The classification of plants by laser-induced breakdown spectroscopy based on two chemometric methods

Zhongqi FENG (冯中琦); Dacheng ZHANG (张大成); Bowen WANG (王博文); Jie DING (丁捷); Xuyang LIU (刘旭阳); Jiangfeng ZHU (朱江峰)

doi:10.1088/2058-6272/ab84ed

Plasma Science and Technology > 2020 > 22(7): 74012-074012. > DOI: 10.1088/2058-6272/ab84ed

Zhongqi FENG (冯中琦), Dacheng ZHANG (张大成), Bowen WANG (王博文), Jie DING (丁捷), Xuyang LIU (刘旭阳), Jiangfeng ZHU (朱江峰). The classification of plants by laser-induced breakdown spectroscopy based on two chemometric methods[J]. Plasma Science and Technology, 2020, 22(7): 74012-074012. DOI: 10.1088/2058-6272/ab84ed

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The classification of plants by laser-induced breakdown spectroscopy based on two chemometric methods

School of Physics and Optoelectronic Engineering, Xidian University, Xi'an 710071, People's Republic of China

Funds: This work was supported by the Fundamental Research Funds for the Central Universities of Ministry of Education of China (No. JB190501), Science and Technology Innovation Team of Shaanxi Province (No. 2019TD-002) and National Natural Science Foundation of China (No. 11774277).

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Received Date: December 28, 2019
Revised Date: March 23, 2020
Accepted Date: March 25, 2020

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Abstract

Abstract

The applications of laser-induced breakdown spectroscopy (LIBS) on classifying complex natural organics are relatively limited and their accuracy still requires improvement. In this work, to study the methods on classification of complex organics, three kinds of fresh leaves were measured by LIBS. 100 spectra from 100 samples of each kind of leaves were measured and then they were divided into a training set and a test set in a ratio of 7:3. Two algorithms of chemometric methods including the partial least squares discriminant analysis (PLS-DA) and principal component analysis Mahalanobis distance (PCA-MD) were used to identify these leaves. By using 23 lines from 16 elements or molecules as input data, these two methods can both classify these three kinds of leaves successfully. The classification accuracies of training sets are both up to 100% by PCA-MD and PLS-DA. The classification accuracies of the test set are 93.3% by PCA-MD and 97.8% by PLS-DA. It means that PLS-DA is better than PCA-MD in classifying plant leaves. Because the components in PLS-DA process are more suitable for classification than those in PCA-MD process. We think that this work can provide a reference for plant traceability using LIBS.

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References (39)

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The classification of plants by laser-induced breakdown spectroscopy based on two chemometric methods