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Eingeladener Vortrag
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Magnesium (Mg) is a major element in a range of silicate and carbonate minerals, the hydrosphere and biosphere and plays important roles in (bio-) geochemical and physiological cycles. Mg has three stable isotopes, 24Mg, 25Mg and 26Mg with natural abundances of 79 %, 10 %, and 11 %, respectively. It is due to their relatively large mass difference (~8% between 24Mg and 26Mg) that isotope fractionation leads to slight variations of isotope amount ratios n(26Mg)/n(24Mg) in biological, environmental and geological samples. Traditionally, isotope ratios are measured by mass spectrometric methods and isotope ratios are expressed as deviation from an internationally agreed upon material, i.e. the zero-point of the δ-value scale. Drawbacks of this method include the high costs for instruments and their operation, experienced operators and elaborate, time-consuming chromatographic sample preparation.
Recently, optical spectrometric methods have been proposed as faster and low-cost alternative for the analysis of isotope ratios of selected elements by means of high- resolution continuum source graphite furnace molecular absorption spectrometry (HR- CS-GFMAS) and laser ablation molecular isotopic spectrometry (LAMIS).
For the determination of Mg isotope amount ratios, the molecular spectrum of the in-situ generated MgF and MgO molecules were studied. In the case of HR-CS-GFMAS, the absorption spectrum was recorded for MgF for the electronic transitions X2Σ → A2Πi and X 2Σ → B2Σ+ around wavelengths 358 nm and 268 nm, respectively. In the case of LAMIS, we investigated the MgF molecule for the electronic transition A2Πi → X2Σ as well as the MgO molecule for the electronic transition A1Π+ → X1Σ around 500 nm. The MgF and MgO spectra are described by the linear combination of their isotopic components or isotopologues: 24MgF, 25MgF, and 26MgF for the MgF and 24MgO, 25MgO, and 26MgO for the MgO (F is monoisotopic, and the isotope composition of O is assumed as constant). By HR-CS-GFMAS the analysis of Mg was done by deconvolution of the MgF spectrum by partial least square regression (PLS) calibrated with enriched isotope spikes. Isotope amount ratios in rock samples with and without matrix separation were analyzed. Calculated δ-values were accurate and obtained with precisions ranging between 0.2 ‰ and 0.5 ‰ (1 SD, n = 10). On the other hand, LAMIS allows the direct analysis of solid samples with the extended possibility of in-situ analysis. Main advantages, limitations, and scopes of both optical techniques are going to be discussed and compared to MC-ICP-MS.
Society for Applied Spectroscopy (SAS) Atomic Section Student Award.
Magnesium is a major element in the hydrosphere and biosphere and plays important roles in (bio-) geochemical and physiological cycles. Mg has three stable isotopes, 24Mg, 25Mg and 26Mg. It is due to their relatively large mass difference (~8% between) that isotope fractionation leads to slight variations of isotope amount ratios in biological, environmental and geological samples. Traditionally, isotope ratios are measured by mass spectrometric methods. Their drawbacks include the high costs for instruments and their operation, experienced operators and elaborate time-consuming chromatographic sample preparation.
Recently, optical spectrometric methods have been proposed as faster and low-cost alternative for the analysis of isotope ratios of selected elements by means of high-resolution continuum source molecular absorption spectrometry (HR-CS-MAS), and laser ablation molecular isotopic spectrometry (LAMIS).
For the determination of Mg isotope ratios in selected rock reference materials, the molecular spectrum of the in-situ generated MgF and MgO molecules were studied and their results compared with MC-ICP-MS. By HR-CS-MAS, samples were dissolved by acid digestion and Mg isotopes analyzed with and without matrix. The absorption spectrum was recorded for MgF for the electronic transitions X 2Σ → A 2 Πi, and X 2Σ → B 2Σ+. In the case of LAMIS, we investigated the MgF molecule for the electronic transition A 2Πi → X 2Σ, as well as direct analysis by the MgO molecule for the electronic transition A 1Π+ → X 1Σ. The MgF and MgO spectra are described as the linear combination of their isotopic components or isotopologues: 24MgF, 25MgF, and 26MgF for the MgF and 24MgO, 25MgO, and 26MgO for the MgO. The isotope analysis was done by deconvolution of the MgF spectrum by partial least square regression (PLS) calibrated with enriched isotope spikes. Results were accurate with precisions ranging between 0.2 ‰ and 0.8 ‰ (2 SD, n= 10) for HR-CS-GFMAS. No statistically significant differences were observed for samples w/o matrix extraction. On the other hand, LAMIS allows the direct analysis of solid samples with the extended possibility of direct analysis, however the precision is lower due the lack of solid isotopic calibration standards.
Mass spectrometric Methods MC-ICP-MS and TIMS) are without doubt the working horse of stable isotope analysis. However, drawbacks of these methods include the high costs for instruments and their operation, experienced operators and elaborate chromatographic sample preparation which are time consuming.
Optical spectrometric methods are proposed as faster and low-cost alternative for the analysis of isotope ratios of selected elements by means of high-resolution continuum source molecular absorption spectrometry (HR-CS-MAS) and laser ablation molecular isotopic spectrometry (LAMIS). First, stable isotope amount compositions of boron (B) and magnesium (Mg) were determined based on the absorption spectra of in-situ generated heteronuclear diatomic molecules (MH or MX) in graphite furnace HR-CS-MAS. The use of a modular simultaneous echelle spectrograph (MOSES) helps to find the maximal isotope shift in the diatomic molecular spectra produced in a graphite furnace by using isotopic spike solutions. Isotopes of boron (10B and 11B) were studied via their hydrides for the electronic transition X 1Σ+ → A 1Π. The spectrum of a given sample is a linear combination of the 10BH molecule and its isotopologue 11BH. Therefore, the isotopic composition of samples can be calculated by a partial least square regression (PLS). For this, a spectral library was built by using samples and spikes with known isotope composition. Boron isotope ratios measured by HR-CS-MAS are identical with those measured by mass spectrometric methods at the 0.15 ‰ level. Similar results were obtained for a multiple isotope system like Mg (24Mg, 25Mg, and 26Mg), where isotope shifts of their isotopologues can be resolved in the MgF molecule for the electronic transition X 2Σ → A 2 Πi. Finally, the application of molecular spectrometry via emission by LAMIS is compared and discussed.
Magnesium is a naturally occurring element that can be found in several mineral forms in the earth crust. This element presents three stable isotopes 24Mg, 25Mg and 26Mg with a natural abundance of 79%, 10%, and 11% respectively. It is due to their relatively large mass difference (~8% between 24Mg and 26Mg) that isotope fractionation leads to slight isotope amount ratio variations n(26Mg)/n(24Mg) in biological and geological samples. Traditionally, isotope amount ratios have been measured by mass spectrometric methods. However, drawbacks of these methods include the high costs for instruments and their operation, experienced operators and elaborate chromatographic sample preparation which are time-consuming. Recently, optical spectrometric methods have been proposed as faster and low-cost alternative for the analysis of isotope ratios of selected elements by means of high-resolution continuum source graphite furnace molecular absorption spectrometry (HR-CS-GFMAS) and laser ablation molecular isotopic spectrometry (LAMIS). For the determination of Mg isotope amount ratios, the molecular spectrum of the in-situ generated MgF and MgO molecules were studied. In the case of HR-CS-GFMAS, the absorption spectrum was recorded for MgF for the electronic transitions X 2Σ → A 2 Πi and X 2Σ → B 2Σ+ around wavelengths 358 nm and 268 nm respectively. In the case of LAMIS, it was studied the MgF molecule for the electronic transitions A 2Πi → X 2Σ as well as the MgO molecule for the electronic transition A 1Π+ → X 1Σ around 500 nm. The MgF and MgO spectra are composed by the linear combination of their isotopic components or isotopologues: 24MgF, 25MgF, and 26MgF for the MgF and 24MgO, 25MgO, and 26MgO for the MgO (F is monoisotopic, and the isotope composition of O is assumed as constant). By HR-CS-GFMAS the analysis of Mg was done by deconvolution of the MgF spectrum by a partial least square regression (PLS) calibrated with enriched isotope spikes. The isotope amount ratios in rock samples with and without matrix separation were analyzed. Resulting delta values were obtained with precisions ranging between 0.2-0.5 ‰. On the other hand, LAMIS allows the direct analysis of solid samples with the extended possibility of in-situ analysis. Main advantages, limitations, and scopes of both optical techniques are going to be discussed and compared with MC-ICP-MS.
Influence of moisture and grain sizes on the analysis of nutrients in agricultural soils using LIBS
(2018)
Over the last few years, there has been a growing interest to apply spectroscopic methods to the agricultural field for better understanding of soil properties and for efficient, sustainable management of arable land. Within the project I4S (intelligence for soil), funded by the BMBF, an integrated system for site-specific soil fertility management is developed, consisting of different sensors like X-Ray fluorescence analysis (XRF), near-infrared spectroscopy (NIR) and laser-induced breakdown spectroscopy (LIBS). LIBS provides a fast and simultaneous multi-element analysis with little to no sample preparation, which makes it a suitable method for real-time analysis on the field.
The quantification of macro and micro nutrients in soils with LIBS is challenging due to matrix effects, different levels of moisture content and varying grain sizes. First studies revealed that the problems with matrix effects can be overcome by using well characterised soils as reference materials and chemometric tools like Partial Least Squares Regression(PLSR) for calibration.
The next step was to investigate the influence of moisture and grain sizes on the LIBS signal, which is a big issue when measuring directly on the field. The results showed that the LIBS signal decreases exponentially with increasing moisture content, as most of the laser energy is used for vaporising the water. With moisture contents of 30 % or higher almost no signal can be detected. This decrease is more severe for sandy soils than for clay soils. First tests of different grain size distributions indicate that the variation of the LIBS signal increases with growing amounts of larger grains. This results in a higher standard deviation, because of a poorer reproducibility of the plasma formation and plasma characteristic. With the help of chemometric tools the influence of moisture and grain sizes should be implemented in the calibration model for accurate analysis of nutrient composition in agricultural soils.
Over the last few years, there has been a growing interest to apply spectroscopic methods to the agricultural field for better understanding of soil properties and for efficient, sustainable management of arable land. Within the project I4S (intelligence for soil), funded by the BMBF, an integrated system for site-specific soil fertility management is developed, consisting of different sensors like X-Ray fluorescence analysis (XRF), near-infrared spectroscopy (NIR) and laser-induced breakdown spectroscopy (LIBS). LIBS provides a fast and simultaneous multi-element analysis with little to no sample preparation, which makes it a suitable method for real-time analysis on the field.
The quantification of macro and micro nutrients in soils with LIBS is challenging due to matrix effects, different levels of moisture content and varying grain sizes. First studies revealed that the problems with matrix effects can be overcome by using well characterised soils as reference materials and chemometric tools like Partial Least Squares Regression (PLSR) for calibration.
The next step was to investigate the influence of moisture and grain sizes on the LIBS signal, which is a big issue when measuring directly on the field. The results showed that the LIBS signal decreases exponentially with increasing moisture content, as most of the laser energy is used for vaporising the water. With moisture contents of 30 % or higher almost no signal can be detected. This decrease is more severe for sandy soils than for clay soils. First tests of different grain size distributions indicate that the variation of the LIBS signal increases with growing amounts of larger grains. This results in a higher standard deviation, because of a poorer reproducibility of the plasma formation and plasma characteristic. With the help of chemometric tools the influence of moisture and grain sizes should be implemented in the calibration model for accurate analysis of nutrient composition in agricultural soils.
Over the last few years, there has been a growing interest to apply spectroscopic methods to the agricultural field for better understanding of soil properties and for efficient, sustainable management of arable land. Within the project I4S (intelligence for soil), funded by the BMBF, an integrated system for site-specific soil fertility management is developed, consisting of different sensors like X-Ray fluorescence analysis (XRF), near-infrared spectroscopy (NIR) and laser-induced breakdown spectroscopy (LIBS). LIBS provides a fast and simultaneous multi-element analysis with little to no sample preparation, which makes it a suitable method for real-time analysis on the field.
The quantification of macro and micro nutrients in soils with LIBS is challenging due to matrix effects, different levels of moisture content and varying grain sizes. First studies revealed that the problems with matrix effects can be overcome by using well characterised soils as reference materials and chemometric tools like Partial Least Squares Regression (PLSR) for calibration.
The next step was to investigate the influence of moisture and grain sizes on the LIBS signal, which is a big issue when measuring directly on the field. The results showed that the LIBS signal decreases exponentially with increasing moisture content, as most of the laser energy is used for vaporising the water. With moisture contents of 30 % or higher almost no signal can be detected. This decrease is more severe for sandy soils than for clay soils. First tests of different grain size distributions indicate that the variation of the LIBS signal increases with growing amounts of larger grains. This results in a higher standard deviation, because of a poorer reproducibility of the plasma formation and plasma characteristic. With the help of chemometric tools the influence of moisture and grain sizes should be implemented in the calibration model for accurate analysis of nutrient composition in agricultural soils.
Over the last few years, there has been a growing interest to apply spectroscopic methods to the agricultural field for better understanding of soil properties and for efficient, sustainable management of arable land. Within the project I4S (intelligence for soil), funded by the BMBF, an integrated system for site-specific soil fertility management is developed, consisting of different sensors like X-Ray fluorescence analysis (XRF), near-infrared spectroscopy (NIR) and laser-induced breakdown spectroscopy (LIBS). LIBS provides a fast and simultaneous multi-element analysis with little to no sample preparation, which makes it a suitable method for real-time analysis on the field.
The quantification of macro and micro nutrients in soils with LIBS is challenging due to matrix effects, different levels of moisture content and varying grain sizes. First studies revealed that the problems with matrix effects can be overcome by using well characterised soils as reference materials and chemometric tools like Partial Least Squares Regression (PLSR) for calibration.
The next step was to investigate the influence of moisture and grain sizes on the LIBS signal, which is a big issue when measuring directly on the field. The results showed that the LIBS signal decreases exponentially with increasing moisture content, as most of the laser energy is used for vaporising the water. With moisture contents of 30 % or higher almost no signal can be detected. This decrease is more severe for sandy soils than for clay soils. First tests of different grain size distributions indicate that the variation of the LIBS signal increases with growing amounts of larger grains. This results in a higher standard deviation, because of a poorer reproducibility of the plasma formation and plasma characteristic. With the help of chemometric tools the influence of moisture and grain sizes should be implemented in the calibration model for accurate analysis of nutrient composition in agricultural soils.
In den letzten Jahrzehnten ist die Nachfrage nach kostengünstigen und flächendeckenden Kartierungsmöglichkeiten im Hinblick auf eine ertragssteigernde und umweltfreundlichere Bewirtschaftung von landwirtschaftlichen Nutzflächen stark gestiegen. Hierfür eignen sich spektroskopische Methoden wie die Röntgenfluoreszenzanalyse (RFA), Raman- und Gammaspektroskopie sowie die laserinduzierte Plasmaspektroskopie (LIBS). In Abhängigkeit von der Funktionsweise der jeweiligen Methoden werden Informationen zu verschiedensten Bodeneigenschaften wie Nährelementgehalt, Textur und pH-Wert erhalten.
Ziel dieser Arbeit ist die Entwicklung eines Online-LIBS-Verfahrens zur Nährelementbestimmmung und Kartierung von Ackerflächen. Die LIBS ist eine schnelle und simultane Multielementanalyse bei der durch das Fokussieren eines hochenergetischen Laserpulses Probenmaterial von der Probenoberfläche ablatiert wird und in ein Plasma überführt wird. Beim Abkühlen des Plasmas wird Strahlung emittiert, welche Rückschlüsse über die elementare Zusammensetzung der Probe gibt. Diese Arbeit ist im Teilprojekt I4S (Intelligenz für Böden) im Forschungsprogramm BonaRes (Boden als nachhaltige Ressource für die Bioökonomie) des Bundesministerium für Bildung und Forschung (BMBF) entstanden. Es wurden insgesamt 651 Bodenproben von verschiedenen Test-Agrarflächen unterschiedlichster Standorte Deutschlands gemessen, ausgewertet und zu Validierungszwecken mit entsprechender Referenzanalytik wie die Optische Emissionsspektroskopie mittels induktiv gekoppeltem Plasma (ICP-OES) und die wellenlängendispersive Röntgenfluoreszenzanalyse (WDRFA) charakterisiert.
Für die Quantifizierung wurden zunächst die Messparameter des LIBS-Systems auf die Bodenmatrix optimiert und für die Elemente geeignete Linien ausgewählt sowie deren Nachweisgrenzen bestimmt. Es hat sich gezeigt, dass eine absolute Quantifizierung basierend auf einem univariaten Ansatz aufgrund der starken Matrixeffekte und der schlechten Reproduzierbarkeit des Plasmas nur eingeschränkt möglich ist. Bei Verwendung eines multivariaten Ansatz wie der Partial Least Squares Regression (PLSR) für die Kalibrierung konnten für die Nährelemente im Vergleich zur univariaten Variante Analyseergebnisse mit höherer Güte und geringeren Messunsicherheiten ermittelt werden. Die Untersuchungen haben gezeigt, dass das multivariate Modell weiter verbessert werden kann, indem mit einer Vielzahl von gut analysierten Böden verschiedener Standorte, Bodenarten und einem breiten Gehaltsbereich kalibriert wird. Mithilfe der Hauptkomponentenanalyse (PCA) wurde eine Klassifizierung der Böden nach der Textur realisiert. Weiterhin wurde auch eine Kalibrierung mit losem Bodenmaterial erstellt. Trotz der Signalabnahme konnten für die verschiedenen Nährelemente Kalibriergeraden mit ausreichender, analytischer Güte erstellt werden.
Für den Einsatz auf dem Acker wurde außerdem der Einfluss von Korngröße und Feuchtigkeit auf das LIBS-Signal untersucht. Die unterschiedlichen Korngrößen haben nur einen geringen Einfluss auf das LIBS-Signal und das Kalibriermodell lässt sich durch entsprechende Proben leicht anpassen. Dagegen ist der Einfluss der Feuchtigkeit deutlich stärker und hängt stark von der Bodenart ab, sodass für jede Bodenart ein separates Kalibriermodell für verschiedene Feuchtigkeitsgehalte erstellt werden muss. Mithilfe der PCA kann der Feuchtigkeitsgehalt im Boden grob abgeschätzt werden und die entsprechende Kalibrierung ausgewählt werden.
Diese Arbeit liefert essentielle Informationen für eine Echtzeit-Analyse von Nährelementen auf dem Acker mittels LIBS und leistet einen wichtigen Beitrag zu einer fortschrittlichen und zukunftsfähigen Nutzung von Ackerflächen.
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