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For ten years µ-XRF (micro-focus X-ray fluorescence) analysis has been performed with SEM/EDS (scanning electron microscope with an energy dispersive X-ray detector) so that non-destructive analysis of elements at trace level concentrations below 100 µg g-1 becomes possible. This can be considered as a valuable completion of the classical electron probe microanalysis by EDS, an analytical method 'suffering' from rather poor limits of detection in the range of one to two orders of magnitude higher than those of µ-XRF. Based on a representative actual application, namely analysis of RoHS relevant elements at trace concentration levels, the performance of the rather new analytical method with respect to its limits of detection is systematically evaluated. CRMs (certified reference materials) specially prepared to support the quantitative XRF analysis of RoHS relevant elements were employed. On the other side, based on calculations of µ-XRF spectra according to a recently developed physical model the optimization of the analytical performance is also successfully undertaken.
In this study the microscopic homogeneity of the newly developed plastic reference materials BAM H001-BAM H010 was investigated. The materials consist of an acrylonitryle-butadien-styrene terpolymer, doped with different amounts of the elements Br, Cd, Cr, Hg and Pb. For the quantitative determination of the degree of homogeneity, a procedure proposed by Kempenaers et al. (Fresenius J. Anal. Chem., 2001, 369, 733-737) was used. On every sample an extensive number of different points were analyzed and standard deviation for every element mentioned above was used to calculate a minimal sampling mass that is necessary to reach a certain level of uncertainty caused by inhomogeneity (mmin,5%). The experiments were taken out with synchrotron µ-XRF (SR µ-XRF) at BESSYII in Berlin and by laser ablation inductively coupled plasma mass spectroscopy (LA-ICP-MS). The calculated values for mmin,5% of both techniques showed comparable results for all elements. It could be shown that the materials are suitable for calibration of micro analytic techniques if at least 64 µg are used.
Knowing the exact nutrient composition of organic fertilizers is a prerequisite for their appropriate application to improve yield and to avoid environmental pollution by over-fertilization.
Traditional standard chemical analysis is cost and time-consuming and thus it is unsuitable for a rapid analysis before manure application. As a possible alternative, a handheld X-ray fluorescence (XRF) spectrometer was tested to enable a fast, simultaneous, and on-site analysis of several elements.
A set of 62 liquid pig and cattle manures as well as biogas digestates were collected, intensively homogenized and analysed for the macro plant nutrients phosphorus, potassium, magnesium, calcium, and sulphur as well as the micro nutrients manganese, iron, copper, and zinc using the standard lab procedure. The effect of four different sample preparation steps (original, dried, filtered, and dried filter residues) on XRF measurement accuracy was examined. Therefore, XRF results were correlated with values of the reference analysis. The best R2 s for each element ranged from 0.64 to 0.92. Comparing the four preparation steps, XRF results for dried samples showed good correlations (0.64 and 0.86) for all elements. XRF measurements using dried filter residues showed also good correlations with R2 s between 0.65 and 0.91 except for P, Mg, and Ca. In contrast, correlation Analysis for liquid samples (original and filtered) resulted in lower R2 s from 0.02 to 0.68, except for K (0.83 and 0.87, respectively). Based on these results, it can be concluded that handheld XRF is a promising measuring system for element analysis in manures and digestates.
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.
The preservation and the improvement of the fertility of soils by agricultural management measures requires carefully planned decisions which are based on a detailed capture of the soil qualities and a detailed understanding of soil processes. Profit losses can be caused on the one hand by conventional, surface-uniform managements (e.g., fertilization) by too low management intensity on one part of the surface, while other parts of the field receive too high doses and it thereby comes to environmental impacts or to waste of resources.
X-ray fluorescence analysis (XRF) and the Laser-induced Breakdown Spectroscopy (LIBS) are possible technologies which permit online analyses of the chemical composition.
Mobile proximal gamma-ray spectrometry (GS) is an emerging approach to estimate soil texture directly in the field. It relies on gamma radiation emitted during the natural decay of potassium-40 (K-40) and other isotopes. The K-40 counts are correlated with total K content, mineralogical soil composition and therefore with soil texture. Yet, it is not clear if K fertilisation impacts the ratio of K-40 to total K which would necessitate to take the fertilisation history into account for soil sensing applications. To elucidate this question, a well-documented long-term experiment was selected. The soils of the Rengen grassland experiment (55 plots) were investigated for total K (XRF-K) and for K-40 via mobile proximal GS. No significant differences in XRF-K and K-40 were found between the treatments with and without K fertilisation, although formely published results point to negative and positive K balances, respectively. Fertiliser analysis revealed a ratio of K-40 to total K that was almost identical to the natural abundance of 0.0117%. It was concluded that it is not necessary to take K fertilisation history into account when predicting soil texture from mobile proximal GS on agricultural land for, e.g., precision farming purposes.