Portable X-ray Fluorescence Spectrometry Research Articles

Rapid screening of pharmaceutical products for elemental impurities by a high-resolution portable energy dispersive X-ray fluorescence spectrometer using an efficient fundamental parameter method.

In this study, a rapid screening method for elemental impurities in pharmaceutical products has been established by portable energy dispersive X-ray fluorescence (EDXRF) spectroscopy combined with the efficient fundamental parameter method. The proposed method has been used for the screening of 22 elemental impurities (i.e., Cd, Pb, As, Hg, Co, V, Ni, Tl, Au, Pd, Ir, Os, Rh, Ru, Se, Ag, Pt, Sb, Mo, Cu, Sn, and Cr) in the International Conference on Harmonization (ICH) Q3D guideline. The verification of results could meet the acceptance criteria for accuracy, precision and linearity in the United States Pharmacopoeia 〈233〉. On the other hand, the limit of quantitation of the proposed EDXRF method for the screening of 22 elemental impurities in pharmaceutical products could meet the concentration limits of each element at 10 g maximum daily intake based on the established permitted daily exposure to oral drugs in the ICH Q3D guideline. Our findings open up new possibilities in the rapid screening of pharmaceutical products for the detection of elemental impurities by EDXRF, which can be expected to provide a novel, nondestructive, high-throughput, portable, and sensitive platform for the process control of elemental impurities to ensure the quality and safety of drugs.

Archaeometric Investigation of Gold Coins (Byzantine Period, Romanus Iii) By Means of Portable Xrf: Characterization and Comparison

Some of the ancient materials in museums can only be examined on-site, which requires in-situ analysis techniques. Coins made of precious metals are one of such materials and portable X-ray fluorescence (p-XRF) spectrometry is one of the most preferred technique for gold and silver-based coins that need to be characterized in situ and non-destructively. In this study, a detailed archaeometric investigation was carried out for the gold coins which were unearthed after the excavations in Melik Ahmet Street (Diyarbakır, 1992) and brought to Directorate of Diyarbakır Museum through confiscation. The chemical compositions of the samples were specified by means of portable XRF which was applied on 45 gold coins of the Romanus III period. The main element in the composition was found as gold detected as 93.89% in average. Silver was the most abundant element after gold, however the highest silver rate did not exceed 9% (5.25% in average). Copper and iron were identified respectively in 12 coins (Cu: 1.05-2.46%) and 18 coins (Fe: 0.87-6.5%). Manganese, nickel, titanium, lead, iridium and osmium were seen in one sample each. The hierarchical clustering analysis applied with gold-silver-copper-iron and gold-silver suggested three different groups. The hierarchical clustering analysis was also applied considering the p-XRF data achieved in this study (belonging to the Romanus III period), solidus samples belonging to six Byzantine period emperors, and for the hollow coins belonging to four Byzantine period emperors. Taking into account the distribution, classification and the variations, the coins of different emperor periods were compared.

Ring-eye blue beads in Iron Age central Italy – Preliminary discussion of technology and possible trade connections

The Iron Age was a remarkable period in glass technology development and its spread across the Mediterranean. Communities that populated what is nowadays Central Italy underwent profound changes during this period forming more complex societies, developing proto-urban and urban centres, and incorporating into a wide trade network of the Mediterranean Sea and beyond. Glass objects in that small region are frequently found in burial sites dated to the first half of the first millennium BCE, with small blue beads with simple ring eyes being among the most abundant types. Fifty-six objects of this type (both whole beads and fragments) were studied with a non-invasive approach by means of Optical Microscopy, Fibre Optics Reflectance Spectroscopy, and portable X-ray Fluorescence spectroscopy. The analyses were conducted at the Museo Nazionale Etrusco di Villa Giulia and at the Museo delle Civiltà (both in Rome, Italy). Five samples from the main set were also analysed with a Scanning Electron Microscope coupled to an Energy Dispersive Spectrometer. The data gave preliminary information on the raw materials used to prepare the glass, the manufacturing techniques, and offered some hints to (tentatively) locate the region of provenance. In particular, the analyses established that the beads are soda-lime-silica glass and the source of cobalt, used as the blue colorant, could be an ore from Egypt. Within this general frame, a smaller group showed a different compositional pattern. These preliminary results contribute new knowledge for tracing exchange routes within the Mediterranean during the Iron Age.

Improving soil organic matter estimation accuracy by combining optimal spectral preprocessing and feature selection methods based on pXRF and vis-NIR data fusion

Rapid and accurate estimation of soil organic matter (SOM) content is of great significance for agricultural production and carbon stock estimation. Visible-near-infrared spectroscopy (Vis-NIR) and portable X-ray fluorescence spectroscopy (pXRF), with the fast, low-cost, and environmental friendly characteristics, can realize the rapid large-scale detection of SOM. However, due to the heterogeneity and complexity of soil, estimation of SOM using a single sensor often leads to high uncertainty in result. Multi-sensor data fusion is one of the approaches to solve this problem, but suitable spectral preprocessing methods and data fusion methods still need further research. In this study, 500 soil samples were collected from two watersheds with large differences in soil parent material, soil type, and climate in the Xinjiang Uygur Autonomous Region of China. The effects of different spectral preprocessing methods for vis-NIR and pXRF spectra on SOM estimation were compared, and the effects of five feature selection methods on single sensor estimation and three different multi-sensor fusion estimations were evaluated. The results showed that vis-NIR spectrum was better than pXRF spectrum for SOM estimation, and the 1.6th-order derivative and baseline correction were the optimal preprocessing method for vis-NIR and pXRF spectra (Beam 3), respectively. Feature selection could improve the accuracy of the single sensor and multi-sensor fusion estimations. The competitive adaptive reweighted sampling (CARS) method was the optimal feature selection method for single sensor estimation and Granger–Ramanathan averaging (GRA) fusion estimation, and the variable importance in projection (VIP) was the optimal feature selection method for direct concatenation and outer-product analysis fusion estimation. In general, the optimal SOM estimation (RMSEp = 3.59 g kg−1, LCCCp = 0.84, RPIQp = 2.67) could be achieved based on CARS feature selection method and GRA fusion. This study proves that the combination of spectral preprocessing and feature selection can effectively improve the accuracy of the single sensor and multi-sensor fusion estimations. Especially, the multi-sensor fusion estimation has higher accuracy than the single sensor estimation. This study will provide a reference for the application of proximal soil sensing.

Using a Two-Stage Scheme to Map Toxic Metal Distributions Based on GF-5 Satellite Hyperspectral Images at a Northern Chinese Opencast Coal Mine

Toxic metals have attracted great concern worldwide due to their toxicity and slow decomposition. Although metal concentrations can be accurately obtained with chemical methods, it is difficult to map metal distributions on a large scale due to their inherently low efficiency and high cost. Moreover, chemical analysis methods easily lead to secondary contamination. To address these issues, 110 topsoil samples were collected using a soil sampler, and positions for each sample were surveyed using a global navigation satellite system (GNSS) receiver from a coal mine in northern China. Then, the metal contents were surveyed in a laboratory via a portable X-ray fluorescence spectroscopy (XRF) device, and GaoFen-5 (GF-5) satellite hyperspectral images were used to retrieve the spectra of the soil samples. Furthermore, a Savitzky–Golay (SG) filter and continuous wavelet transform (CWT) were selected to smooth and enhance the soil reflectance. Competitive adaptive reweighted sampling (CARS) and Boruta algorithms were utilized to identify the feature bands. The optimum two-stage method, consisting of the random forest (RF) and ordinary kriging (OK) methods, was used to infer the metal concentrations. The following outcomes were achieved. Firstly, both zinc (Zn) (68.07 mg/kg) and nickel (Ni) (26.61 mg/kg) surpassed the regional background value (Zn: 48.60 mg/kg, Ni: 19.5 mg/kg). Secondly, the optimum model of RF, combined with the OK (RFOK) method, with a relatively higher coefficient of determination (R2) (R2 = 0.60 for Zn, R2 = 0.30 for Ni), a lower root-mean-square error (RMSE) (RMSE = 12.45 mg/kg for Zn, RMSE = 3.97 mg/kg for Ni), and a lower mean absolute error (MAE) (MAE = 9.47 mg/kg for Zn, MAE = 3.31mg/kg for Ni), outperformed the other four models, including the RF, OK, inverse distance weighted (IDW) method, and the optimum model of RF combined with IDW (RFIDW) method in estimating soil Zn and Ni contents, respectively. Thirdly, the distribution of soil Zn and Ni concentrations obtained from the best-predicted method and the GF-5 satellite hyperspectral images was in line with the actual conditions. This scheme proves that satellite hyperspectral images can be used to directly estimate metal distributions, and the present study provides a scientific base for mapping heavy metal spatial distribution on a relatively large scale.

Geochemical characterization of Jordanian basalts using portable X-ray fluorescence spectrometry and sourcing of the Amman Theater Statue

Despite the prevalence of basalt as a raw material for sculpture, architecture, and artifacts in Iron Age Jordan, geochemical characterization and sourcing of these artifacts to their geologic point of origin is rarely performed, in part due to the lack of a database of geologic basalt sources. In order to address this problem, for this study, geologic basalt samples were collected from Al Hashemiya (A & B), the Wadi Mujib Rim, Baluʿ, Karak, Dana, and Umm Qays and analyzed using an Olympus Vanta portable x-ray fluorescence (pXRF) spectrometer. Previously collected samples from Wadi Zarqa Maʿin that were analyzed by wavelength dispersive x-ray fluorescence (WD-XRF) were also included but were not re-analyzed. Analyses were also conducted on the Amman Theater Statue and results were compared to our compiled data, which determined that the most likely geologic source for this basalt artifact is the source we identify as Al Hashemiya A. By publishing characterization data from these sources, we hope to provide a resource for archaeologists and archaeometrists throughout the region.

Combining Proximal and Remote Sensors in Spatial Prediction of Five Micronutrients and Soil Texture in a Case Study at Farmland Scale in Southeastern Brazil

Despite the increasing adoption of proximal sensors worldwide, rare works have coupled proximal with remotely sensed data to spatially predict soil properties. This study evaluated the contribution of proximal and remotely sensed data to predict soil texture and available contents of micronutrients using portable X-ray fluorescence (pXRF) spectrometry, magnetic susceptibility (MS), and terrain attributes (TA) via random forest algorithm. Samples were collected in Brazil from soils with high, moderate, and low weathering degrees (Oxisols, Ultisols, Inceptisols, respectively), and analyzed by pXRF and MS and for texture and available micronutrients. Seventeen TA were generated from a digital elevation model of 12.5 m spatial resolution. Predictions were made via: (i) TA; (ii) TA + pXRF; (iii) TA + MS; (iv) TA + MS + pXRF; (v) MS + pXRF; and (vi) pXRF; and validated via root mean square error (RMSE) and coefficient of determination (R2). The best predictions were achieved by: pXRF dataset alone for available Cu (R² = 0.80) and clay (R2 = 0.67) content; MS + pXRF dataset for available Fe (R2 = 0.68) and sand (R2 = 0.69) content; TA + pXRF + MS dataset for available Mn (R2 = 0.87) content. PXRF data were key to the best predictions. Soil property maps created from these predictions supported the adoption of sustainable soil management practices.

Congregation leaving the Reformed Church in Nuenen by Vincent van Gogh: a combined multi-instrumental approach to analyse the painting’s stratigraphy in support of varnish removal

Vincent van Gogh’s painting Congregation Leaving the Reformed Church in Nuenen from the collection of the Van Gogh Museum in Amsterdam was executed in 1884 and partially repainted by the artist in 1885. The painting was restored in 1961, however, the details of this treatment were not documented. After being stolen from the museum in 2002 and finally recovered in 2016, the Church was subjected to an extensive technical examination campaign which started in 2017. The aims were to: characterise the stratigraphy of both initial and later paint layers (including identification of the painting materials used by Van Gogh), evaluate the condition of the painting and assess the feasibility of the desired restoration treatment. Portable X-ray fluorescence spectrometry (XRF) was performed to non-invasively identify elements related to pigments in the paint layers of the two painting campaigns. To further identify constituent materials and comprehend the painting’s complex stratigraphy, a single paint sample was collected and embedded in resin for analysis by means of Optical Microscopy, Scanning Electron Microscopy with Energy Dispersive X-ray spectrometry (SEM-EDS) and Fourier Transform Infrared spectrometry - Attenuated Total Reflectance (FTIR-ATR). Additional non-invasive measurements were performed in a MOLAB campaign in 2018 by two complementary and portable analytical techniques: Optical Coherence Tomography (OCT) and reflection FTIR spectroscopy were used to gain further insight into the painting’s stratigraphy and identify surface layers across various regions of the painting. The presence of an original varnish under the paint from 1885 (and therefore likely applied by Van Gogh himself) was revealed by OCT. It was characterised as being protein based by FTIR-ATR and reflection FTIR spectroscopy. Based on the knowledge on the artist’s varnishing practice, it could be concluded that this most likely concerns an egg white varnish for the first time found in an early work by Van Gogh. The upper varnish layer, however, was identified as an alkyd resin applied during the aforementioned 1961 treatment. The combined use of FTIR and OCT enabled non-invasive in situ assessment of solvent cleaning procedures aimed at the selective removal of the 1961 restoration varnish with the preservation of Van Gogh’s original varnish. Specifically, OCT and FTIR analyses were carried out before, during and after each cleaning test to carefully assess the condition of the painted surface and that of the original varnish. The results of the cleaning tests aided in fine-tuning the procedure of varnish removal during the restoration process.

Non-destructive characterisation of dolerite archaeological artefacts

A methodological proposal for the characterisation of dolerite rock aiming to test a non-destructive and non-invasive analytical approach has been developed. Geological samples were collected from several natural outcrops and studied together with seven archaeological stone tools found in a Chalcolithic site of the southern Valencian Community (Spain). The samples were analysed employing portable energy dispersive X-ray fluorescence spectroscopy, Raman microspectroscopy and Fourier transform near infrared spectroscopy. The obtained data were statistically processed in order to evaluate affinities and differences among the geological outcrops and to evaluate the possible provenance of the stone tools. The results of the different techniques were compared and evaluated. The three techniques showed results that were in most of the cases consistent one with each other, suggesting that combining multielement analysis and Raman could be a good way to identify stone tools raw material procurement, being the prior step for the reconstruction of ancient exchange networks.

Exploring the environmental properties and resource utilization of construction waste in Beijing-Tianjin-Hebei region.

Beijing-Tianjin-Hebei region is a capital economic circle for the future. Promoting the coordinated development of its population, economy, resources and environment is a major national strategy. And as towns and cities continue to expand, the volume of construction waste is gradually expanding, posing a major challenge to the sustainable development of the construction industry. In order to solve this problem, this paper used portable X-ray fluorescence spectrometry to realize the on-site rapid monitoring of heavy metals in construction waste, and the correlation analysis result was R2 = 0.9908. The visualization of enrichment factor evaluation results was realized through ArcGIS. The Beijing-Tianjin-Hebei region is mainly polluted by heavy metal elements Cr, Zn, Pb and Hg, showing regional pollution characteristics, and the results of mercury morphology analysis show that all are inorganic mercury pollution, and methylmercury is not detected, and the cause can be traced to heavy industrial production in Tangshan City, which is consistent with industrial ecology. The results of leaching toxicity and cation anion analysis showed that the construction waste in Beijing-Tianjin-Hebei region had environmental risks to the surrounding surface water and groundwater. The resource treatment and disposal path were determined by means of XRD, ternary phase diagram and oxide composition analysis to avoid secondary pollution. This study explores the environmental properties and resource utilization pathways of construction waste in the Beijing-Tianjin-Hebei region, laying the foundation for research work on construction waste in the development of national urban agglomerations, effectively solving regional environmental pollution problems and promoting the sustainable development of the construction industry.

Geochemical study of the Ashele Copper-Zinc Deposit using portable X-ray fluorescence spectrometry based on matrix effect correction, Northwest China

Because the Ashele Cu–Zn deposit is located deep below and core samples are difficult to obtain, portable X-ray fluorescence spectroscopy (pXRF), which can be used for rapid and non-destructive analysis in the field, was chosen as the testing instrument. However, the testing accuracy and precision of elements are significantly affected by matrix effects. In this study, 170 samples from the deposit were measured, and the data was corrected using the matrix effect correction (MEC) method instead of the simple linear regression (SLR) method to enhance the data quality, followed by geochemical and correspondence analysis of the data. The results show that calibration data corrected by the MEC method was of greater quality than those corrected by the SLR method, particularly for elements such as Co, Cr, Mo, Sn, Ba, and W. The Ashele Cu–Zn deposit is formed in multi-phase hydrothermal superposition mineralization and is rich in Mg, Fe, and S but deficient in Al, Si, K, and Ca. The main mineralized zones are located at 400–500 m and 200–300 m. Cu, Zn, and Pb are significantly enriched in the mineralization, with the axial zoning sequence of the primary halo (Pb–Zn–Mn–As–Cu–Cd–Sn–Ba–Bi–Sb–Co–W–Mo) showing inverse zoning. The correspondence analysis results also show a clear distinction between non-metallogenesis and metallogenesis. Also, the application of pXRF based on MEC in the Ashele Cu–Zn deposit is effective and can be extended to other types of deposit studies.

Proximal sensor data fusion and auxiliary information for tropical soil property prediction: Soil texture

• Does combining proximal sensor always bring synergy for predicting soil texture? • Vis-NIR, NixPro TM , and pXRF data were tested for soil texture predictions. • PXRF provided key information to create accurate prediction models. • Smoothed Vis-NIR data preprocessing and dry NixPro TM condition positively influenced the results. • Soil texture and textural classes were accurately predicted by at least one approach. Soil texture is a primary variable influencing many soil chemical-physical-biological processes, providing important information for decision-making regarding sustainable soil management. The standard traditional methods for determining soil texture, however, are performed manually and are time-consuming, costly, and generate chemical wastes. As an alternative, portable X-ray fluorescence (pXRF) spectrometry and visible near-infrared spectroscopy (Vis-NIR) have been increasingly used worldwide to predict soil attributes. Other sensors (e.g., NixPro TM color sensor) are also promising, but less evaluated to date. Thus, investigations towards proximal sensor data fusion for prediction of soil textural separates (clay, silt, and total, coarse, and fine sand contents) and soil textural classes (loam, loamy sand, etc) in tropical soils are rare. Therefore, this study aimed to evaluate proximal sensor data for predicting soil particle size fractions and soil textural classes (both Family particle size classes and USDA soil texture triangle) via random forest algorithm in tropical regions. A total of 464 soil samples were collected from A (n = 208) and B (n = 256) horizons in Brazil. Soil samples were submitted to laboratory analyses for soil texture and proximal sensor (pXRF, Vis-NIR, and NixPro TM ) scanning. Samples were randomly split into 70% for modeling and 30% for validation. The best approach varied according to the predicted attribute; however, pXRF data were key information for soil texture prediction accuracy. The best results delivered highly accurate predictions via the aforementioned proximal sensors for rapid assessment of soil texture (total sand R 2 = 0.84, RMSE = 7.60%; silt 0.83, 6.11%; clay 0.90, 5.64%; coarse sand 0.87, 6.30%; fine sand 0.82, 5.27%). Categorical prediction accuracy for soil textural classes (Family particle size classes, overall accuracy = 0.97, Kappa index = 0.95; USDA soil texture triangle, 0.83, 0.73) was enhanced when the predictions were made by soil order sub-datasets. Smoothed Vis-NIR preprocessing and dry NixPro TM color data positively influenced the results. The results reported here represent alternatives for reducing costs and time needed for evaluating soil texture, supporting agronomic and environmental strategies in Brazilian conditions. Further works should extend the results of this study to temperate regions to corroborate the conclusions presented herein regarding the fusion of these three proximal sensors.

Portable x-ray fluorescence spectroscopy geochemical sourcing of Miocene primate fossils from Kenya

Understanding the biogeography and evolution of Miocene catarrhines relies on accurate specimen provenience. It has long been speculated that some catarrhine specimens among the early collections from Miocene sites in Kenya have incorrect provenience data. The provenience of one of these, the holotype of Equatorius africanus (NHM M16649), was previously revised based on x-ray fluorescence spectroscopy. Here we use nondestructive portable x-ray fluorescence spectroscopy to test the provenience of additional catarrhine specimens that, based on morphology and/or incomplete provenience information, were identified as possibly having been collected at a different site from that recorded at museum accession. We test the hypotheses that two specimens purportedly from the Early Miocene site of Rusinga (KNM-RU 1681 and KNM-RU 1999) are instead from Maboko, three specimens purportedly from the Middle Miocene site of Fort Ternan (KNM-FT 8, KNM-FT 41, and KNM-FT 3318) are instead from Songhor, and one specimen accessioned as being from Songhor (KNM-SO 5352) is from that site. Elemental data reveal that two of the specimens (KNM-FT 3318 and KNM-RU 1681) are likely to have been collected at sites other than their museum-accessioned provenience, while two others (KNM-RU 1999, and KNM-FT 41) were confirmed to have correct provenience. Results for both KNM-FT 8 and KNM-SO 5352, while somewhat equivocal, are best interpreted as supporting their accessioned provenience. Our results have implications for the distribution of certain catarrhine species during the Miocene in Kenya. Confirmation of the provenience of the specimens also facilitates taxonomic attribution, and resulted in additions to the morphological characterizations of some species. The protocol presented here has potential for wider application to assessing questions of provenience for fossils from other locations and periods.

Distinguishing Genuine Imperial Qing Dynasty Porcelain from Ancient Replicas by On-Site Non-Invasive XRF and Raman Spectroscopy.

The combined use of non-invasive on-site portable techniques, Raman microscopy, and X-ray fluorescence spectroscopy on seven imperial bowls and two decorated dishes, attributed to the reigns of the Kangxi, Yongzheng, Qianlong, and Daoguang emperors (Qing Dynasty), allows the identification of the coloring agents/opacifiers and composition types of the glazes and painted enamels. Particular attention is paid to the analysis of the elements used in the (blue) marks and those found in the blue, yellow, red, and honey/gilded backgrounds on which, or in reserve, a floral motif is principally drawn. The honey-colored background is made with gold nanoparticles associated with a lead- and arsenic-based flux. One of the red backgrounds is also based on gold nanoparticles, the second containing copper nanoparticles, both in lead-based silicate enamels like the blue and yellow backgrounds. Tin and arsenic are observed, but cassiterite (SnO2) is clearly observed in one of the painted decors (dish) and in A676 yellow, whereas lead (calcium/potassium) arsenate is identified in most of the enamels. Yellow color is achieved with Pb-Sn-Sb pyrochlore (Naples yellow) with various Sb contents, although green color is mainly based on lead-tin oxide mixed with blue enamel. The technical solutions appear very different from one object to another, which leads one to think that each bowl is really a unique object and not an item produced in small series. The visual examination of some marks shows that they were made in overglaze (A608, A616, A630, A672). It is obvious that different types of cobalt sources were used for the imprinting of the marks: cobalt rich in manganese for bowl A615 (Yongzheng reign), cobalt rich in arsenic for bowl A613 (but not the blue mark), cobalt with copper (A616), and cobalt rich in arsenic and copper (A672). Thus, we have a variety of cobalt sources/mixtures. The high purity of cobalt used for A677 bowl indicates a production after ~1830–1850.

Home and community composts in Nantes city (France): quality and safety regarding trace metals and metalloids.

Home and community composting are key strategies for local organic waste management. The quality and safety of industrial composts are controlled, but those of home and community composts are not, and this could make them unsafe for use in kitchen gardens. Home (n = 20) and community (n = 41) composts, from urban and suburban areas including mildly Pb-contaminated allotment gardens, were analyzed for quality and safety regarding trace metals and metalloids (TMM) using mid-infrared Fourier transform spectrometry (FT-MIR) and portable X-ray fluorescence spectrometry, respectively. Home composts had a significantly higher Pb content (98mg.kg-1 ± 10mg.kg-1) than community composts (21mg.kg-1 ± 2mg.kg-1). Numerous home composts (85%) and a few community composts (17%) exceeded the organic farming thresholds for Pb (45mg.kg-1) and Zn (100mg.kg-1). The high mineral matter content and the relative abundance of chemical functions attributable to silicates (up to 35%) highly paralleled with TMM contents, mostly concentrated in the fine fraction. Co-inertia analysis highlighted strong and significant links between TMM contents and the whole chemical signature delivered by FT-MIR spectrometry. Pb-contaminated soil could be carried into home compost by green waste or by voluntary addition. Covariance analyses indicated that mineral matter and chemical functions only partly explained the variability in Pb content, suggesting a more complex combination of drivers. Community composting appears as a suitable local solution resulting in high-quality compost that complies with European organic farming regulations, while home composting from allotment gardens should be seriously evaluated to comply with such safety requirements.

Fusion of Gamma-rays and portable X-ray fluorescence spectral data to measure extractable potassium in soils

The detection and mapping of plant-extractable potassium (Ka) using proximal soil sensing and data fusion (DF) techniques are essential to optimise K2O fertiliser application, improve crop yield, and minimise environmental and financial costs. This work evaluates the potential of combined use of portable gamma ray and x-ray fluorescence spectroscopy for in field detection and mapping of Ka. After subjected to various pre-processing methods, spectral data were split into calibration (75%) and validation (25%) sets, and single sensor and DF models were developed using partial least squares regression (PLSR). Maps of Ka were used to present spatial variability of potassium across an 8.4 ha Voor de Hoeves target field, in Flanders, Belgium. Results showed that the gamma-ray PLSR model using wet soils had greater predictive ability with coefficient of determination (R2) = 0.71, ratio of performance deviation (RPD) = 1.89, root mean square error (RMSE) = 31.7 mg kg-1, and ratio of performance to interquartile range (RPIQ) = 2.36 than the corresponding wet-XRF PLSR model (R2 = 0.61, RPD = 1.64, RMSE = 48.8 mg kg-1 and RPIQ = 1.84). The DF PLSR model on wet soils, resulted in a more accurate Ka predictive ability (R2 = 0.75, RPD = 2.03, RMSE = 31.3 mg kg-1 and RPIQ = 2.79), compared to the individual gamma ray or XRF sensors in wet soils. The best accuracy was obtained with XRF spectrometer using dry samples (R2 = 0.77, RPD = 2.14, RMSE = 26.5 mg kg-1 and RPIQ = 3.39). All Ka prediction maps showed spatial similarity to the corresponding measured maps in the target field. In conclusion, since DF increased the Ka prediction accuracy compared to the single sensor models using wet soils, it is recommended to be adopted in future studies as a potential solution for Ka measurement, mapping, and ultimately for site-specific K2O fertilisation management. The XRF analysis of dry spectra is recommended as the best method for accurate measurement of Ka.

Influence of auxiliary soil variables to improve PXRF-based soil fertility evaluation in India

Portable X-ray fluorescence (PXRF)spectrometry has already been established as a rapid and cost-effective tool for predicting various soil physicochemical properties. This study used PXRF in combination with physiographic, agro-climatic, soil parent-material, and physicochemical attributes (pH, electrical conductivity (EC), loss on ignition organic matter, and organic carbon) as auxiliary properties to predict multiple soil fertility indicators [available K, Ca, Mg, Fe, Cu, Zn, Mn, B, K/Mg ratio, total exchangeable bases (TEB), and sulfur availability index (SAI)] via four machine-learning algorithms (random forest, support vector regression, stepwise multiple linear regression, and an averaged model). Principal component analysis (PCA) indicated the links between PXRF-reported elements, agro-climatic zones, and soil parent materials. Although no universal prediction model can be selected to suit all 11 soil fertility parameters, three parameters (available Ca, Fe, and TEB) produced reasonable model performance with an R2 > 0.50 for most prediction model-dataset combinations. Concatenation of auxiliary soil parameters with PXRF data showed relative improvement in model accuracy compared to PXRF in isolation. Notably, the agro-climatic zone appeared influential for predicting available K, Mg, Zn, Fe, Mn, B, K/Mg ratio, and TEB. For potential fertilizer recommendation, six parameters (available K, Ca, Mg, Cu, Mn, and B) produced reasonable classification performance via the averaged model using all auxiliary predictors (κ > 0.30). The same categorical model was used, as an instance, for delineating a conceptualized framework for (PXRF+ auxiliary properties)-based fertilizer recommendation facilitating site-specific nutrient management. More research is needed to enhance model prediction/classification accuracy by including a well-balanced dataset and other relevant auxiliary variables with PXRF. Nevertheless, the importance of adding auxiliary soil properties with PXRF elemental data for cost-effective and accessible nutrient management in resource-poor countries seems promising.

Archaeometallurgical Analysis of Lead Weights and Sling Bullets from Seleucid Tell Iẓṭabba: More on Lead Origin in Seleucid Palestine

Lead isotope and portable energy-dispersive X-ray fluorescence spectrometry were applied to a small group of Hellenistic lead objects from Tell Iztabba (Beth Shean, Israel). The market weights and sling bullets from this short-lived Seleucid-founded site were analysed in order to understand their production process and the provenance of the raw materials. The sling bullets are of pure lead, and its lead isotopic signature suggests that the lead was produced from Lavrion ores. The weights are heterogeneous in composition and point to the use of mixed or reused scrap metal. Anatolian or Aegaean lead ores are the raw material sources for the weights. Whether the sling bullets belonged to the defenders of the site or to the attackers cannot be determined from the analysis, but their Greek provenance together with the fact that they were recovered at the site may suggest their use by its defenders.

The Meteoritic Origin of Morocco Iron Dagger Blades

Up until now, a few artifacts made of meteoritic iron have been discovered worldwide, though none in Morocco. The number of these objects has rarely been verified, as museums generally do not allow artifacts to be tested, and they are often confused with common smelted objects of the Iron Age. In this work, portable X-ray fluorescence (pXRF) and scanning electron microscopy-energy dispersive X-ray spectroscopy (SEM-EDS) have been used to analyze three iron dagger blades recovered in two localities near Imilchil and Missour in Morocco. The composition of one blade (7.2 wt% Ni and 1.1 wt% Co) strongly supports its meteoritic origin, whereas it was not so for the other two ones. The results of this work provide the first case of the exploitation of meteoritic iron as a metal source in Morocco.

Multi-analytical Study on the Tara Thangka at Daxingshan Temple in Xi'an, Shaanxi, China

ABSTRACT In this study, a Tara thangka (from a complete set of 21) dating to the mid-Qing Dynasty (1776–1839 CE) at Daxingshan Temple in Xi'an, Shaanxi, China was analyzed using various techniques, including portable X-ray fluorescence spectroscopy (p-XRF), Raman spectroscopy (RS), Fourier transform infrared spectroscopy (FTIR), optical microscopy (OM), and mass spectrometry-based proteomics. Through a multi-analytical methodology, in situ non-invasive testing was complemented with an analysis of a limited number of samples. By complementary evidence derived from the above analyses, it can be determined that the thangka was painted on a hemp substrate, with common colorants such as cinnabar, orpiment, gold, azurite, and malachite, and porcine glue as binding material. These results provided important scientific data for the production crafts of the precious Tara thangkas, contributing to the revelation of its value in art history and enabling conservators to make informed conservation decisions.