Nondestructive discrimination of Potentilla anserina L. from different production areas based on near‐infrared spectroscopy

• Published in: Phytochemical analysis 2024-06, Vol.35 (4), p.723-732
• Main Authors: Ma, Xiaobo, Hai, Ping, Zhang, Mengqi, Tian, Mengyin, Zhang, Wei, Li, Lian, Zang, Hengchang
• Format: Article
• Language: English
• Subjects: Adaptive sampling; Chinese medicine; Discriminant Analysis; discrimination analysis; Drugs, Chinese Herbal - chemistry; Herbal medicine; Infrared spectra; Infrared spectroscopy; Least-Squares Analysis; Medicine, Chinese Traditional; model transfer; Near infrared radiation; near‐infrared spectroscopy; Potentilla - chemistry; Potentilla anserina; Principal Component Analysis; Principal components analysis; Quality control; Spectroscopy, Near-Infrared - methods; Spectrum analysis; Test sets; Traditional Chinese medicine
• ISSN: 0958-0344; 1099-1565
• DOI: 10.1002/pca.3324

Introduction The traditional Chinese medicine (TCM) Potentilla anserina L. can use both as food and medicine. At present, the market mainly depends on experience to identify the species and determine the production areas of P. anserina. To ensure the quality of P. anserina, it is essential to improve the level of quality control. Objective We aimed to establish a rapid and nondestructive discrimination model to identify P. anserina from different production areas by near‐infrared spectroscopy. Methods The spectra of complete P. anserina medicinal materials and their powder of the same variety from four production areas were collected, and principal component analysis discriminant analysis and partial least squares discriminant analysis (PLS‐DA) were conducted based on different pretreatment methods and band selection methods. Then, the spectra of complete medicinal materials were converted into the spectra of medicinal powder for nondestructive identification. Results The correct recognition rate (CRR) of the PLS‐DA discriminant model was the best after spectral preprocessing using autoscaling and competitive adaptive reweighted sampling for band selection. The CRRs of the calibration set and validation set were 100%, the CRRs of the external test set were 95%, 90%, 82%, and 88%, respectively, and the CRRs of the transfer external test set were 84%, 80%, 82%, and 86%, respectively. Conclusion We realized the nondestructive and effective identification of P. anserina from different origins and laid a foundation for the industrialization and upgrading of TCM. The spectra of the complete medicinal material of P. anserina were transferred to the spectra of medicinal powder, and a fast and nondestructive model of producing areas discrimination of P. anserina was established. This method realizes the identification of medicinal material origins from the same variety and has significance for guiding the identification of plant‐based drugs and the quality control of TCM.