A New Plant Indicator (Artemisia lavandulaefolia DC.)‎ of Mercury in Soil Developed by Fourier-Transform Near-Infrared Spectroscopy Coupled with Least Squares Support Vector Machine

Joint Authors

Xu, Lu
Tang, Bang-Cheng
Shi, Qiong
Xie, Shunping

Source

Journal of Analytical Methods in Chemistry

Issue

Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-6, 6 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2019-09-09

Country of Publication

Egypt

No. of Pages

6

Main Subjects

Chemistry

Abstract EN

A rapid indicator of mercury in soil using a plant (Artemisia lavandulaefolia DC., ALDC) commonly distributed in mercury mining area was established by fusion of Fourier-transform near-infrared (FT-NIR) spectroscopy coupled with least squares support vector machine (LS-SVM).

The representative samples of ALDC (stem and leaf) were gathered from the surrounding and distant areas of the mercury mines.

As a reference method, the total mercury contents in soil and ALDC samples were determined by a direct mercury analyzer incorporating high-temperature decomposition, catalytic adsorption for impurity removal, amalgamation capture, and atomic absorption spectrometry (AAS).

Based on the FT-NIR data of ALDC samples, LS-SVM models were established to distinguish mercury-contaminated and ordinary soil.

The results of reference analysis showed that the mercury level of the areas surrounding mercury mines (0–3 kilometers, 7.52–88.59 mg/kg) was significantly higher than that of the areas distant from mercury mines (>5 kilometers, 0–0.75 mg/kg).

The LS-SVM classification model of ALDC samples was established based on the original spectra, smoothed spectra, second-derivative (D2) spectra, and standard normal transformation (SNV) spectra, respectively.

The prediction accuracy of D2-LS-SVM was the highest (0.950).

FT-NIR combined with LS-SVM modeling can quickly and accurately identify the contaminated ALDC.

Compared with traditional methods which rely on naked eye observation of plants, this method is objective and more sensitive and applicable.

American Psychological Association (APA)

Xu, Lu& Shi, Qiong& Tang, Bang-Cheng& Xie, Shunping. 2019. A New Plant Indicator (Artemisia lavandulaefolia DC.) of Mercury in Soil Developed by Fourier-Transform Near-Infrared Spectroscopy Coupled with Least Squares Support Vector Machine. Journal of Analytical Methods in Chemistry،Vol. 2019, no. 2019, pp.1-6.
https://search.emarefa.net/detail/BIM-1169115

Modern Language Association (MLA)

Xu, Lu…[et al.]. A New Plant Indicator (Artemisia lavandulaefolia DC.) of Mercury in Soil Developed by Fourier-Transform Near-Infrared Spectroscopy Coupled with Least Squares Support Vector Machine. Journal of Analytical Methods in Chemistry No. 2019 (2019), pp.1-6.
https://search.emarefa.net/detail/BIM-1169115

American Medical Association (AMA)

Xu, Lu& Shi, Qiong& Tang, Bang-Cheng& Xie, Shunping. A New Plant Indicator (Artemisia lavandulaefolia DC.) of Mercury in Soil Developed by Fourier-Transform Near-Infrared Spectroscopy Coupled with Least Squares Support Vector Machine. Journal of Analytical Methods in Chemistry. 2019. Vol. 2019, no. 2019, pp.1-6.
https://search.emarefa.net/detail/BIM-1169115

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1169115