TY - JOUR A1 - Erler, A. A1 - Riebe, D. A1 - Beitz, T. A1 - Löhmannsröben, H.-G. A1 - Leenen, M. A1 - Pätzold, S. A1 - Ostermann, Markus A1 - Wójcik, M. T1 - Mobile Laser-Induced Breakdown Spectroscopy for Future Application in Precision Agriculture—A Case Study N2 - 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 KW - LIBS KW - Precision agriculture KW - Soil KW - Multivariate methods KW - Feature selection PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-580777 DO - https://doi.org/10.3390/s23167178 VL - 23 IS - 16 SP - 1 EP - 17 PB - MDPI AG CY - Basel, Schweiz AN - OPUS4-58077 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Büchele, Dominique A1 - Chao, Madlen A1 - Ostermann, Markus A1 - Leenen, M. A1 - Bald, Ilko T1 - Multivariate chemometrics as a key tool for prediction of K and Fe in a diverse German agricultural soil-set using EDXRF N2 - Within the framework of precision agriculture, the determination of various soil properties is moving into focus, especially the demand for sensors suitable for in-situ measurements. Energy-dispersive X-ray fluorescence (EDXRF) can be a powerful tool for this purpose. In this study a huge diverse soil set (n = 598) from 12 different study sites in Germany was analysed with EDXRF. First, a principal component analysis (PCA) was performed to identify possible similarities among the sample set. Clustering was observed within the four texture classes clay, loam, silt and sand, as clay samples contain high and sandy soils low iron mass fractions. Furthermore, the potential of uni- and multivariate data evaluation with partial least squares regression (PLSR) was assessed for accurate Determination of nutrients in German agricultural samples using two calibration sample sets. Potassium and iron were chosen for testing the performance of both models. Prediction of these nutrients in 598 German soil samples with EDXRF was more accurate using PLSR which is confirmed by a better overall averaged deviation and PLSR should therefore be preferred. KW - XRF KW - Chemometrics KW - Soil KW - Agriculture KW - Multivariate PY - 2019 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-498671 DO - https://doi.org/10.1038/s41598-019-53426-5 VL - 9 SP - 17588 PB - Nature AN - OPUS4-49867 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -