TY  - JOUR
A1  - Erler, Alexander
A1  - Riebe, Daniel
A1  - Beitz, Toralf
A1  - Löhmannsröben, Hans-Gerd
A1  - Gebbers, Robin
T1  - Soil Nutrient Detection for Precision Agriculture Using Handheld Laser-Induced Breakdown Spectroscopy (LIBS) and Multivariate Regression Methods (PLSR, Lasso and GPR)
JF  - Sensors
N2  - 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.
KW  - LIBS
KW  - lasso
KW  - PLS regression
KW  - gaussian processes
KW  - soil
KW  - precision agriculture
KW  - nutrients
Y1  - 2020
U6  - https://doi.org/10.3390/s20020418
SN  - 1424-8220
VL  - 20
IS  - 2
PB  - MDPI
CY  - Basel
ER  - 
TY  - GEN
A1  - Erler, Alexander
A1  - Riebe, Daniel
A1  - Beitz, Toralf
A1  - Löhmannsröben, Hans-Gerd
A1  - Gebbers, Robin
T1  - Soil Nutrient Detection for Precision Agriculture Using Handheld Laser-Induced Breakdown Spectroscopy (LIBS) and Multivariate Regression Methods (PLSR, Lasso and GPR)
T2  - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe
N2  - 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.
T3  - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 815 
KW  - LIBS
KW  - lasso
KW  - PLS regression
KW  - gaussian processes
KW  - soil
KW  - precision agriculture
KW  - nutrients
Y1  - 2020
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-444183
SN  - 1866-8372
IS  - 815
ER  - 
TY  - GEN
A1  - Lemke, Matthias
A1  - Fernández-Trujillo, Rebeca
A1  - Löhmannsröben, Hans-Gerd
T1  - In-situ LIF analysis of biological and petroleum-based hydraulic oils on soil
N2  - Absorption and fluorescence properties of 4 hydraulic oils (3 biological and 1 petroleum-based) were investigated. In-situ LIF (laser-induced fluorescence) analysis of the oils on a brown sandy loam soil was performed. With calibration, quantitative detection was achieved. Estimated limits of detection were below ca. 500 mg/kg for the petroleum-based oil and ca. 2000 mg/kg for one biological oil. A semi-quantitative classification scheme is proposed for monitoring of the biological oils. This approach was applied to investigate the migration of a biological oil in soil-containing compartments, namely a soil column and a soil bed.
T3  - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - paper 011 
KW  - in-situ
KW  - optical oil sensor
KW  - lubricants
KW  - hydraulic oils
KW  - soil
KW  - laser induced
Y1  - 2005
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-12268
ER  -