Distinguish <i>Fritillaria cirrhosa</i> and non-<i>Fritillaria cirrhosa</i> using laser-induced breakdown spectroscopy

Kai WEI (魏凯); Xutai CUI (崔旭泰); Geer TENG (腾格尔); Mohammad Nouman KHAN; Qianqian WANG (王茜蒨)

doi:10.1088/2058-6272/ac0969

Plasma Science and Technology > 2021 > 23(8): 85507-085507. > DOI: 10.1088/2058-6272/ac0969

Kai WEI (魏凯), Xutai CUI (崔旭泰), Geer TENG (腾格尔), Mohammad Nouman KHAN, Qianqian WANG (王茜蒨). Distinguish Fritillaria cirrhosa and non-Fritillaria cirrhosa using laser-induced breakdown spectroscopy[J]. Plasma Science and Technology, 2021, 23(8): 85507-085507. DOI: 10.1088/2058-6272/ac0969

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Distinguish Fritillaria cirrhosa and non-Fritillaria cirrhosa using laser-induced breakdown spectroscopy

¹ School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, People's Republic of China
² Key Laboratory of Photonic Information Technology, Ministry of Industry and Information Technology, Beijing Institute of Technology, Beijing 100081, People's Republic of China

Funds: This work is supported by National Natural Science Foundation of China (No. 62075011) and Graduate Technological Innovation Project of Beijing Institute of Technology (No. 2019CX20026).

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Received Date: March 08, 2021
Revised Date: June 06, 2021
Accepted Date: June 07, 2021

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Abstract

Abstract

As traditional Chinese medicines, Fritillaria from different origins are very similar and it is difficult to distinguish them. In this study, the laser-induced breakdown spectroscopy combined with learning vector quantization (LIBS-LVQ) was proposed to distinguish the powdered samples of Fritillaria cirrhosa and non-Fritillaria cirrhosa. We also studied the performance of linear discriminant analysis, and support vector machine on the same data set. Among these three classifiers, LVQ had the highest correct classification rate of 99.17%. The experimental results demonstrated that the LIBS-LVQ model could be used to differentiate the powdered samples of Fritillaria cirrhosa and non-Fritillaria cirrhosa.
- laser-induced breakdown spectroscopy (LIBS),
- learning vector quantization,
- chemometric models,
- robustness of model

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[1]	Wang Y F, Gu Z Y and He C H 2015 Northwest Pharm. J. 30 436 (in Chinese)
[2]	Yang Z F 2001 Chin. J. Chin. Mater. Med. 26 351 (in Chinese)
[3]	Hu G L et al 2005 Chin. J. Pharm. Anal. 25 150 (in Chinese)
[4]	Wang W N et al 2013 Spectrosc. Spect. Anal. 33 2109 (in Chinese)
[5]	Liang X Q et al 2014 Glob. Tradit. Chin. Med. 7 308 (in Chinese)
[6]	Hao D C, Gu X J and Xiao P G 2013 Chin. J. Nat. Med. 11 330 (in Chinese)
[7]	Häkkänen H J and Korppi-Tommola J E I 1995 Appl.Spectrosc. 49 1721
[8]	Lucena P, Vadillo J and Laserna J 1999 Anal. Chem. 71 4385
[9]	Kim T, Lin C T and Yoon Y 1998 J. Phys. Chem. B 102 4284
[10]	Kim H et al 2019 Opt. Laser Technol. 112 117
[11]	Wang Q Q et al 2020 Opt. Laser Technol. 125 106035
[12]	Loebe K, Uhl A and Lucht H 2003 Appl. Opt. 42 6166
[13]	Taschuk M T, Tsui Y Y and Fedosejevs R 2006 Appl.Spectrosc. 60 1322
[14]	Novotný K et al 2008 Spectrochim. Acta B 63 1139
[15]	Ma Q L et al 2010 Spectrochim. Acta B 65 707
[16]	Kaiser J et al 2009 Spectrochim. Acta B 64 67
[17]	Lei W et al 2009 Spectrochim. Acta B 64 891
[18]	Baudelet M et al 2006 Appl. Phys. Lett. 89 163903
[19]	Li X H et al 2018 Opt. Laser Technol. 102 233
[20]	Dong C Z, Yang F and Su M G 2015 J. Northwest Norm. Univ.(Nat. Sci.) 51 44 (in Chinese)
[21]	Liu X N et al 2015 Chin. J. Chin. Mater. Med. 40 2239 (in Chinese)
[22]	Li Z F et al 2016 Infrared Laser Eng. 45 1006003 (in Chinese)
[23]	Li Z F et al 2016 Chin. J. Lumin. 37 100 (in Chinese)
[24]	Shen Y Y and Liu C L 2018 Cogn. Comput. 10 334
[25]	Saeedi E, Kong Y and Hossain M S 2017 Front. Inform.Technol. Electron. Eng. 18 511
[26]	Lloyd G R et al 2007 J. Chem. Inf. Model. 47 1553
[27]	Song K et al 2018 J. Power Sources 389 230
[28]	Andrade D F, Guedes W N and Pereira F M V 2018 Microchem. J. 137 443
[29]	Singh J et al 2017 Food Chem. 221 1778
[30]	Moncayo S et al 2017 Food Chem. 232 322
[31]	Markiewicz-Keszycka M et al 2018 Food Chem. 244 324
[32]	Velioglu H M et al 2018 Meat Sci. 138 28
[33]	Moncayo S et al 2018 J. Anal. At. Spectrom. 33 210
[34]	Chen T B et al 2019 J. Anal. At. Spectrom. 34 884
[35]	Chatterjee S et al 2019 Anal. Bioanal. Chem. 411 2855
[36]	Moncayo S et al 2015 Chemometr. Intell. Lab. 146 354
[37]	Vors E, Tchepidjian K and Sirven J B 2016 Spectrochim. Acta B 117 16

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1.	Akash, R., Sarathi, R., Haddad, M. Pollution Monitoring on Polymeric Insulators Adopting Laser-Induced Breakdown Spectroscopy, Computer Vision, and Machine Learning Techniques. IEEE Transactions on Plasma Science, 2025. DOI:10.1109/TPS.2025.3539261
2.	Zhang, R., Hu, S., Ma, C. et al. Laser-induced breakdown spectroscopy (LIBS) in biomedical analysis. TrAC - Trends in Analytical Chemistry, 2024. DOI:10.1016/j.trac.2024.117992
3.	Yin, R., Qiao, Y., Wang, J. et al. Precise Testing Technology of Aluminum Based on SAF-LIBS Theory \| [基于 SAF-LIBS 理论的铝精密检测技术研究]. Zhongguo Jiguang/Chinese Journal of Lasers, 2024, 51(17): 1711001. DOI:10.3788/CJL231557
4.	Xie, W., Fu, G., Xu, J. et al. Evaluation of Sample Preparation Methods for the Classification of Children’s Ca–Fe–Zn Oral Liquid by Libs. Journal of Applied Spectroscopy, 2024, 91(1): 209-217. DOI:10.1007/s10812-024-01708-w
5.	Zhou, F., Xie, W., Lin, M. et al. Rapid authentication of geographical origins of Baishao (Radix Paeoniae Alba) slices with laser-induced breakdown spectroscopy based on conventional machine learning and deep learning. Spectrochimica Acta - Part B Atomic Spectroscopy, 2024. DOI:10.1016/j.sab.2023.106852
6.	Peng, J., Lin, M., Xie, W. et al. Fast identification of geographical origins of Baishao (Radix Paeoniae Alba) using the deep fusion of LIBS spectrum and ablation image. Microchemical Journal, 2023. DOI:10.1016/j.microc.2023.109337
7.	Wei, K., Teng, G., Wang, Q. et al. Rapid Test for Adulteration of Fritillaria Thunbergii in Fritillaria Cirrhosa by Laser-Induced Breakdown Spectroscopy. Foods, 2023, 12(8): 1710. DOI:10.3390/foods12081710
8.	Wei, K., Wang, Q., Teng, G. et al. Application of Laser-Induced Breakdown Spectroscopy Combined with Chemometrics for Identification of Penicillin Manufacturers. Applied Sciences (Switzerland), 2022, 12(10): 4981. DOI:10.3390/app12104981
9.	Hu, M., Ma, F., Li, Z. et al. Sensing of Soil Organic Matter Using Laser-Induced Breakdown Spectroscopy Coupled with Optimized Self-Adaptive Calibration Strategy. Sensors, 2022, 22(4): 1488. DOI:10.3390/s22041488

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Distinguish Fritillaria cirrhosa and non-Fritillaria cirrhosa using laser-induced breakdown spectroscopy

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