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Journal of Applied Spectroscopy

, Volume 85, Issue 1, pp 190–196 | Cite as

Quantitative Analysis of Ca, Mg, and K in the Roots of Angelica pubescens f. biserrata by Laser-Induced Breakdown Spectroscopy Combined with Artificial Neural Networks

  • J. Wang
  • M. Shi
  • P. Zheng
  • Sh. Xue
  • R. Peng
Article

Laser-induced breakdown spectroscopy has been applied for the quantitative analysis of Ca, Mg, and K in the roots of Angelica pubescens Maxim. f. biserrata Shan et Yuan used in traditional Chinese medicine. Ca II 317.993 nm, Mg I 517.268 nm, and K I 769.896 nm spectral lines have been chosen to set up calibration models for the analysis using the external standard and artificial neural network methods. The linear correlation coefficients of the predicted concentrations versus the standard concentrations of six samples determined by the artificial neural network method are 0.9896, 0.9945, and 0.9911 for Ca, Mg, and K, respectively, which are better than for the external standard method. The artificial neural network method also gives better performance comparing with the external standard method for the average and maximum relative errors, average relative standard deviations, and most maximum relative standard deviations of the predicted concentrations of Ca, Mg, and K in the six samples. Finally, it is proved that the artificial neural network method gives better performance compared to the external standard method for the quantitative analysis of Ca, Mg, and K in the roots of Angelica pubescens.

Keywords

laser-induced breakdown spectroscopy roots of Angelica pubescens artifi cial neural networks quantitative analysis 

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© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Chongqing Municipal Level Key Laboratory of Photoelectronic Information Sensing and Transmitting Technology, College of Optoelectronic EngineeringChongqing University of Posts; and TelecommunicationsChongqingChina
  2. 2.Chongqing Academy of Chinese MedicineChongqingChina

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