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

2019 ◽  
Vol 11 (23) ◽  
pp. 3006-3013 ◽  
Author(s):  
Guangmeng Guo ◽  
Guanghui Niu ◽  
Qi Shi ◽  
Qingyu Lin ◽  
Di Tian ◽  
...  
Keyword(s):  
Quantitative Analysis ◽  
Multivariate Regression ◽  
Comprehensive Assessment ◽  
Laser Induced Breakdown Spectroscopy ◽  
Regression Methods ◽  
Breakdown Spectroscopy ◽  
Laser Induced Breakdown

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

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

Sensors ◽  
2020 ◽  
Vol 20 (2) ◽  
pp. 418 ◽  
Author(s):  
Alexander Erler ◽  
Daniel Riebe ◽  
Toralf Beitz ◽  
Hans-Gerd Löhmannsröben ◽  
Robin Gebbers
Keyword(s):  
Precision Agriculture ◽  
Multivariate Regression ◽  
Humus Content ◽  
Laser Induced Breakdown Spectroscopy ◽  
Soil Parameters ◽  
Soil Matrix ◽  
Regression Methods ◽  
Breakdown Spectroscopy ◽  
Laser Induced Breakdown

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.

A NOVEL STRATEGY FOR DIRECT ELEMENTAL DETERMINATION USING LASER-INDUCED BREAKDOWN SPECTROSCOPY: FLUENCE CALIBRATION

2021 ◽  
Author(s):  
Raquel C Machado ◽  
Diego Victor Babos ◽  
Daniel Fernandes Andrade ◽  
Edenir Rodrigues Pereira-Filho
Keyword(s):  
Quantitative Analysis ◽  
Matrix Effects ◽  
Calibration Method ◽  
Laser Induced Breakdown Spectroscopy ◽  
Breakdown Spectroscopy ◽  
Elemental Determination ◽  
Laser Induced Breakdown ◽  
Direct Solid Analysis ◽  
Novel Strategy ◽  
Direct Solid

Quantitative analysis requires several efforts to obtain an adequate calibration method to overcome matrix effects employing direct solid analysis by laser-induced breakdown spectroscopy (LIBS). To this end, in this study,...

Repeatability enhancing method for one-shot LIBS analysis via spectral intensity correction based on probability distribution

2021 ◽  
Author(s):  
Fu Chang ◽  
Jianhong Yang ◽  
Huili Lu ◽  
Haixia Li
Keyword(s):  
Quantitative Analysis ◽  
Probability Distribution ◽  
Spectral Intensity ◽  
Laser Induced Breakdown Spectroscopy ◽  
Breakdown Spectroscopy ◽  
Laser Induced Breakdown ◽  
Multiple Measurements

It is significant to improve the repeatability of quantitative analysis of laser-induced breakdown spectroscopy (LIBS) in one-shot measurement where the skill of averaging is not valid because multiple measurements are...

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

2017 ◽  
Vol 32 (6) ◽  
pp. 1166-1176 ◽  
Author(s):  
Xiao Fu ◽  
Fa-Jie Duan ◽  
Ting-Ting Huang ◽  
Ling Ma ◽  
Jia-Jia Jiang ◽  
...  
Keyword(s):  
Quantitative Analysis ◽  
Variable Selection ◽  
Selection Method ◽  
Laser Induced Breakdown Spectroscopy ◽  
Fast Variable ◽  
Breakdown Spectroscopy ◽  
Variable Selection Method ◽  
Laser Induced Breakdown

A fast variable selection method combining iPLS and mIPW-PLS is proposed to reduce the dimensions of the spectrum for LIBS quantitative analysis.

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