Dataset Information

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

ABSTRACT: 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.

SUBMITTER: Erler A

PROVIDER: S-EPMC7014682 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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

Erler Alexander A Riebe Daniel D Beitz Toralf T Löhmannsröben Hans-Gerd HG Gebbers Robin R

Sensors (Basel, Switzerland) 20200111 2

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, soi ...[more]

PMID: 31940811

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Project description:In this work, we report the results of the compositional analysis of an aluminum gallium arsenide (AlGaAs) sample using the calibration-free laser-induced breakdown spectroscopy (CF-LIBS) technique. The AlGaAs sample was doped with three various concentrations of gallium (Ga), arsenic (As), and aluminum (Al), as reported by the manufacturer, and the CF-LIBS technique was employed to identify the doping concentration. A pulsed Q-switched Nd: YAG laser capable of delivering 200 and 400 mJ energy at 532 and 1064 nm, respectively, was focused on the target sample for ablation, and the resulting emission spectra were captured using a LIBS 2000+ spectrometer covering the spectral range from 200 to 720 nm. The emission spectra of the AlGaAs sample yielded spectral lines of Ga, As, and Al. These lines were further used to calculate the plasma parameters, including electron temperature and electron number density. The Boltzmann plot method was used to calculate the electron temperature, and the average electron temperature was found to be 5744 ± 500 K. Furthermore, the electron number density was calculated from the Stark-broadened line profile method, and the average number density was calculated to be 6.5 × 1017 cm-3. It is further observed that the plasma parameters including electron temperature and electron number density have an increasing trend with laser irradiance and a decreasing trend along the plume length up to 2 mm. Finally, the elemental concentrations in terms of weight percentage using the CF-LIBS method were calculated to be Ga: 94%, Al: 4.77% and As: 1.23% for sample-1; Ga: 95.63%, Al: 1.15% and As: 3.22% for sample-2; and Ga: 97.32%, Al: 0.69% and As: 1.99% for sample-3. The certified concentrations were Ga: 95%, Al: 3% and As: 2% for sample-1; Ga: 96.05%, Al: 1% and As: 2.95% for sample-2; and Ga: 97.32%, Al: 0.69% and As: 1.99% for sample-3. The concentrations measured by CF-LIBS showed good agreement with the certified values reported by the manufacturer. These findings suggest that the CF-LIBS technique opens up an avenue for the industrial application of LIBS, where quantitative/qualitative analysis of the material is highly desirable.

Dataset Information

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

Publications

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

Similar Datasets

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