Literature DB >> 25543288

Geoherbalism evaluation of Radix Angelica sinensis based on electronic nose.

Sihao Zheng1, Weiguang Ren2, Linfang Huang3.   

Abstract

Radix Angelica sinensis (Danggui, DG), derived from the dry root of Angelicae sinensis, is popularly used for its antioxidant, hematinic and immuno-enhancement. However, DG from different origins possess different quality, and difficult to identity. In this study, we used electronic nose technique to investigate DG from different producing areas for monitoring the correlation of origin and quality. The electronic nose was employed to establish classification model of DG originated from four main producing areas of Gansu, Yunnan, Sichuan and Hubei in China. Principal component analysis (PCA) and discriminant function analysis (DFA) were performed to differentiate DG samples from four main producing areas. The content of phthalides of DG were determined to confirm the quality changes and investigate its correlation with the odor response values by Gas Chromatography-Mass Spectrometer (GC-MS). The results of PCA and DFA analysis showed that the electronic nose could accurately distinguish DG from four main producing areas. The method of electronic nose for identification could be verified by GC-MS technology, and the main ingredient content was consistent with its odor of DG. In conclusion, electronic nose could effectively identify different origins of DG, and could be applied for rapid identification and quality control of genuine Angelica herbs.
Copyright © 2014 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Electronic nose; Geoherbalism; Identification; Radix Angelicae Sinensis

Mesh:

Substances:

Year:  2014        PMID: 25543288     DOI: 10.1016/j.jpba.2014.10.033

Source DB:  PubMed          Journal:  J Pharm Biomed Anal        ISSN: 0731-7085            Impact factor:   3.935


  9 in total

1.  A Novel Feature Extraction Approach Using Window Function Capturing and QPSO-SVM for Enhancing Electronic Nose Performance.

Authors:  Xiuzhen Guo; Chao Peng; Songlin Zhang; Jia Yan; Shukai Duan; Lidan Wang; Pengfei Jia; Fengchun Tian
Journal:  Sensors (Basel)       Date:  2015-06-29       Impact factor: 3.576

2.  A Novel Semi-Supervised Electronic Nose Learning Technique: M-Training.

Authors:  Pengfei Jia; Tailai Huang; Shukai Duan; Lingpu Ge; Jia Yan; Lidan Wang
Journal:  Sensors (Basel)       Date:  2016-03-14       Impact factor: 3.576

3.  Effects of Angelica Extract on Schwann Cell Proliferation and Expressions of Related Proteins.

Authors:  Xiaowen Jiang; Lin Liu; Binqing Zhang; Ziyin Lu; Lu Qiao; Xinxin Feng; Wenhui Yu
Journal:  Evid Based Complement Alternat Med       Date:  2017-07-18       Impact factor: 2.629

4.  Identification of the raw and processed Crataegi Fructus based on the electronic nose coupled with chemometric methods.

Authors:  Chenghao Fei; Chenchen Ren; Yulin Wang; Lin Li; Weidong Li; Fangzhou Yin; Tulin Lu; Wu Yin
Journal:  Sci Rep       Date:  2021-01-20       Impact factor: 4.379

5.  Determination of the geographical origin of Tetrastigma hemsleyanum Diels & Gilg using an electronic nose technique with multiple algorithms.

Authors:  Zhizhuang Wu; Xiaodan Ye; Fangyuan Bian; Ganglei Yu; Guibing Gao; Jiande Ou; Yukui Wang; Yueqiao Li; Xuhua Du
Journal:  Heliyon       Date:  2022-09-28

6.  A Novel Semi-Supervised Method of Electronic Nose for Indoor Pollution Detection Trained by M-S4VMs.

Authors:  Tailai Huang; Pengfei Jia; Peilin He; Shukai Duan; Jia Yan; Lidan Wang
Journal:  Sensors (Basel)       Date:  2016-09-10       Impact factor: 3.576

7.  The Scientific Basis and Advantage of Human Experiential Assessment in the quality control of Chinese Herbal Medicines exampling as Schisandrae Chinensis Fructus.

Authors:  Yongfeng Zhou; Dingkun Zhang; Haotian Li; Haizhu Zhang; Jixiang Fang; Yanqin Ma; Ping Zhang; Jiabo Wang; Xiaohe Xiao
Journal:  Sci Rep       Date:  2018-04-09       Impact factor: 4.379

8.  Is it possible to rapidly and noninvasively identify different plants from Asteraceae using electronic nose with multiple mathematical algorithms?

Authors:  Hui-Qin Zou; Gang Lu; Yong Liu; Rudolf Bauer; Ou Tao; Jian-Ting Gong; Li-Ying Zhao; Jia-Hui Li; Zhi-Yu Ren; Yong-Hong Yan
Journal:  J Food Drug Anal       Date:  2015-08-01       Impact factor: 6.157

9.  Quality grade classification of China commercial moxa floss using electronic nose: A supervised learning approach.

Authors:  Min Yee Lim; Jian Huang; Fu-Rong He; Bai-Xiao Zhao; Hui-Qin Zou; Yong-Hong Yan; Hui Hu; Dong-Sheng Qiu; Jun-Jie Xie
Journal:  Medicine (Baltimore)       Date:  2020-08-14       Impact factor: 1.817

  9 in total

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