TY - CONF A1 - Büchele, Dominique A1 - Rühlmann, Madlen A1 - Schmid, Thomas A1 - Ostermann, Markus T1 - Comparison between uni- and multivariate data analysis for the determination of nutrients in soils using XRF N2 - Aim of the Federal Institute for Materials Research and Testing (BAM) in the frame of I4S - “Intelligence for Soil” is the characterization of an X-ray fluorescence (XRF) based sensor for robust online-application of arable land.Fast soil mapping for agricultural purpose allows the site-specific optimized introduction of plant essential nutrients like S, K, Ca, and Fe. This is important given that the distribution of minor and trace elements varies widely. The non-destructive and contactless XRF is suitable for rapid in-situ analysis on the field due to minimal sample preparation and simultaneous multi-element analysis. Soils are already considered as a complex matrix due to their wide range of elements in different contents, especially light elements with low atomic numbers (Z<19). Problems by measuring soil samples also arise from heterogeneity of the sample and matrix effects. Large grain size distribution causes strong inhomogeneity and matrix effects occur through physical properties related to high concentration of main components. Matrix-specific calibration strategies for determination of total major and minor plant essential nutrients are particularly important regarding these difficulties. For accurate calibration, data treatment and evaluation must also be considered. Empirical univariate and multivariate data analysis were compared regarding their analytical figures of merit. Using principal component analysis (PCA) it was possible to classify German soils in different groups as sand, clay and silt. A calibration curve was obtained by partial least squares regression (PLSR) and the elemental content of German soils was predicted. Elemental distribution maps for different German arable lands were created and the results compared to reference measurements. The correlation between predicted values and reference values were in good agreement for most major and minor nutrients. T2 - BonaRes Conference CY - Berlin, Germany DA - 26.02.2018 KW - PLSR KW - XRF KW - Soil KW - PCA PY - 2018 AN - OPUS4-45007 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -