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.
Article PDF
Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.Avoid common mistakes on your manuscript.
References
T. Fujioka, K. H. Furumi, and H. Okabe, Chem. Pharm. Bull., 47, 96–100 (1999).
M. Senila, A. Drolc, and A. Pintar, J . Anal. Sci. Technol., 5, 1–9 (2014).
X. D. Yuan, K. H. Ling, and C. W. Keung, Phytochem. Anal., 20, 293–297 (2009).
S. Arpadjan, G. Çelik, and S. Taşkesen, Food Chem. Toxicol., 46, 2871–2875 (2008).
P. C. Zheng, H. D. Liu, and J. M. Wang, Anal. Methods, 6, 2163–2169 (2014).
S. Kashiwakura and K. Wagatsuma, Anal. Sci., 29, 1159–1164 (2013).
B. Chen, H. Kano, and M. Kuzuya. Anal. Sci., 24, 289–291 (2008).
M. Y. Yao, L. Huang, and J. Zheng, Opt. Laser Technol., 52, 70–74 (2013).
L. Huang, M. Y. Yao, and J. L. Lin, J. Appl. Spectrosc., 80, 957–961 (2014).
P. C. Zheng, H. D. Liu, and J. M. Wang, J. An al. At. Spectrom., 30, 867–874 (2015).
Y. Li, Y. Lu, and R. E. Zheng, Spect rosc. & Spectr. Anal., 32, 582–585 (2012).
M. Yao, J. Lin, and M. Liu, Appl. Opt., 51, 1552–1557 (2012).
L. Huang, M. Yao, Y. Xu, and M. Liu, Appl. Phys. B, 111, 45–51 (2013).
D. Zhu, J. Chen, and J. Lu, Anal. Methods, 4, 819–823 (2012).
Y. Cai, P. C. Chu, and S. K. Ho, Front . Phys., 7, 670–678 (2012).
Y. Wang, W. L. Liu, and Y. F. Song, Chem. Phys., 447, 30–35 (2015).
E. Jobiliong, H. Suyanto, and A. M. Marpaung, J. Appl. Spectrosc., 69, 115–123 (2015).
Y. Zhang, G. Xiong, and S. Li, Combust. Flame, 160, 725–733 (2013).
Y. Yuan, S. Li, and Q. Yao, Proc. Combust. Inst., 35, 2339–2346 (2015).
Y. Zhang, S. Li, Y. Ren, and Q. Yao, Proc. Combust. Inst., 35, 3681–3688 (2015).
E. C. Ferreira, D. M. Milori, and E. J. Ferreira, Spectrochim. Acta, B, 63, 1216–1220 (2008).
P. Inakollu, T. Philip, and A. K. Rai, Spectrochim. Acta, B, 64, 99–104 (2009).
L. X. Sun, H. B. Yu, and Z. B. Cong, Acta Opt. Sin., 30, 2757–2765 (2010).
V. Motto-Ros, A. S. Koujelev, and G. R. Osinski, J. Europ. Opt. Soc. Rapid Publ., 3, 08011 (2008).
S. Y. Oh, F. Y. Yueh, and J. P. Singh, Appl. Opt., 49, C36–C41 (2010).
P. C. Zheng, M. J. Shi, and J. M. Wang, Plasma Sci. Technol, 17, 664–670 (2015).
J. B. Sirven, B. Bousquet, and L. Canioni, Anal. Bioanal.Chem., 385, 256–262 (2006).
R. Beale and T. Jackson, Neural Computing – An Introduction, CRC Press, Florida, USA (1990).
Author information
Authors and Affiliations
Corresponding author
Additional information
Abstract of article is published in Zhurnal Prikladnoi Spektroskopii, Vol. 85, No. 1, p. 175, January–February, 2018.
Rights and permissions
About this article
Cite this article
Wang, J., Shi, M., Zheng, P. et al. 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 Appl Spectrosc 85, 190–196 (2018). https://doi.org/10.1007/s10812-018-0631-7
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10812-018-0631-7