Identification of Polygonatum odoratum Based on Support Vector Machine

被引:2
|
作者
Li, Zhong [1 ]
Zheng, Jie [2 ]
Long, Qin [1 ]
Li, Yi [1 ]
Zhou, Huaying [3 ]
Liu, Tasi [4 ]
Han, Bin [1 ]
机构
[1] Guangdong Pharmaceut Univ, Dept Tradit Chinese Med Resources, Coll Tradit Chinese Med, Guangzhou, Peoples R China
[2] Guangdong Univ Technol, Dept Pharmaceut Engn, Coll Chem Engn & Light Ind, Guangzhou, Peoples R China
[3] Guangdong Pharmaceut Univ, Dept Comp Sci, Coll Med Informat Engn, Guangzhou, Peoples R China
[4] Hunan Univ Chinese Med, Dept Tradit Chinese Med Resources, Coll Tradit Chinese Med, Changsha, Peoples R China
关键词
Adulterants; identification; Polygonatum odoratum; support vector machine; ultraviolet;
D O I
10.4103/pm.pm_410_19
中图分类号
R914 [药物化学];
学科分类号
100701 ;
摘要
Background: The dried rhizome of Polygonatum odoratum (Mill.) Druce has been widely used in traditional medicinal preparations in China, Japan, and Korea. In China, it is distributed in Hunan, Guangdong, and Liaoning provinces, and its quality differs from habitat to habitat. In addition, P. odoratum has some adulterants, such as Polygonatum inflatum Kom, Polygonatum prattii Baker, and Polygonatum cyrtonema Hua. The morphological traits and chemical composition of the aforementioned adulterants have many similarities with those of P. odoratum. Therefore, it is possible that people often use adulterants instead of P. odoratum for clinical treatment. 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.
引用
收藏
页码:538 / 542
页数:5
相关论文
共 50 条
  • [1] Authorship identification based on support vector machine
    Yoshida, A
    Nobesawa, S
    Sato, K
    Saito, H
    6TH WORLD MULTICONFERENCE ON SYSTEMICS, CYBERNETICS AND INFORMATICS, VOL III, PROCEEDINGS: IMAGE, ACOUSTIC, SPEECH AND SIGNAL PROCESSING I, 2002, : 423 - 428
  • [2] Fever Identification of Pigs Based on Support Vector Machine
    Zhu Weixing
    Wang Wei
    2011 INTERNATIONAL CONFERENCE ON COMPUTERS, COMMUNICATIONS, CONTROL AND AUTOMATION (CCCA 2011), VOL II, 2010, : 177 - 180
  • [3] Rapid Raman spectroscopic identification of three homoisoflavanones in polygonatum odoratum based on twice chromatography derivatization
    Xu, Tao
    Li, Qian
    Xu, Feng
    Li, Li
    Li, Shuang
    Dong, Yanli
    Liang, Xin
    Zhang, Hongguang
    Hou, Peng
    Sun, Ge
    Cao, Meng
    Dou, Hao
    HELIYON, 2023, 9 (12)
  • [4] Leaf spot of Polygonatum odoratum caused by Colletotrichum spaethianum
    Liu, Liping
    Zhang, Lin
    Qiu, Penglei
    Wang, Yu
    Liu, Yanni
    Li, Yu
    Gao, Jie
    Hsiang, Tom
    JOURNAL OF GENERAL PLANT PATHOLOGY, 2020, 86 (02) : 157 - 161
  • [5] Study of nonlinear system identification based on support vector machine
    Zhang, MG
    Yan, WW
    Yuan, ZT
    PROCEEDINGS OF THE 2004 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7, 2004, : 3287 - 3290
  • [6] Identification method of encrypted traffic based on support vector machine
    Cheng G.
    Chen Y.
    Dongnan Daxue Xuebao (Ziran Kexue Ban)/Journal of Southeast University (Natural Science Edition), 2017, 47 (04): : 655 - 659
  • [7] Antioxidant homoisoflavonoids from Polygonatum odoratum
    Zhou, Xiaoling
    Zhang, Yuping
    Zhao, Huading
    Liang, Junsheng
    Zhang, Yi
    Shi, Shuyun
    FOOD CHEMISTRY, 2015, 186 : 63 - 68
  • [8] Chemical constituents from Polygonatum odoratum
    Quan, Ling-Tong
    Wang, Shao-Chen
    Zhang, Jing
    BIOCHEMICAL SYSTEMATICS AND ECOLOGY, 2015, 58 : 281 - 284
  • [9] Chemical Composition Analysis and Biofunctionality of Polygonatum sibiricum and Polygonatum odoratum Extracts
    Liao, Wayne C.
    Huang, Jung -Ping
    Huang, Wen-Ying
    BIORESOURCES, 2023, 18 (02) : 3608 - 3619
  • [10] Smoke Identification of Low-light Indoor Video Based on Support Vector Machine
    Huang, Mengtao
    Wang, Yi
    Hu, Yongcai
    PROCEEDINGS OF 2017 3RD IEEE INTERNATIONAL CONFERENCE ON COMPUTER AND COMMUNICATIONS (ICCC), 2017, : 2045 - 2049