Original ArticlePharmacognosy MagazineVol. 16 | Issue 71 | 2020 | pp. 538–542Open access
Identification of Polygonatum odoratum Based on Support Vector Machine
- 1,
- 2,
- 1,
- 1,
- 3*,
- 4,
- 1
- 1 Department of Traditional Chinese Medicine Resources, College of Traditional Chinese Medicine, Guangdong Pharmaceutical University, China.
- 2 Department of Pharmaceutical Engineering, College of Chemical Engineering and Light Industry, Guangdong University of Technology, China.
- 3 Department of Computer Science, College of Medical Information Engineering, Guangdong Pharmaceutical University,Guangzhou, China.
- 4 Department of Traditional Chinese Medicine Resources, College of Traditional Chinese Medicine, Hunan University of Chinese Medicine, Changsha, China.
Published in Pharmacognosy Magazine
Correspondence: Huaying Zhou
Department of Computer Science, College of Medical Information Engineering, Guangdong Pharmaceutical University,Guangzhou, China.
Email: 287059250@qq.com
Copyright: © 2020 Manuscript Technomedia. This is an open access article.
- Published:
- Oct 20, 2020
- Received:
- Sep 27, 2019
- Accepted:
- Apr 21, 2020
- DOI:
- 10.4103/pm.pm_410_19
How to cite
Li, Z., Zheng, J., Long, Q., Li, Y., Zhou, H., Liu, T., & Han, B. (2020). Identification of Polygonatum odoratum Based on Support Vector Machine. Pharmacognosy Magazine, 16(71), 538–542. https://doi.org/10.4103/pm.pm_410_19
Abstract
Objectives: We aimed to establish a reliable and accurate classification model of P. odoratum based on the support vector machine (SVM) and identify it from different habitats; we also aimed to identify its adulterants. Materials and Methods: In this study, we first determined the ultraviolet (UV) absorption spectrum of the water extract of the rhizome from 162 samples (including P. odoratum from Hunan, Guangdong, Heilongjiang, Yunnan, and Liaoning Provinces and adulterant species including P. inflatum, P. prattii, P. cyrtonema, and Disporopsis pernyi (Hua) Diels) by UV‑visible spectrophotometry. The UV absorption data were preprocessed with the SVM model before establishing the habitat and other details. Results: According to our results, the SVM model showed a prediction accuracy of 100%. The model accurately identified five different habitats and four different adulterants of P. odoratum. Pretreatment of samples with UV spectrum might be useful in the accurate identification of P. odoratum. Conclusion: The SVM model seems very prospective in identifying herbs with multiple habitats and its adulterants.
Keywords
Subject
Article metadata
| Title | Identification of Polygonatum odoratum Based on Support Vector Machine |
|---|---|
| Authors | Zhong Li; Jie Zheng; Qin Long; Yi Li; Huaying Zhou; Tasi Liu; Bin Han |
| Affiliations | Department of Traditional Chinese Medicine Resources, College of Traditional Chinese Medicine, Guangdong Pharmaceutical University, China.; Department of Pharmaceutical Engineering, College of Chemical Engineering and Light Industry, Guangdong University of Technology, China.; Department of Computer Science, College of Medical Information Engineering, Guangdong Pharmaceutical University,Guangzhou, China.; Department of Traditional Chinese Medicine Resources, College of Traditional Chinese Medicine, Hunan University of Chinese Medicine, Changsha, China. |
| Corresponding author | 287059250@qq.com |
| Journal | Pharmacognosy Magazine |
| Volume / Issue | Vol. 16, Issue 71 (2020) |
Also in this issue
- Methanolic Extract of Mitragyna speciosa Korth Leaf Exhibits Place Preference Only at Higher Doses in Micepp. 449–454
- Apigenin attenuated ethylene glycol induced urolithiasis in uninephrectomized hypertensive rats: A possible role of bikunin, BMP‑2/4, and osteopontinpp. 455–463
- Neuroprotective Effect of the Essential Oil of Lavandula officinalis against Hydrogen Peroxide‑induced Toxicity in Micepp. 464–470
- Evaluation of Antioxidant, Anti-inflammatory, and Analgesic Activities of Cissus vitiginea L. Leavespp. 471–478
- Narirutin Suppresses M1‑Related Chemokine InterferonGamma-Inducible Protein‑10 Production in Monocyte‑Derived M1 Cells via Epigenetic Regulationpp. 479–485
Readers Also Viewed
Development and Validation of UV/visible Spectrophotometric Method for Estimation of Piroxicam from Bulk and Formulation
Sandip Mohan Honmane, Kunal Rajaram Yadav, Yuvraj Dilip Dange
Apr 23, 2025
Effects of Artificial Intelligence on Academic Performance of Library and Information Science University Students: A Meta-Analysis (2023-2025)
Kayode Sunday John Dada
Aug 6, 2026
Bridging Innovation and Impact: A Multidisciplinary Approach to Contemporary Research Challenges
Mueen Ahmed KK
Aug 11, 2026