pieces, the research established a simple, fast, reliable, and validated near-infrared qualitative and quantitative model combined with chemometrics. 51 batches of crude and 40 batches of processed Corydalis Rhizoma from the Zhejiang and Jiangsu provinces of China were collected and analyzed. Crude and processed Corydalis Rhizoma samples were crushed to obtain NIR spectra. The content of seven alkaloids in crude and processed Corydalis Rhizoma was determined by high-performance liquid chromatography (HPLC). Pretreatment methods were screened such as normalization methods, offset filtering methods, and smoothing. Combined with partial least squares-discriminant analysis (PLS-DA) and partial least squares (PLS), the qualitative and quantitative models of crude and processed Corydalis Rhizoma were established, and the correlation coefficient (R 2), root mean square error of calibration (RMSEC), and root mean square error of prediction (RMSEP) were used as evaluation indexes. Tetrahydropalmatine was used as an example for screening pretreatment methods; the results showed that MSC combined with the second derivative and no smoothing and the model with the wavelength range of 10000-5000 cm-1 had the best predictive ability and applied to all seven alkaloid components. Among them, the correlation coefficients were all higher than 0.99, and RMSEC and RMSEP were all less than 1%. The qualitative and quantitative model of the seven alkaloids in Corydalis Rhizoma can effectively identify the crude and processed Corydalis Rhizoma and determine the content of the seven alkaloids. By studying the NIR qualitative and quantitative models of crude and processed Corydalis Rhizoma, we can achieve rapid discrimination and quantitative prediction of crude and processed Corydalis Rhizoma. These methods can greatly improve the efficiency of traditional Chinese medicine analysis and provide a strong scientific basis for the quality identification and control of traditional Chinese medicine.