Multi-element quantitative analysis of soils by laser induced breakdown spectroscopy (LIBS) coupled with univariate and multivariate regression methods

Guo, Gaofeng; Niu, Guanghui; Shi, Qi; Lin, Qingyu; Tian, Di; Duan, Yixiang

doi:10.1039/c9ay00890j

Cited by 59 publications

(40 citation statements)

References 39 publications

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“…Multivariate analysis is commonly used in the analysis of complex spectra [28][29][30]. This technique numerically estimates how multiple independent input variables interact to produce the dependent response; this can result in a fit with less statistical uncertainty than a univariate calibration [31].…”

Section: Multivariate Analysismentioning

confidence: 99%

Quantitative Analysis of Cerium-Gallium Alloys Using a Hand-Held Laser Induced Breakdown Spectroscopy Device

Rao

Cook

Hall

et al. 2019

Atoms

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A hand-held laser-induced breakdown spectroscopy device was used to acquire spectral emission data from laser-induced plasmas created on the surface of cerium-gallium alloy samples with Ga concentrations ranging from 0–3 weight percent. Ionic and neutral emission lines of the two constituent elements were then extracted and used to generate calibration curves relating the emission line intensity ratios to the gallium concentration of the alloy. The Ga I 287.4-nm emission line was determined to be superior for the purposes of Ga detection and concentration determination. A limit of detection below 0.25% was achieved using a multivariate regression model of the Ga I 287.4-nm line ratio versus two separate Ce II emission lines. This LOD is considered a conservative estimation of the technique’s capability given the type of the calibration samples available and the low power (5 mJ per 1-ns pulse) and resolving power ( λ / Δ λ = 4000) of this hand-held device. Nonetheless, the utility of the technique is demonstrated via a detailed mapping analysis of the surface Ga distribution of a Ce-Ga sample, which reveals significant heterogeneity resulting from the sample production process.

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Section: Multivariate Analysismentioning

confidence: 99%

Quantitative Analysis of Cerium-Gallium Alloys Using a Hand-Held Laser Induced Breakdown Spectroscopy Device

Rao

Cook

Hall

et al. 2019

Atoms

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show abstract

“…Multivariate analysis is a common in the analysis of complex spectra [28][29][30]. This technique numerically estimates how multiple independent input variables interact to produce the dependent response; this can result in a fit with less statistical uncertainty than a univariate calibration [31].…”

Section: Multivariate Analysismentioning

confidence: 99%

Quantitative Analysis of Cerium-Gallium Alloys Using a Hand-Held Laser Induced Breakdown Spectroscopy Device

Rao¹,

Cook²,

Hall³

et al. 2019

Preprint

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A hand-held laser-induced breakdown spectroscopy device was used to acquire spectral emission data from laser-induced plasmas created on the surface of cerium-gallium alloy samples with Ga concentrations ranging from 0 to 3 weight percent. Ionic and neutral emission lines of the two constituent elements were then extracted and used to generate calibration curves relating the emission line intensity ratios to the gallium concentration of the alloy. The Ga I 287.4 nm emission line was determined to be superior for the purposes of Ga detection and concentration determination. A limit of detection below 0.25% was achieved using a multivariate regression model of the Ga I 287.4 nm line ratio versus two separate Ce II emission lines. This LOD is considered a conservative estimation of technique's capability given the type of the calibration samples available and low power (5 mJ per 1 ns pulse) and resolving power (λ/∆λ = 4000) of this handheld device. Nonetheless, the utility of the technique is demonstrated via a detailed mapping analysis of the surface Ga distribution of a Ce-Ga sample which reveals significant heterogeneity resulting from the sample production process.

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“…While publications on large-scale field mapping by LIBS are scarce [19], the detection of soil nutrients in the laboratory has already been demonstrated in a series of publications [20]. For example, in a study by Guo et al, 13 different elements in 17 different standard soils were determined by LIBS applying PLSR and SVR [21]. Single pulse and double pulse LIBS were compared at the determination of K, Ca, Mg, Fe, Na and Mn in 63 soil samples applying PLSR and SVR [22].…”

Section: Introductionmentioning

confidence: 99%

“…These investigations started with univariate analysis of the total carbon content using the two C lines at 193 nm [26,27] and 247.9 nm [28]. Later, multivariate methods such as PLSR [29][30][31], Lasso and multivariate regression with covariance estimation [15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30][31][32] were applied, which also allowed the differentiation of inorganic and organic C. Multivariate approaches were also used to determine further soil parameters such as soil pH [33].…”

Section: Introductionmentioning

confidence: 99%

Soil Nutrient Detection for Precision Agriculture Using Handheld Laser-Induced Breakdown Spectroscopy (LIBS) and Multivariate Regression Methods (PLSR, Lasso and GPR)

Erler

Riebe

Beitz

et al. 2020

Sensors

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Precision agriculture (PA) strongly relies on spatially differentiated sensor information. Handheld instruments based on laser-induced breakdown spectroscopy (LIBS) are a promising sensor technique for the in-field determination of various soil parameters. In this work, the potential of handheld LIBS for the determination of the total mass fractions of the major nutrients Ca, K, Mg, N, P and the trace nutrients Mn, Fe was evaluated. Additionally, other soil parameters, such as humus content, soil pH value and plant available P content, were determined. Since the quantification of nutrients by LIBS depends strongly on the soil matrix, various multivariate regression methods were used for calibration and prediction. These include partial least squares regression (PLSR), least absolute shrinkage and selection operator regression (Lasso), and Gaussian process regression (GPR). The best prediction results were obtained for Ca, K, Mg and Fe. The coefficients of determination obtained for other nutrients were smaller. This is due to much lower concentrations in the case of Mn, while the low number of lines and very weak intensities are the reason for the deviation of N and P. Soil parameters that are not directly related to one element, such as pH, could also be predicted. Lasso and GPR yielded slightly better results than PLSR. Additionally, several methods of data pretreatment were investigated.

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Multi-element quantitative analysis of soils by laser induced breakdown spectroscopy (LIBS) coupled with univariate and multivariate regression methods

Abstract: A comprehensive assessment of soils was developed using laser induced breakdown spectroscopy (LIBS) coupled with univariate and multivariate regression methods.

Cited by 59 publications

References 39 publications

Quantitative Analysis of Cerium-Gallium Alloys Using a Hand-Held Laser Induced Breakdown Spectroscopy Device

Quantitative Analysis of Cerium-Gallium Alloys Using a Hand-Held Laser Induced Breakdown Spectroscopy Device

Quantitative Analysis of Cerium-Gallium Alloys Using a Hand-Held Laser Induced Breakdown Spectroscopy Device

Soil Nutrient Detection for Precision Agriculture Using Handheld Laser-Induced Breakdown Spectroscopy (LIBS) and Multivariate Regression Methods (PLSR, Lasso and GPR)

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