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A fast variable selection method for quantitative analysis of soils using laser-induced breakdown spectroscopy

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Abstract

Variable selection is widely utilized in spectral data analysis. However, for the quantitative analysis of laser-induced breakdown spectroscopy (LIBS), conventional variable selection methods could be inapplicable due to too many dense and informative variables leading to unreliable modeling and a bad explanation effect. To solve this problem, we propose a fast variable selection method combining interval partial least squares (iPLS) and modified iterative predictor weighting-partial least squares (mIPW-PLS) and apply it to the LIBS quantitative analysis of soils. Our method is validated by detecting the concentrations of Cu, Ba, Cr, Mg and Ca in different kinds of soil samples. The results demonstrate that variables with maximal relevance were selected effectively and efficiently. Compared with other methods, our method establishes a more simplified model with high accuracy and robustness as well as improved predictive ability. The number of variables used for calculation was reduced significantly. The root mean square error of prediction (RMSEP) and the R2 of prediction showed more satisfactory results compared with conventional methods. The limits of detection (LODs) obtained for Cu, Ba, Cr, Mg and Ca were 11.4, 4.3, 3.6, 529.5 and 307.6 mg kg−1.

Graphical abstract: A fast variable selection method for quantitative analysis of soils using laser-induced breakdown spectroscopy

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Publication details

The article was received on 29 Mar 2017, accepted on 25 Apr 2017 and first published on 25 Apr 2017


Article type: Paper
DOI: 10.1039/C7JA00114B
Citation: J. Anal. At. Spectrom., 2017, Advance Article
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    A fast variable selection method for quantitative analysis of soils using laser-induced breakdown spectroscopy

    X. Fu, F. Duan, T. Huang, L. Ma, J. Jiang and Y. Li, J. Anal. At. Spectrom., 2017, Advance Article , DOI: 10.1039/C7JA00114B

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