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 R²s 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 R²s 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 R²s 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.

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.

As the drive towards recycling electronic waste increases, demand for rapid and reliable analytical methodology to analyse the metal content of the waste is increasing, e.g. to assess the value of the waste and to decide the correct recycling routes. Here, we comprehensively assess the suitability of different x-ray fluorescence spectroscopy (XRF)-based techniques as rapid analytical tools for the determination of critical raw materials, such as Al, Ti, Mn, Fe, Co, Ni, Cu, Zn, Nb, Pd and Au, in three electronic waste matrices: printed circuit boards (PCB), light emitting diodes (LED), and lithium (Li)-ion batteries. As validated reference methods and materials to establish metrological traceability are lacking, several laboratories measured test samples of each matrix using XRF as well as other independent complementary techniques (instrumental neutron activation analysis (INAA), inductively coupled plasma mass spectrometry (ICP-MS) and ICP optical emission spectrometry (OES)) as an inter-laboratory comparison (ILC). Results highlighted key aspects of sample preparation, limits of detection, and spectral interferences that affect the reliability of XRF, while additionally highlighting that XRF can provide more reliable data for certain elements compared to digestion-based approaches followed by ICP-MS analysis (e.g. group 4 and 5 metals). A clear distinction was observed in data processing methodologies for wavelength dispersive XRF, highlighting that considering the metals present as elements (rather than oxides) induces overestimations of the mass fractions when compared to other techniques. Eventually, the effect of sample particle size was studied and indicated that smaller particle size (<200 µm) is essential for reliable determinations.

Detailed knowledge about soil composition is an important prerequisite for many applications, for example precision agriculture. Current standard laboratory methods are complex and time‐consuming but could be complemented by non‐invasive optical techniques. Its capability to provide a molecular fingerprint of individual soil components makes Raman spectroscopy a very promising candidate. A major challenge is strong fluorescence interference inherent to soil, but this issue can be overcome effectively using shifted excitation Raman difference spectroscopy (SERDS). A customized dual‐wavelength diode laser emitting at 785.2 and 784.6 nm was used to investigate 117 soil samples collected from an agricultural field along a distance of 624 m and down to depths of 1 m. To address soil spatial heterogeneity, a raster scan approach comprising 100 measurement spots per sample was applied. Based on the Raman spectroscopic fingerprint extracted from intense fluorescence interference by SERDS, 13 mineral soil constituents were identified, and even closely related molecular species could be discriminated, for example polymorphs of titanium dioxide and calcium carbonate. For the first time, the capability of SERDS is demonstrated to predict the calcium carbonate content as an important soil parameter using partial least squares regression (R² = 0.94, root mean square error of cross‐validation RMSECV = 2.1%). Our findings demonstrate that SERDS can extract a wealth of spectroscopic information from disturbing backgrounds enabling qualitative and quantitative soil analysis. This highlights the large potential of SERDS for precision agriculture but also in further application areas, for example geology, cultural heritage and planetary exploration.

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 (m_min,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 m_min,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.