TY - JOUR A1 - Sowoidnich, Kay A1 - Pätzold, Stefan A1 - Ostermann, Markus A1 - Sumpf, Bernd A1 - Maiwald, Martin T1 - Qualitative and quantitative soil characterization on an agricultural field using a portable shifted excitation Raman difference spectroscopy instrument N2 - Site-specific farmland management requires comprehensive information about the soil status to derive informed treatment decisions, e.g. for liming or fertilizer recommendations. Standard laboratory methods relying on sample collection have only limited ability to adequately capture the spatial variability of typical agricultural fields. Here, on-site analytical techniques with the potential to measure the soil properties on a substance-specific level and at the required spatial resolution could be very beneficial. Raman spectroscopy is a very promising technique for this purpose as it provides a molecular fingerprint of soil constituents. However, intrinsic soil fluorescence and daylight interference can be major issues masking characteristic Raman signals. Here, we apply an in-house developed portable shifted excitation Raman difference spectroscopy (SERDS) instrument based on a dual-wavelength diode laser emitting around 785 nm to effectively separate the Raman signals of soil from such interferences. SERDS investigations on a selected agricultural field in Germany demonstrate that the Raman spectroscopic signature of 9 soil minerals and organic carbon could successfully be separated from intense backgrounds. Using partial least squares regression against reference analyses, a successful prediction of the soil carbonate (R2 = 0.86, root mean squared error of cross validation RMSECV = 2.49%) and soil organic carbon content (R2 = 0.89, RMSECV = 0.32%) as important soil parameters is realized. The results obtained on-site with the portable instrument were confirmed by SERDS laboratory experiments of collected soil samples thus highlighting the capability and reliability of portable SERDS as promising and complementary tool for precision agriculture KW - XRF KW - Raman spectroscopy KW - Soil KW - SERDS KW - Precision agriculture PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-634597 DO - https://doi.org/10.1039/d5an00178a SN - 0003-2654 VL - 150 IS - 13 SP - 2934 EP - 2944 PB - Royal Society of Chemistry (RSC) AN - OPUS4-63459 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Tobias, Charlie A1 - Gehrenkemper, Lennart A1 - Bernstein, Thomas A1 - Schlau, Sven A1 - Simon, Fabian A1 - Röllig, Mathias A1 - Meermann, Björn A1 - von der Au, Marcus T1 - Development of a fully automated slurry sampling introduction system for GF-AAS and its application for the determination of cadmium in different matrices N2 - element analysis, offering high sensitivity and precision. However, its effectiveness is limited by sample preparation challenges for solid samples like soils and microplastics. Traditional methods include sample preparation, such as digestion, which is time-consuming and involves reagents, like acids, contributing to measurement uncertainty and higher carbon footprints. Slurry sampling allows direct analysis of suspensions, offering a more efficient alternative. However, maintaining suspension stability is challenging, requiring robust autosampler systems to streamline the process and enhance analytical performance. Results: We present a novel autosampler extension for slurry sample introduction into GF-AAS. This system ensures suspension stability with a stirring device and closed vessels to prevent evaporation and contamination, incorporating a cooling unit to reduce solvent and analyte losses. It installs and removes in minutes without additional connections. Validation with cadmium analysis in BAM-U110 (Soil) and BAM-H010 (ABS) showed high reliability. For BAM-U110 (Soil), we achieved recovery rates of 94 % ± 13 % in water suspension. The recovery rate for BAM-H010 (ABS) was 104 % ±11 % in acetonitrile suspension. These results demonstrate the system’s robustness, versatility, and accuracy for different matrices. Significance: The autosampler extension helps solve key problems in trace element analysis of solid samples, making the process faster and more accurate. It works well with complex materials, making it useful for areas like microplastic or nanoparticle analysis. This improvement also helps meet regulations for monitoring environ mental and polymer samples, offering a reliable and flexible tool for high-throughput analysis with fewer errors. KW - Slurry AAS KW - Soil KW - Cd PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-618531 DO - https://doi.org/10.1016/j.aca.2024.343460 SN - 0003-2670 VL - 1335 SP - 1 EP - 7 PB - Elsevier BV AN - OPUS4-61853 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Schmidinger, J. A1 - Barkov, V. A1 - Tavakoli, H. A1 - Correa, J. A1 - Ostermann, Markus A1 - Atzmueller, M. A1 - Gebbers, R. A1 - Vogel, S. T1 - Which and how many soil sensors are ideal to predict key soil properties: A case study with seven sensors N2 - Soil sensing enables rapid and cost-effective soil analysis. However, a single sensor often does not generate enough information to reliably predict a wide range of soil properties. Within a case-study, our objective was to identify how many and which combinations of soil sensors prove to be suitable for high-resolution soil mapping. On a subplot of an agricultural field showing a high spatial soil variability, six in-situ proximal soil sensors (PSSs) next to remote sensing (RS) data from Sentinel-2 were evaluated based on their capabilities to predict a set of soil properties including: soil organic carbon, pH, moisture as well as plant-available phosphorus, magnesium and potassium. The set of PSSs consisted of ion-selective pH electrodes, a capacitive soil moisture sensor, an apparent soil electrical conductivity measuring system as well as passive gamma-ray-, X-ray fluorescence- and nearinfrared spectroscopy. All possible combinations of sensors were exhaustively evaluated and ranked based on their predict KW - XRF KW - Soil KW - Remote Sensing KW - Precision agriculture PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-613920 DO - https://doi.org/10.1016/j.geoderma.2024.117017 VL - 450 SP - 1 EP - 17 PB - Elsevier B.V. AN - OPUS4-61392 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - 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 - Sowoidnich, K. A1 - Maiwald, M. A1 - Ostermann, Markus A1 - Sumpf, B. T1 - Shifted excitation Raman difference spectroscopy for soil component identification and soil carbonate determination in the presence of strong fluorescence interference N2 - 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. KW - Calcium carbonate KW - Raman spectroscopy KW - Soil KW - X-Ray fluorescence KW - SERDS PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-569016 DO - https://doi.org/10.1002/jrs.6500 SN - 0377-0486 IS - Special Issue SP - 1 EP - 14 PB - John Wiley & Sons Ltd. CY - Hoboken, New Jersey, USA AN - OPUS4-56901 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Wander, Lukas A1 - Lommel, Lukas A1 - Meyer, Klas A1 - Braun, Ulrike A1 - Paul, Andrea T1 - Development of a low-cost method for quantifying microplastics in soils and compost using near-infrared spectroscopy N2 - Near-infrared (NIR) spectroscopy is a promising candidate for low-cost, nondestructive, and high-throughput mass quantification of micro¬plastics in environmental samples. Widespread application of the technique is currently hampered mainly by the low sensitivity of NIR spectroscopy compared to thermo-analytical approaches commonly used for this type of analysis. This study shows how the application of NIR spectroscopy for mass quantification of microplastics can be extended to smaller analyte levels by combining it with a simple and rapid microplastic enrichment protocol. For this purpose, the widely used flotation of microplastics in a NaCl solution, accelerated by centrifugation, was chosen which allowed to remove up to 99 % of the matrix at recovery rates of 83–104 %. The spectroscopic measurements took place directly on the stainless-steel filters used to collect the extracted particles to reduce sample handling to a minimum. Partial least squares regression (PLSR) models were used to identify and quantify the extracted microplastics in the mass range of 1–10 mg. The simple and fast extraction procedure was systematically optimized to meet the requirements for the quantification of microplastics from common PE-, PP-, and PS-based packaging materials with a particle size < 1 mm found in compost or soils with high natural organic matter content (> 10 % determined by loss on ignition). Microplastics could be detected in model samples at a mass fraction of 1 mg g-1. The detectable microplastic mass fraction is about an order of magnitude lower compared to previous studies using NIR spectroscopy without additional enrichment. To emphasize the cost-effectiveness of the method, it was implemented using some of the cheapest and most compact NIR spectrometers available. KW - NIR KW - Soil KW - compost KW - PLSR PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-546405 DO - https://doi.org/10.1088/1361-6501/ac5e5f SN - 0957-0233 VL - 33 IS - 7 SP - 075801 EP - 075814 PB - IOP Publishing Ltd. CY - UK AN - OPUS4-54640 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Horf, M. A1 - Gebbers, R. A1 - Vogel, S. A1 - Ostermann, Markus A1 - Piepel, M.-F. A1 - Olfs, H.-W. T1 - Determination of Nutrients in Liquid Manures and Biogas Digestates by Portable Energy-Dispersive X-ray Fluorescence Spectrometry N2 - 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. KW - XRF KW - Animal slurry KW - Fertilizer KW - Soil KW - Precision farming PY - 2021 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-527622 DO - https://doi.org/10.3390/s21113892 VL - 21 IS - 11 SP - 3892 PB - MDPI CY - Basel, Switzerland AN - OPUS4-52762 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Adame, Andressa T1 - Development of an automatic system for in situ analysis of soil using a handheld Energy Dispersive X-Ray Fluorescence (EDXRF) N2 - The project “Intelligence for Soil” (I4S) aims at the design of an integrated system for improvement of soil functions and fertilizer recommendations. This system is composed by different sensors that will provide a detailed assessment of soil properties and processes, which are prerequisites for a site-specific, resource-saving and ecofriendly soil management, considering the soil as a sustainable resource for the bioeconomy. One of these sensors will be an energy-dispersive X-Ray Fluorescence spectrometer. It is a non-destructive technique suitable for in-situ measurements due to a minimum sample preparation and it allows fast multielement analyses. In this work, an automatic system has been developed using a handheld equipment from Olympus (Vanta C series). A polypropylene (PP) film was used to protect the measuring window of the device from dust and possible cross-contamination. To control the stepper motor that unrolls the PP film, a microcontroller was used to ensure that a piece of clean PP is in front of the measuring window for each new analysis. Preliminary calibration studies using pre-defined methods, Geochem and Soil Methods, were performed with the following Certified Reference Materials (CRMs): NRC Till 1-3, NIST 2710, BAM U110, ERM CC141, BCR 142R, IAEA Soil 7. The CRMs were measured 10 times at different spots. The spot size was 10 mm in diameter, irradiation time was 60 ? s. The averaged data from X ray characteristic emission line intensities for Al, P, Si, Ca, Fe, Mn, Zn, Cu and Ni Kα were in close agreement with certified mass fraction data. The linear correlation coefficients (r) ranged from 0.852 for P to 0.999 for Mn. A second round of calibration studies were performed with the following CRMs: GBW07402, GBW 07405, NCS DC 73023, NCS DC 73030, NCS DC 85109, NCS DC 87104, NIST 1646a, NIST 2704, NIST 2710, NRC Till 1-3, VS 2498-83, and the same pre-defined methods and experimental parameters were employed. The results of the 13 CRMs were now compared with the values obtained by a validated WDXRF method. The linear correlation coefficients (r) ranged from 0.998 for Ca to 0.999 for Zn. Other elements such as S, K and Ti can also be properly determined, but validation still requires more robust calibration models. Further calibration studies will be performed in order to circumvent matrix effects and to guarantee reliable results. Besides that, the automatic system will be placed on a mobile sensor platform and the system will be tested in the field. A guidance for on site-specific fertilization integrating the results obtained from different sensors placed on the platform is expected. T2 - 16. Kolloquium Prozessanalytik CY - Online Meeting DA - 23.11.2020 KW - Röntgenfluoreszenz KW - Boden KW - XRF KW - Soil PY - 2020 AN - OPUS4-51776 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -