Accuracy enhancement of a multivariate calibration for lead determination in soils by laser induced breakdown spectroscopy

Krylov, I.N.; Popov, A. M.; Зоров, Н. Б.; Лабутин, Т.А.

doi:10.1016/j.sab.2017.12.005

Cited by 40 publications

(21 citation statements)

References 29 publications

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“…The "matrix effects" are caused by changes in the emission line intensities of some elements in samples when the physical properties and the chemical composition of the matrix vary [46]. Previous studies have indicated that chemometrics and multivariate methods involving spectral preprocessing and calibration are efficient at reducing the "matrix effects" when applying LIBS to the determination of elements [47,48]. However, there are only a few studies combining chemometrics and LIBS for the measurements of soil properties, especially for soil nutrients.…”

Section: Introductionmentioning

confidence: 99%

Fast and Simultaneous Determination of Soil Properties Using Laser-Induced Breakdown Spectroscopy (LIBS): A Case Study of Typical Farmland Soils in China

et al. 2019

Soil Systems

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Accurate management of soil nutrients and fast and simultaneous acquisition of soil properties are crucial in the development of sustainable agriculture. However, the conventional methods of soil analysis are generally labor-intensive, environmentally unfriendly, as well as time- and cost-consuming. Laser-induced breakdown spectroscopy (LIBS) is a “superstar” technique that has yielded outstanding results in the elemental analysis of a wide range of materials. However, its application for analysis of farmland soil faces the challenges of matrix effects, lack of large-scale soil samples with distinct origin and nature, and problems with simultaneous determination of multiple soil properties. Therefore, LIBS technique, in combination with partial least squares regression (PLSR), was applied to simultaneously determinate soil pH, cation exchange capacity (CEC), soil organic matter (SOM), total nitrogen (TN), total phosphorus (TP), total potassium (TK), available phosphorus (AP), and available potassium (AK) in 200 soils from different farmlands in China. The prediction performances of full spectra and characteristic lines were evaluated and compared. Based on full spectra, the estimates of pH, CEC, SOM, TN, and TK achieved excellent prediction abilities with the residual prediction deviation (RPDV) values > 2.0 and the estimate of TP featured good performance with RPDV value of 1.993. However, using characteristic lines only improved the predicted accuracy of SOM, but reduced the prediction accuracies of TN, TP, and TK. In addition, soil AP and AK were predicted poorly with RPDV values of < 1.4 based on both full spectra and characteristic lines. The weak correlations between conventionally analyzed soil AP and AK and soil LIBS spectra are responsible for the poor prediction abilities of AP and AK contents. Findings from this study demonstrated that the LIBS technique combined with multivariate methods is a promising alternative for fast and simultaneous detection of some properties (i.e., pH and CEC) and nutrient contents (i.e., SOM, TN, TP, and TK) in farmland soils because of the extraordinary prediction performances achieved for these attributes.

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Section: Introductionmentioning

confidence: 99%

Fast and Simultaneous Determination of Soil Properties Using Laser-Induced Breakdown Spectroscopy (LIBS): A Case Study of Typical Farmland Soils in China

et al. 2019

Soil Systems

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“…Matrix effects can have different sources, including the laser-to-sample coupling, collisional interactions within the plasma, or the plasma temperature, which influences the ratio of neutral and ionized species. These matrix effects and spectral interferences were already investigated for Pb determined in different types of soil [11]. The study demonstrated that spectral interferences from main components (Ca, Fe, Ti, Mg) and trace components (Mn, Nb, Zr) were a reason for significant differences between the univariate calibration models.…”

Section: Introductionmentioning

confidence: 86%

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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“…Measurements in low resolution mode on FCs with 10 11 Ω resistors. Simultaneous measurements of 177 Hf + , 181 Ta + and 188 Os + were used to correct for isobaric interferences from 180 Hf + , 180 Ta + , 184 Os + and 186 Os + , respectively, by applying published relative isotope abundance data. After correction for mass-dependent fractionation using the double spike approach, results were expressed relative to NIST SRM 3163.…”

Section: Mc-icp-msmentioning

confidence: 99%

Atomic Spectrometry Update – a review of advances in environmental analysis

Bacon

Butler

Cairns

et al. 2019

J. Anal. At. Spectrom.

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Accuracy enhancement of a multivariate calibration for lead determination in soils by laser induced breakdown spectroscopy

Cited by 40 publications

References 29 publications

Fast and Simultaneous Determination of Soil Properties Using Laser-Induced Breakdown Spectroscopy (LIBS): A Case Study of Typical Farmland Soils in China

Fast and Simultaneous Determination of Soil Properties Using Laser-Induced Breakdown Spectroscopy (LIBS): A Case Study of Typical Farmland Soils in China

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

Atomic Spectrometry Update – a review of advances in environmental analysis

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