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In this paper, we present the potential of Terahertz Time-Domain Imaging (THz-TDI) as a tool to perform non-invasive 3D analysis of an ancient enamel plate manufactured by Longwy Company in France. The THz data collected in the reflection mode were processed using noise filtering procedures and an advanced imaging approach. The results validate the capability to identify glaze layers and the thickness of ceramic materials. To characterize the nature of the pigments, we also use with X-ray images, visible near-infrared hyperspectral imaging spectroscopy, and p-XRF (portable X-ray fluorescence) to qualitatively and quantitively identify the materials used. The obtained information enables a better understanding of the decoration chromogens nature and, thus, to determine the color palette of the artists who produced such decorative object. We also establish the efficiency of a focus, Z-tracker, which enables to perform THz imaging on non-flat samples and to attenuate artifacts obtained with a short focus lens. Then, 3D images are extracted and generated, providing a real vision. We also report the evaluation of the internal damage state through the detection of fractures.

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The investigation of ancient artifacts is often constrained by their scarce availability and high protection and custody protocols. Among these, coinage represents an especially valuable kind-of-samples given their uniqueness and the subjacent information that is hidden behind their composition. Their analysis are often carried out using non-destructive techniques in order to avoid any alteration of the samples. In the field of Cultural Heritage analysis, smartphone-based methodologies have experienced a significant increase during the last few years, given their wide availability and ability to yield fast results. However, their analytical application demands a thorough and careful tuning during the methodology optimization. In this work, 21 historical gold and golden coins spanning a historical period of more than 2000 years have been analytically investigated. To that end, a two-fold approach has been implemented: first, the elemental composition has been analysed using portable X-ray fluorescence; and second, an innovative smartphone-based imaging method has been applied to measure their colour. Results allowed to describe the coins from their elemental profile, identifying some potentially debased ones, as well as some others not containing any gold. When possible, the results have been compared to previously reported cases, but our samples include some previously unreported cases representing new insights. All in all, this article provides new analytical data on unanalysed unique historical samples, in terms of their elemental profile and colorimetric properties, making use of an innovative, non-invasive nor destructive, fast and affordable colorimetric smartphone-based method to characterise historical coins.

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Chinese porcelain with an optically clear colored glaze, imported to Europe from the Kangxi period (1662-1722, Qing Dynasty) onwards was highly collected by the French Elite of the 18th century. The bright colors with a clear, shiny glaze were unlike anything produced in Europe at that time. The colors of enamelled artifacts (on biscuits or already glazed porcelain) can be fully monochrome or consist of associations of large monochromatic areas with or without application of gilding. Non-invasive portable XRF and mobile Raman analyses have previously shown their effectiveness in the characterization of (colored) glassy silicates. In this study, we compare the Raman signatures of twenty-one Chinese artifacts fully-or with major monochrome area (sancai)-decorated with blue, turquoise (or celectian blue), honey-yellow, green, eggplant, and red color. Different types of glazes are identified and confirmed by pXRF: lead-rich, lead-poor-alkali, lead-doped alkali, and alkali-based compositions. However, an unexpected low level of lead is observed in the turquoise glazes, likely to optimize the gloss. Raman spectroscopy appears more reliable to compare the Pb content than pXRF. This work presents Raman spectral signatures of glazes that can potentially be used for non-invasive object classification and counterfeit detection.

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Marginalized communities experience barriers that can prevent soil monitoring efforts and knowledge transfer. To address this challenge, this study compared two analytical methods: portable X-ray fluorescence spectroscopy (pXRF, less time, cost) and inductively coupled plasma mass spectrometry (ICP-MS, "gold standard"). Surface soil samples were collected from residential sites in Arizona, USA (N = 124) and public areas in Troy, New York, USA (N = 33). Soil preparation differed between groups to account for community practice. Statistical calculations were conducted, paired t test, Bland-Altman plot, and a two-way ANOVA indicated no significant difference for As, Ba, Ca, Cu, Mn, Pb, and Zn concentrations except for Ba in the t test. Iron, Ni, Cr, and K were statistically different for Arizona soils and V, Ni, Fe, and Al concentrations were statistically different for New York soils. Zinc was the only element with high R2 and low p value. Pollution load index (PLI), enrichment factors (EF), and geo-accumulation index (Igeo) were calculated for both methods using U.S. Geological Survey data. The PLI were > 1, indicating soil pollution in the two states. Between pXRF and ICP-MS, the Igeo and EF in Arizona had similar degree of contamination for most elements except Zn in garden and Pb in yard, respectively. For New York, the Igeo of As, Cu, and Zn differed by only one classification index between the two methods. The pXRF was reliable in determining As, Ba, Ca, Cu, Mn, Pb, and Zn in impacted communities. Therefore, the pXRF can be a cost-effective alternative to using ICP-MS techniques to screen soil samples for several environmentally relevant contaminants to protect environmental public health.

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X-ray fluorescence is a fast, cost-effective, and eco-friendly method for elemental analyses. Portable X-ray fluorescence spectrometers (pXRF) have proven instrumental in detecting metals across diverse matrices, including plants. However, sample preparation and measurement procedures need to be standardized for each instrument. This study examined sample preparation methods and predictive capabilities for nickel (Ni) concentrations in various plants using pXRF, employing empirical calibration based on inductively coupled plasma optical emission spectroscopy (ICP-OES) Ni data. The evaluation involved 300 plant samples of 14 species with variable of Ni accumulation. Various dwell times (30, 60, 90, 120, 300 s) and sample masses (0.5, 1.0, 1.5, 2.0 g) were tested. Calibration models were developed through empirical and correction factor approaches. The results showed that the use of 1.0 g of sample (0.14 g cm-2) and a dwell time of 60 s for the study conditions were appropriate for detection by pXRF. Ni concentrations determined by ICP-OES were highly correlated (R2 = 0.94) with those measured by the pXRF instrument. Therefore, pXRF can provide reliable detection of Ni in plant samples, avoiding the digestion of samples and reducing the decision-making time in environmental management.

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Soil contamination in outdoor shooting ranges (OSRs) is a major threat for human health, particularly when, after the end of activities, the land is used for recreational areas or agricultural production. The status of land degradation of an OSR in southern Italy was assessed using a multisensor approach. It was based on: i) proximal sensors, including electromagnetic induction (EMI) for measuring soil electrical conductivity (ECa) and magnetic susceptibility (MSa), γ-ray spectrometry for K, eU and eTh analyses and ultrasonic penetrometry detecting cone index (CI) data representative of soil's strength, ii) field surveys on soil thickness (ST), and iii) laboratory analyses of potentially-toxic-elements (PTEs) by portable X-ray fluorescence spectrometry and polycyclic aromatic hydrocarbons (PAHs) by gas-chromatography. Spatial variability of measurements was modelled and mapped using geostatistical methods. The most densely measured covariate (i.e., the ECa of the topsoil) was used within kriging with external drift to improve the PTEs predictions. The PTEs maps were complemented by maps of spatial uncertainty. A robust multivariate principal component analysis (rPCA) was applied to proximal sensor and laboratory data and allowed to identify associations of PAHs, lead, CI with the topsoil ECa along the first component (PC1), highlighting the correlation between land anthropogenic effects and EMI measures; while the association between the ST (estimating the depth of underground travertine hard-layers) and the bottom soil ECa and MSa along the second component (PC2) evidenced the influence of soil stratigraphy on the EMI measures. This study demonstrates that the simultaneous use of different proximal sensors associated with laboratory analysis can allow to assess and model the spatial variability of the land degradation status of an OSR, including soil compaction, organic and inorganic contamination. The correlation between EMI data with the PTEs content highlights the potential of this technique in the field of soil contamination.

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This study evaluated the reliability of portable X-ray fluorescence (pXRF) in Pb2+adsorption kinetics and isotherm experiments using soybean straw biochar. The research aimed to compare pXRF results with those obtained through traditional atomic absorption spectrometry (AAS). Soybean straw biochar, produced at 400 °C, was employed as the adsorbent for Pb2+. The efficiency of adsorption was assessed using Langmuir and Freundlich models. The kinetics of Pb2+adsorption was analysed through pseudo-first-order and pseudo-second-order models. The pseudo-second-order model described the kinetics of Pb2+adsorption on biochar better than the pseudo-first order model. Importantly, the pXRF technique demonstrated comparable results to those of AAS, making it a reliable and resource-efficient method for studying Pb2+kinetics. The results of the isotherm analyses fit the Langmuir model, indicating a desirable and irreversible adsorption of Pb2+on biochar. PXRF measurements on biochar allowed simultaneous observations of Pb2+adsorption and K+and Ca2+desorption, highlighting ionic exchange as the primary adsorption mechanism. In conclusion, our results showcased the applicability of pXRF for Pb+2adsorption studies in biochars, offering a valuable alternative to traditional methods. The findings contribute to the understanding of biochar as an effective adsorbent for heavy metals, emphasizing the potential of pXRF for cost-effective and efficient environmental research. In this study, we present a novel and detailed procedure that will allow other researchers to continue their studies on Pb2+adsorption on biochar or similar matrices, significantly reducing the resources and time used and enabling the simultaneous study of the behavior of other ions participating in the process.

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Plastic and rubber granules are commonly used as infill material in all-weather sports facilities, providing an ideal activity surface for millions of Europeans on a daily basis. However, concerns have been raised about the presence of hazardous elements in these granules, which can pose risks both to the environment and human health. Our study focusses on the elemental composition of rubber granules used in fall sports facilities in Rzeszów, (Podkarpackie, Poland) using field portable X-ray fluorescence (FP-XRF) as a non-destructive and 'white analytical technique'. The results show the content of Zn, Fe, Cr, Ba, Br, Ti, Cu, Cd, As, Au, Bi, Pb, Ni, Sb, and Sn in the rubber granule samples. This study highlights the need for stringent quality control measures and regulations to ensure the safety of all-weather sports facilities and protect the well-being of sportsman. When modern FP-XRF spectrometry is employed as a "white analytical technique," for the first time it becomes possible to identify the presence of hazardous elements, addressing the pressing concerns highlighted by the ECHA and enabling proactive measures to mitigate potential risks. This approach ensures the protection of the health and sustainability of sports facilities, contributing to the ongoing hot topics in the field.

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In the Minier Valley (France, Aveyron), an archaeological site excavation has led to the discovery of 25 kg of lead (Pb) slag, found in a secondary position. On a macroscopic level, these slags can be classified into two distinct categories, vitreous black and porous gray. This clear visual differentiation has been previously documented at other Pb-silver (Ag) metallurgy sites dating from the 12th century to the 14th century in Europe, and more particularly in the workshops of Mont Lozère, located approximately 80 km away from Le Minier. However, to date, scant evidence exists regarding the specific metallurgical process that produced this slag. This study presents the results of the analysis of 218 Pb slags (Supplemental Material) using portable X-ray fluorescence (pXRF). This method does not appear to be ideally suited for investigating this type of artifact, as it does not provide quantification of oxygen content. Nevertheless, it can be used to quickly identify trends and determine whether the two identified facies exhibit dissimilar chemical compositions. The results indicate that, based on the elemental compositions of the slags, no discernible distinction can be made to categorize them into two separate groups, both in bivariate and multivariate analyses. Consequently, it can be inferred that the gray and black slags originate from a single process executed within the same type of furnace. Scanning electron microscopy energy dispersive spectrometry analyses on selected samples demonstrate that variations in metal content are considerably exaggerated by pXRF, but that the trends observed are confirmed. The use of pXRF is therefore a relevant tool for determining whether or not Pb-Ag slag is the result of the same process. However, this initial approach needs to be refined by other analyses to confirm whether the smelted ores are of local origin and to be able to better define the details of the metallurgical process used.

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Environmental Justice (EJ) communities may experience barriers that can prevent soil monitoring efforts and knowledge transfer. To address this gap, this study compared two analytical methods: portable X-ray Fluorescence Spectroscopy (pXRF, less time and costs) and Inductively Coupled Plasma Mass Spectrometry (ICP-MS, "gold standard"). Surface soil samples were collected from yards and gardens in three counties in Arizona, USA (N=124) and public areas in Troy, New York, USA (N=33). Statistical calculations, i.e., two-sample t-tests, Bland-Altman plots, and a two-way ANOVA indicated no significant difference for As, Ba, Ca, Cu, Mn, Pb, and Zn concentrations except for Ba in the two-sample t-test. Iron, Ni, Cr, and K were statistically different for Arizona soils and V, Ni, Fe and Al concentrations were statistically different for New York soils. To assess the degree of contamination, a pollution load index (PLI), enrichment factors (EF), and geo-accumulation index (Igeo) were calculated for both methods using U.S. Geological Survey soils data. The PLI were >1, indicating pollution across the two states. Between pXRF and ICP-MS, the Igeo and EF in Arizona had similar degree of soil contamination for most elements except Zn in garden and Pb in yard, respectively. In New York, the Igeo of As, Cu, and Zn differed by an order of magnitude between the two methods. The results of this study demonstrate that pXRF is a reliable method for the inexpensive and rapid analysis of As, Ba, Ca, Cu, Mn, Pb, and Zn. Thus, EJ communities may use pXRF to screen large numbers of soil samples for several environmentally relevant contaminants to protect environmental public health.

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Urban forest soils perform important ecosystem services, such as the sequestration of potentially toxic elements, but some can serve as a source for human exposure if ingested or eroded by wind. Assessment of trace elements in urban soils through traditional methods is costly but portable X-ray fluorescence (pXRF) can allow for rapid screening for hazardous concentrations. Our objectives were (1) evaluate trace elements (As, Cd, Cr, Cu, Pb, and Zn) at 460 locations in and around urban forests across three town and cities in New England and across multiple land-uses, (2) evaluate accuracy and precision of pXRF compared with traditional digestion-inductively coupled plasma analyses, (3) determine if pXRF measurements are improved by processing the soil (oven drying, rock fragment removal, and organic matter (OM) removal). Our findings show that urban forest soils have extensive Pb accumulations (42 out of 460 with >200 mg/kg), while As and Zn exceeded regulatory limits in limited outlier samples. Urban forest soils adjacent to multi-family residences have higher Pb and Zn concentrations than recreational and open lots. Fortunately, Cd, Cr, and Cu were far below hazardous concentrations. Our comparisons suggest pXRF measurements of Cu, Pb, and Zn can be considered accurate while Cd and Cr may be screened by pXRF. However, As should not be considered qualitative nor quantitative due to 70% type 1 (false positive) error on samples. While the accuracy and precision were nominally improved through soil drying, removal of rock fragments, and removal of OM (<5% decrease in relative error), our results show processing soil samples is likely not needed.

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Seafood elemental profiling (SEP) is the quantification of a range of elements in seafood products and may serve in addressing questions of seafood provenance and quality. Traditional methods for analyzing soft tissue present several limitations for the industry-level use of SEP. Portable handheld X-ray fluorescence (pXRF) analysis is a promising alternative to conventional methods; however, its application for biological analysis has not been fully established. Intact giant tiger prawn (Penaeus monodon) abdomens were analyzed with a Vanta M series XRF portable analyzer following a novel soft tissue protocol. Exploratory statistics (principal component analysis, nonmetric multidimensional scaling, and canonical discriminant analysis), as well as random forest models, have been implemented with pXRF profiles, yielding 81% accuracy when assigning the geographical origin of P. monodon. The results of this study highlight that SEP via pXRF is a viable industry-level analysis, and its application will depend on improved instrument calibration to account for fluctuating wetness factors that are influenced by cooking, storage, and other pre- and post-harvest treatments.

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Farms use large quantities of fertilizers from many sources, making quality control a challenging task, as the traditional wet-chemistry analyses are expensive, time consuming and not environmentally-friendly. As an alternative, this work proposes the use of portable X-ray fluorescence (pXRF) spectrometry and machine learning algorithms for rapid and low-cost estimation of macro and micronutrient contents in mineral and organic fertilizers. Four machine learning algorithms were tested. Whole (i.e., as delivered by the manufacturer) (CP) and ground (AQ) samples (429 in total) were analyzed to test the effect of fertilizer granulometry in prediction performance. Model validation indicated highly accurate predictions of macro (N: R2 = 0.92; P: 0.97; K: 0.99; Ca: 0.94, Mg: 0.98; S: 0.96) and micronutrients (B: 0.99; Cu: 0.99; Fe: 0.98; Mn: 0.91; Zn: 0.94) for both organic and mineral fertilizers. RPD values ranged from 2.31 to 9.23 for AQ samples, and Random Forest and Cubist Regression were the algorithms with the best performances. Even samples analyzed as they were received from the manufacturer (i.e., no grinding) provided accurate predictions, which accelerate the confirmation of nutrient contents contained in fertilizers. Results demonstrated the potential of pXRF data coupled with machine learning algorithms to assess nutrient composition in both mineral and organic fertilizers with high accuracy, allowing for clean, fast and accurate quality control. Sensor-driven quality assessment of fertilizers improves soil and plant health, crop management efficiency and food security with a reduced environmental footprint.

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The illegal wildlife trade is a significant threat to global biodiversity, often targeting already threatened species. In combating the trade, it is critical to know the provenance of the traded animal or part to facilitate targeted conservation actions, such as education and enforcement. Here, we present and compare two methods, portable X-ray fluorescence (pXRF) and stable isotope analysis (SIA), to determine both the geographic and source provenance (captive or wild) of traded animals and their parts. Using three critically endangered, frequently illegally traded Philippine species, the Palawan forest turtle (Siebenrockiella leytensis), the Philippine cockatoo (Cacatua haematuropygia), and the Philippine pangolin (Manis culionensisis), we demonstrate that using these methods, we can more accurately assign provenance using pXRF data (x¯ = 83%) than SIA data (x¯ = 47%). Our results indicate that these methods provide a valuable forensic tool that can be used in combating the illegal wildlife trade.

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Following the Fundão dam failure in Brazil, 60 million m3 of iron-rich tailings were released impacting an extensive area. After this catastrophe, a detailed characterization and monitoring of iron-rich tailings is required for agronomic and environmental purposes. This can be facilitated by using proximal sensors which have been an efficient, fast, and cost-effective tool for eco-friendly analysis of soils and sediments. This work hypothesized that portable X-ray fluorescence (pXRF) spectrometry combined with a pocket-sized (Nix™ Pro) color sensor and benchtop magnetic susceptibilimeter can produce substantial data for fast and clean characterization of iron-rich tailings. The objectives were to differentiate impacted and non-impacted areas (soils and sediments) based on proximal sensors data, and to predict attributes of agronomic and environmental importance. A total of 148 composite samples were collected on totally impacted, partially impacted, and non-impacted areas (natural soils). The samples were analyzed via pXRF to obtain the total elemental composition; via Nix™ Pro color sensor to obtain the red (R), green (G), and blue (B) parameters; and assessed for magnetic susceptibility (MS). The same samples used for analyses via the aforementioned sensors were wet-digested (USEPA 3051a method) followed by ICP-OES quantification of potentially toxic elements. Principal component analysis was performed to differentiate impacted and non-impacted areas. The pXRF data alone or combined with other sensors were used to predict soil agronomic properties and semi-total concentration of potentially toxic elements via random forest regression. For that, samples were randomly separated into modeling (70%) and validation (30%) datasets. The pXRF proved to be an efficient method for rapid and eco-friendly characterization of iron-rich tailings, allowing a clear differentiation of impacted and non-impacted areas. Also, important soil agronomic properties (clay, cation exchange capacity, soil organic carbon, pH and macronutrients availability) and semi-total concentrations of Ba, Pb, Cr, V, Cu, Co, Ni, Mn, Ti, and Li were accurately predicted (based upon the lowest RMSE and highest R2 and RPD values). Sensor data fusion (pXRF + Nix Pro + MS) slightly improved the accuracy of predictions. This work highlights iron-rich tailings from the Fundão dam failure can be in detail characterized via pXRF ex situ, providing a secure basis for complementary studies in situ aiming at identify contaminated hot spots, digital mapping of soil and properties variability, and embasing pedological, agricultural and environmental purposes.

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Portable energy-dispersive X-ray fluorescence spectroscopy (pXRF) was employed in the characterization of the pigments present in the painting "Still Life with Vase, Plate and Flowers", of unknown authorship, but previously attributed to Vincent van Gogh, belonging to the collection of the São Paulo Museum of Art (MASP). In situ pXRF measurements were carried out by means of a portable system in order to provide the museum with a scientific documentation about the materials in the painting. Spectra were taken at different color regions and different hues in the pictorial layer. Some of the materials identified in the painting were chalk and/or gypsum, lithopone, lead white, zinc white, bone black, barium yellow, chrome yellow, yellow ochre, chrome green, Prussian blue, cobalt blue, vermilion and red earth. Besides that, it was possible to suggest the use of a lake pigment. The pigments whose use is suggested by this work are in total agreement with those available to European artists in the end of the 19th century.

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Several materials have been characterized using proximal sensors, but still incipient efforts have been driven to plant tissues. Eucalyptus spp. cultivation in Brazil covers approximately 7.47 million hectares, requiring faster methods to assess plant nutritional status. This study applies portable X-ray fluorescence (pXRF) spectrometry to (i) distinguish Eucalyptus clones using pre-processed pXRF data; and (ii) predict the contents of eleven nutrients in the leaves of Eucalyptus (B, Ca, Cu, Fe, K, Mg, Mn, N, P, S, and Zn) aiming to accelerate the diagnosis of nutrient deficiency. Nine hundred and twenty samples of Eucalyptus leaves were collected, oven-dried, ground, and analyzed using acid-digestion (conventional method) and using pXRF. Six machine learning algorithms were trained with 70% of pXRF data to model conventional results and the remaining 30% were used to validate the models using root mean square error (RMSE) and coefficient of determination (R2). The principal component analysis clearly distinguished developmental stages based on pXRF data. Nine nutrients were accurately predicted, including N (not detected using pXRF spectrometry). Results for B and Mg were less satisfactory. This method can substantially accelerate decision-making and reduce costs for Eucalyptus foliar analysis, constituting an ecofriendly approach which should be tested for other crops.

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Ca and Mg are the most important chemical elements in lime. Properly measuring Ca and Mg contents is essential to assess the quality of lime products. Quality control guarantees the adequate use of lime in industrial processes, in soils, and helps avoiding adulteration. Proximal sensors can aid in this process by determining Ca and Mg contents easily, rapidly and without producing chemical waste. The objective of this study was to evaluate the use an environmentally-friendly method of analyzing the quality of lime. We studied 1) the use of portable X-ray fluorescence (pXRF) to predict concentrations of Ca and Mg in lime, 2) tested if NixPro™ sensor can improve prediction accuracy and 3) tested if sample preparation methods (grinding) affect analyses. 74 samples of lime were analyzed by two different laboratories (lab. 1 = 38, lab. 2 = 36). All samples submitted to pXRF and NixPro™ analyses. Sensor analyses were done in whole (CP) and ground (AQ) samples to test the effect of sample preparation in prediction performance. High correlation was found between Ca and Mg contents measured via pXRF and laboratory analyses. Mg-CP presented the highest correlation coefficient (r = 0.81); Mg-AQ, the lowest (0.57). Predictions presented good performance (R2 > 0.68); Mg had the best results (0.86). Separating models per laboratory showed that some datasets are harder to model, probably due to variability in the source material (limestone). The addition of NixPro™ data contributed to improve prediction accuracy, although slightly. Predictions using CP samples presented the best results, especially for Mg, indicating that grinding is not necessary. This pioneer study demonstrated that fused proximal sensors can be used to rapidly and easily determine contents of Ca and Mg in soil amendments without producing chemical waste.

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The rapid development of the smelting industry increases the release of antimony (Sb) into the soil environment, which threatens human health and ecosystems. A total of 87 samples were collected from an abandoned Sb smelting site to evaluate pollution characteristics and environmental risks of the potentially toxic elements (PTEs). The contents of As, Cu, Ni, Pb, Sb, and Zn in the fresh soils determined by P-XRF were 131, 120, 60, 145, 240, and 154 mg/kg, respectively, whilst following drying, grinding, and sieving pretreatments, the corresponding contents increased to 367, 179, 145, 295, 479, and 276 mg/kg, respectively. There was a significant correlation between the data obtained by P-XRF and ICP-OES in the treated samples, which showed the application feasibility of P-XRF. The average contents of Sb and As were 440.6 and 411.6 mg/kg, respectively, which exceeded the control values of the development land in GB 36600-2018. The ecological risk levels of the six PTEs decreased in the following order: As > Sb > Pb > Zn > Ni > Cu. Non-carcinogenic risk revealed that As, Pb, and Sb posed health risks for children, whilst for carcinogenic risk, the risk values for As and Ni were higher than the limit values for both children and adults. Anthropogenic sources accounted for more than 70.0% of As, Pb, and Sb concentrations in soils, indicating a significant influence on PTEs accumulation. The findings provide a basis for quick determination of the contamination characteristics and risk control of PTEs at Sb smelting sites.

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Lead adulteration of spices, primarily via Pb chromate compounds, has been documented globally as a growing public health concern. Currently, Pb detection in spices relies primarily on expensive and time-consuming laboratory analyses. Advancing rapid Pb detection methods, inclusive of their accuracy and precision, would improve field assessments by food safety inspectors, stakeholders, and the public in the hope of reducing Pb exposure risks at its source. Here, we present two field procedures for Pb detection: portable X-ray fluorescence analysis (pXRF) and a simple colorimetric test. We assess their efficacy to detect Pb and its chemical form in seven spice types, including powders, spice-salt mixtures, and dried roots, compared to the proven laboratory technique, inductively coupled plasma mass spectrometry (ICP-MS). Lead concentrations measured using pXRF and ICP-MS were within 5% of each other for spice powders and 24% for dried roots. By pXRF, spice samples were analyzed within collection plastic bags without preparation, resulting in a detection limit of 2 mg Pb/kg for spice powders, which is comparable to national food standards. The colorimetric test utilized here targets hexavalent chromium, making the method selective to Pb chromate adulteration assuming that this is its dominant source in spices. Color development, and thus detection, was observed when Pb concentrations exceeded approximately 5-70 mg/kg in dried turmeric roots and 1000 mg/kg in spice powders; however, it was ineffective for the spice-salt mixture. We show that pXRF analysis and a colorimetric assay provide information that may improve field decisions about Pb adulteration in a range of spice types, helping to minimize Pb exposure.

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