Comparison of two laser-induced breakdown spectroscopy techniques for total carbon measurement in soils

Belkov, M. V.; Бураков, В. С.; Giacomo, A. De; Kiris, V. V.; Raikov, S. N.; Тарасенко, Н. В.

doi:10.1016/j.sab.2009.07.019

Cited by 58 publications

(40 citation statements)

References 27 publications

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“…Martin et al (2010) reported full cross-validation accuracy for a LIBS PLS1 TC calibration (SEP = 3.1g C kg -1 ) using soil samples from a single soil series in each of three states-not a geographically independent validation given that the samples were not selected to be geographically independent (Brown et al, 2005;Brown et al, 2006;Dardenne et al, 2000). Lastly, Belkov et al (2009) calibrated combined-and double-pulse LIBS to "homemade certified standards", then In this study, the research team was not able to explain SOC variance using LIBS (r 2 = 0.22, RPD = 1.1) even though the LIBS prediction error (SEP) for SOC was less than that for TC and IC (Table 3). Assuming a constant prediction error, r 2 and RPD will both increase with greater variation in the target variable.…”

Section: Discussionmentioning

confidence: 99%

Cropland Field Monitoring: MMV Page 1 Montana Cropland Enrolled Farm Fields Carbon Sequestration Field Sampling, Measurement, Monitoring, and Verification: Application of Visible-Near Infrared Diffuse Reflectance Spectroscopy (VNIR) and Laser-induced Breakdown Spectroscopy (LIBS)

Spangler¹,

Bricklemyer²,

Brown³

2012

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Brown. 2010. On-the-go VisNIR: Potential and limitations for mapping soil clay and organic carbon. Comput. Electron. . AbstractIn situ or on-the-go visible and near infrared (VisNIR) diffuse reflectance spectroscopy has been proposed as a rapid and inexpensive tool for intensively mapping soil texture and organic carbon (SOC). While lab-based VisNIR has been established as a viable technique for estimating various soil properties, few experiments have compared the predictive accuracy of on-the-go and lab-based VisNIR. In this study, eight north central Montana wheat fields were intensively interrogated using on-the-go and lab-based VisNIR. The on-the-go VisNIR system employed a spectrophotometer (350-2224 nm, 8-nm spectral resolution) built into an agricultural shank mounted on a toolbar and pulled behind a tractor. Regional (whole-field out cross-validation) and hybrid (regional model including randomly chosen 'local' calibration samples) spectral models were calibrated using partial least squares regression. Lab-based spectral data consistently provided more accurate predictions than on-the-go data. However, neither in situ nor lab-based spectroscopy yielded even semi-quantitative SOC predictions. For hybrid models with 9 local samples included in the calibrations, standard error of prediction (SEP) values were 2.6 and 3.4 g kg -1 for lab and on-the-go VisNIR respectively, with  SOC = 3.2 g kg -1 . With an SOC coefficient of variation (CV) = 26.7%, even with a relatively low SEP values, there was little SOC variability to explain. For clay content, hybrid +7 calibrations yielded lab SEP = 53.1 g kg -1 and residual product differential (RPD) = 1.8 with on-the-go SEP = 69.4 g kg -1 and RPD = 1.4. With more variability ( Clay = 91.4 g kg -1 and CV = 49.6%), both lab and on-the-go VisNIR show better explanatory power. There are a number of potential explanations for degraded onthe-go predictive accuracy: soil heterogeneity, field moisture, consistent sample presentation, and a difference between the spatial support of on-the-go measurements and soil samples collected for laboratory analyses. In terms of predictive accuracy, our results are largely consistent with those previously published by Christy (2008), but on-the-go VisNIR was not able to capture the subtle SOC variability in Montana soils. Though the current configuration of the Veris on-the-go VisNIR system allows for rapid field scanning, on-the-go soil processing (i.e. drying, crushing, and sieving) could improve predictions. 2.1

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Section: Discussionmentioning

confidence: 99%

Cropland Field Monitoring: MMV Page 1 Montana Cropland Enrolled Farm Fields Carbon Sequestration Field Sampling, Measurement, Monitoring, and Verification: Application of Visible-Near Infrared Diffuse Reflectance Spectroscopy (VNIR) and Laser-induced Breakdown Spectroscopy (LIBS)

Spangler¹,

Bricklemyer²,

Brown³

2012

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“…In this work, the LOD achieved for Cr in soil was 46.2 mg/kg. The LOD for LIBS is higher due to relatively low sensitivity of the technique compared to ICP-MS and some other trace metals monitoring techniques [35,45].…”

Section: Limit Of Detectionmentioning

confidence: 99%

“…The application of LIBS to soil [6,[24][25][26][27][33][34][35][36] and sediment [22,37,38] analyses has been of growing interest during the last decade. The LIBS technique has been mainly applied to solve two related problems of soil analysis.…”

Section: Introductionmentioning

confidence: 99%

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Laser-induced breakdown spectroscopy and inductively coupled plasma-mass spectrometry for determination of Cr in soils from Brits District, South Africa

Ambushe¹,

Plessis²,

McCrindle³

2015

Bull. Chem. Soc. Eth.

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ABSTRACT. Laser-induced breakdown spectroscopy (LIBS) is an emerging analytical technique, which can be used to perform elemental analysis of any material, irrespective of its physical state. In this study, the LIBS technique has been applied for quantification of total Cr in soil samples collected from polluted areas of Brits, North West Province, South Africa. A Q-switched neodymium-yttrium aluminium garnet (Nd-YAG) laser (10 Hz, λ = 1064 nm) was employed for generation of a laser-induced plasma on the surface of the soil sample. The atomic emission lines were recorded using an Andor Shamrock SR-303i spectrometer, fitted with an intensified charge-coupled device (ICCD) camera. Detailed investigation of experimental parameters such as gate delay time, gate width and laser pulse energy was conducted. Soil samples were dried, finely ground, sieved and thereafter pelletized before LIBS analysis. Calibration curve for the quantification of Cr was constructed using certified reference materials of soils and sediments. The concentrations of Cr in soil samples varied from 111 to 3180 mg/kg. In order to test the validity of the LIBS results, inductively coupled plasma-mass spectrometry (ICP-MS) was also employed for determination of Cr. The results obtained using LIBS were found to be in good agreement with those of ICP-MS.

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“…They also performed classification by principal components analyses (Sirven et al, 2006). Belkov (Belkov et al, 2009) showed the possibility of measuring the carbon content in 11 soil samples. The calibration curve was fit by an exponential function within 2% to 8% range.…”

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confidence: 99%

Artificial Neural Networks for Material Identification, Mineralogy and Analytical Geochemistry Based on Laser-Induced Breakdown Spectroscopy

Koujelev¹,

Lui²

2011

Artificial Neural Networks - Industrial and Control Engineering Applications

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Comparison of two laser-induced breakdown spectroscopy techniques for total carbon measurement in soils

Cited by 58 publications

References 27 publications

Cropland Field Monitoring: MMV Page 1 Montana Cropland Enrolled Farm Fields Carbon Sequestration Field Sampling, Measurement, Monitoring, and Verification: Application of Visible-Near Infrared Diffuse Reflectance Spectroscopy (VNIR) and Laser-induced Breakdown Spectroscopy (LIBS)

Cropland Field Monitoring: MMV Page 1 Montana Cropland Enrolled Farm Fields Carbon Sequestration Field Sampling, Measurement, Monitoring, and Verification: Application of Visible-Near Infrared Diffuse Reflectance Spectroscopy (VNIR) and Laser-induced Breakdown Spectroscopy (LIBS)

Laser-induced breakdown spectroscopy and inductively coupled plasma-mass spectrometry for determination of Cr in soils from Brits District, South Africa

Artificial Neural Networks for Material Identification, Mineralogy and Analytical Geochemistry Based on Laser-Induced Breakdown Spectroscopy

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