Classification of Chinese Herbal Medicine by Laser-Induced Breakdown Spectroscopy with Principal Component Analysis and Artificial Neural Network-Reference-Cited by-同舟云学术

Classification of Chinese Herbal Medicine by Laser-Induced Breakdown Spectroscopy with Principal Component Analysis and Artificial Neural Network

Published:2017-11-15 Issue:4 Volume:51 Page:575-586
ISSN:0003-2719
Container-title:Analytical Letters
language:en
Short-container-title:Analytical Letters

Author:

Wang Jinmei¹,Liao Xiangyu¹,Zheng Peichao¹,Xue Shuwen¹,Peng Rui²

Affiliation:

1. Chongqing Municipal Level Key Laboratory of Photoelectronic Information Sensing and Transmitting Technology, College of Optoelectronic Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China

2. Chongqing Academy of Chinese Medicine, Chongqing, China

Funder

the Scientific Research Foundation for Returned Overseas Chinese Scholars, Foundation and Advanced Technology Research Project of Chongqing

the Doctor fund of CQUPT

the Key Project of Foundation and Advanced Technology Research Project of Chongqing

the Science Research Funds of Chongqing Municipal Education Commission

Publisher

Informa UK Limited

Subject

Electrochemistry,Biochemistry (medical),Clinical Biochemistry,Spectroscopy,Biochemistry,Analytical Chemistry

Link

https://www.tandfonline.com/doi/pdf/10.1080/00032719.2017.1340949

Reference32 articles.

1. Aromatic Herbal Products Analysis by Laser-Induced Breakdown Spectroscopy

2. Analysis of Roman-Hispanic Archaeological Ceramics using Laser-Induced Breakdown Spectroscopy

3. Qualitative analysis of a sulfur-fumigated Chinese herbal medicine by comprehensive two-dimensional gas chromatography and high-resolution time of flight mass spectrometry using colorized fuzzy difference data processing

4. Comprehensive determination of polycyclic aromatic hydrocarbons in Chinese herbal medicines by solid phase extraction and gas chromatography coupled to tandem mass spectrometry

5. Rapid analysis of energetic and geo-materials using LIBS

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