High accuracy analysis of fiber-optic laser-induced breakdown spectroscopy by using multivariate regression analytical methods

2021 ◽  
pp. 106160
Author(s):  
Feng Chen ◽  
Wanjie Lu ◽  
Yanwu Chu ◽  
Deng Zhang ◽  
Cong Guo ◽  
...  
Keyword(s):  
Analytical Methods ◽  
Multivariate Regression ◽  
Fiber Optic ◽  
High Accuracy ◽  
Laser Induced Breakdown Spectroscopy ◽  
Accuracy Analysis ◽  
Breakdown Spectroscopy ◽  
Laser Induced Breakdown

In situ classification of rocks using stand-off laser-induced breakdown spectroscopy with a compact spectrometer

2018 ◽  
Vol 33 (3) ◽  
pp. 461-467 ◽  
Author(s):  
W. T. Li ◽  
Y. N. Zhu ◽  
X. Li ◽  
Z. Q. Hao ◽  
L. B. Guo ◽  
...  
Keyword(s):  
High Accuracy ◽  
Remote Detection ◽  
Laser Induced Breakdown Spectroscopy ◽  
Breakdown Spectroscopy ◽  
Laser Induced Breakdown

The ASPI-LDA algorithm combined with a compact spectrometer to achieve high accuracy classification, which has a great potential for field in situ remote detection.

scholarly journals High-Sensitivity Determination of Nutrient Elements in Panax notoginseng by Laser-induced Breakdown Spectroscopy and Chemometric Methods

Molecules ◽  
2019 ◽  
Vol 24 (8) ◽  
pp. 1525 ◽  
Author(s):  
Tingting Shen ◽  
Weijiao Li ◽  
Xi Zhang ◽  
Wenwen Kong ◽  
Fei Liu ◽  
...  
Keyword(s):  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Least Squares ◽  
Panax Notoginseng ◽  
High Accuracy ◽  
Laser Induced Breakdown Spectroscopy ◽  
Quantitative Detection ◽  
Breakdown Spectroscopy ◽  
Laser Induced Breakdown

High-accuracy and fast detection of nutritive elements in traditional Chinese medicine Panax notoginseng (PN) is beneficial for providing useful assessment of the healthy alimentation and pharmaceutical value of PN herbs. Laser-induced breakdown spectroscopy (LIBS) was applied for high-accuracy and fast quantitative detection of six nutritive elements in PN samples from eight producing areas. More than 20,000 LIBS spectral variables were obtained to show elemental differences in PN samples. Univariate and multivariate calibrations were used to analyze the quantitative relationship between spectral variables and elements. Multivariate calibration based on full spectra and selected variables by the least absolute shrinkage and selection operator (Lasso) weights was used to compare the prediction ability of the partial least-squares regression (PLS), least-squares support vector machines (LS-SVM), and Lasso models. More than 90 emission lines for elements in PN were found and located. Univariate analysis was negatively interfered by matrix effects. For potassium, calcium, magnesium, zinc, and boron, LS-SVM models based on the selected variables obtained the best prediction performance with Rp values of 0.9546, 0.9176, 0.9412, 0.9665, and 0.9569 and root mean squared error of prediction (RMSEP) of 0.7704 mg/g, 0.0712 mg/g, 0.1000 mg/g, 0.0012 mg/g, and 0.0008 mg/g, respectively. For iron, the Lasso model based on full spectra obtained the best result with an Rp value of 0.9348 and RMSEP of 0.0726 mg/g. The results indicated that the LIBS technique coupled with proper multivariate chemometrics could be an accurate and fast method in the determination of PN nutritive elements for traditional Chinese medicine management and pharmaceutical analysis.

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.

Detection of Metals in the Environment Using a Portable Laser-Induced Breakdown Spectroscopy Instrument

1996 ◽  
Vol 50 (2) ◽  
pp. 222-233 ◽  
Author(s):  
Karen Y. Yamamoto ◽  
David A. Cremers ◽  
Monty J. Ferris ◽  
Leeann E. Foster
Keyword(s):  
Detection Limit ◽  
Fiber Optic ◽  
Laser Induced Breakdown Spectroscopy ◽  
Portable Instrument ◽  
Fiber Optic Cable ◽  
Breakdown Spectroscopy ◽  
Ccd Detector ◽  
Sampling Probe ◽  
Laser Induced Breakdown ◽  
Spectrally Resolved

A portable instrument, based on laser-induced breakdown spectroscopy (LIBS), has been developed for the detection of metal contaminants on surfaces. The instrument has a weight of 14.6 kg, fits completely into a small suitcase (46 × 33 × 24 cm), and operates from 115 V ac. The instrument consists of a sampling probe connected to the main analysis unit by electrical and optical cabling. The hand-held probe contains a small laser to generate laser sparks on a surface and a fiber-optic cable to collect the spark light. The collected light is spectrally resolved and detected with the use of a compact spectrograph/CCD detector system. The instrument has been evaluated for the analysis of metals in the environment: Ba, Be, Pb, and Sr in soils; Pb in paint; and Be and Pb particles collected on filters. Detection limits in ppm for metals in soils were 265 (Ba), 9.3 (Be), 298 (Pb), and 42 (Sr). The detection limit for Pb in paint was 0.8% (8000 ppm), corresponding to 0.052 mg/cm2. The higher limit obtained for Pb in paint is attributed to the use of the 220.35-nm Pb(II) line instead of the stronger 405.78-nm Pb(I) line used for soils. Spectral interferences prevented use of the 405.78-nm line to determine Pb in paint. The surface detection limit for Be particles on filters was dependent on particle size and ranged from 21 to 63 ng/cm2. The detection limit for Pb particles on filters was 5.6 μg/cm2.

Twelve different types of data normalization for the proposition of classification, univariate and multivariate regression models for the direct analyses of alloys by laser-induced breakdown spectroscopy (LIBS)

2016 ◽  
Vol 31 (10) ◽  
pp. 2005-2014 ◽  
Author(s):  
Jeyne Pricylla Castro ◽  
Edenir Rodrigues Pereira-Filho
Keyword(s):  
Multivariate Regression ◽  
Regression Models ◽  
Direct Analysis ◽  
Laser Induced Breakdown Spectroscopy ◽  
Emission Signal ◽  
Breakdown Spectroscopy ◽  
Different Types ◽  
Laser Induced Breakdown ◽  
Signal Normalization

Emission signal normalization in LIBS for the direct analysis of metal samples aiming at the determination of 10 analytes (Al, Cr, Cu, Fe, Mn, Mo, Ni, Ti, V and Zn).

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