@article{RethfeldtBrinkmannRiebeetal.2021,
  author    = {Rethfeldt, Nina and Brinkmann, Pia and Riebe, Daniel and Beitz, Toralf and K{\"o}llner, Nicole and Altenberger, Uwe and L{\"o}hmannsr{\"o}ben, Hans-Gerd},
  title     = {Detection of Rare Earth Elements in Minerals and Soils by Laser-Induced Breakdown Spectroscopy (LIBS) Using Interval PLS},
  series = {Minerals},
  volume    = {11},
  journal   = {Minerals},
  publisher = {MDPI},
  address   = {Basel, Schweiz},
  issn      = {2075-163X},
  doi       = {10.3390/min11121379},
  pages     = {1 -- 17},
  year      = {2021},
  abstract  = {The numerous applications of rare earth elements (REE) has lead to a growing global demand and to the search for new REE deposits. One promising technique for exploration of these deposits is laser-induced breakdown spectroscopy (LIBS). Among a number of advantages of the technique is the possibility to perform on-site measurements without sample preparation. Since the exploration of a deposit is based on the analysis of various geological compartments of the surrounding area, REE-bearing rock and soil samples were analyzed in this work. The field samples are from three European REE deposits in Sweden and Norway. The focus is on the REE cerium, lanthanum, neodymium and yttrium. Two different approaches of data analysis were used for the evaluation. The first approach is univariate regression (UVR). While this approach was successful for the analysis of synthetic REE samples, the quantitative analysis of field samples from different sites was influenced by matrix effects. Principal component analysis (PCA) can be used to determine the origin of the samples from the three deposits. The second approach is based on multivariate regression methods, in particular interval PLS (iPLS) regression. In comparison to UVR, this method is better suited for the determination of REE contents in heterogeneous field samples. View Full-Text},
  language  = {en}
}
@article{ErlerRiebeBeitzetal.2023,
  author    = {Erler, Alexander and Riebe, Daniel and Beitz, Toralf and L{\"o}hmannsr{\"o}ben, Hans-Gerd and Leenen, Mathias and P{\"a}tzold, Stefan and Ostermann, Markus and W{\´o}jcik, Michał},
  title     = {Mobile laser-induced breakdown spectroscopy for future application in precision agriculture},
  series = {Sensors},
  volume    = {23},
  journal   = {Sensors},
  number    = {16},
  publisher = {MDPI},
  address   = {Basel},
  issn      = {1424-8220},
  doi       = {10.3390/s23167178},
  pages     = {17},
  year      = {2023},
  abstract  = {In precision agriculture, the estimation of soil parameters via sensors and the creation of nutrient maps are a prerequisite for farmers to take targeted measures such as spatially resolved fertilization. In this work, 68 soil samples uniformly distributed over a field near Bonn are investigated using laser-induced breakdown spectroscopy (LIBS). These investigations include the determination of the total contents of macro- and micronutrients as well as further soil parameters such as soil pH, soil organic matter (SOM) content, and soil texture. The applied LIBS instruments are a handheld and a platform spectrometer, which potentially allows for the single-point measurement and scanning of whole fields, respectively. Their results are compared with a high-resolution lab spectrometer. The prediction of soil parameters was based on multivariate methods. Different feature selection methods and regression methods like PLS, PCR, SVM, Lasso, and Gaussian processes were tested and compared. While good predictions were obtained for Ca, Mg, P, Mn, Cu, and silt content, excellent predictions were obtained for K, Fe, and clay content. The comparison of the three different spectrometers showed that although the lab spectrometer gives the best results, measurements with both field spectrometers also yield good results. This allows for a method transfer to the in-field measurements.},
  language  = {en}
}