Detection of adulteration in Eragrostis tef (Zucc.) Trotter flour using EDXRF and ComDim-MLR data fusion.

The teff cereal gained worldwide attention because it is gluten-free and rich in iron; thus, its flour is subject to fraud. This study evaluated the ability of Energy Dispersive X-Ray Fluorescence Spectroscopy (EDXRF) to identify teff flours adulterated with rice, whole wheat, oat, and rye flours. The adulteration followed a {5,4} simplex-lattice design. After smoothing and pretreatments, 15 kV and 50 kV spectra were fused by Common Dimension Analysis (ComDim). Multiple Linear Regression (MLR) models using EDXRF-ComDim scores and percentage of teff were adjusted. The best model presented four common dimensions (CD), r2prediction = 0.8534, low RMSEP (0.0564), and absence of overfitting. The obtained model was robust to quantify adulteration in teff flour even with the differences in the intensity of EDXRF spectra of different crops. Therefore, EDXRF, in tandem with ComDim data fusion, was an efficient tool for the adulteration control of teff flours.

Metals quantification in e-cigarettes liquids by Total Reflection X-ray Spectrometry.

Electronic cigarettes (e-cig) have gained popularity around the world and its health risks demands more research. This study aims at characterizing e-cig liquids (e-liquids) and its constituents by Total Reflection X-ray Spectrometry (TXRF). The internal standard method was the quantification procedure employed. The spectrometer's performance was evaluated with one certified reference material and spiked samples. It was possible to quantify K, Ca, Ti, Cr, Mn, Fe, Ni, Cu, Zn, Br, and Pb in the e-liquids. Concentrations above the limit for potable water were found in 10 out of 38 samples. Principal component analysis was useful for identifying toxic samples. TXRF is a promising technique for e-liquids evaluation due to its simplicity and performance.

Energy dispersive X-ray fluorescence analysis to estimate the maximum temperature reached in burned soils from an Amazonian region.

Determining the maximum temperature reached in soil during burning is important when evaluating fire intensity. Forest conversion is an ongoing process in the Amazon ecosystem. It is of utmost importance to predict fire effects on soil properties and avoid damaging environmental systems. Spectroscopic methods combined with multivariate statistics may provide chemical and mineralogical information from soil. This study aims at predicting the maximum temperature reached in Oxisols from an Amazonian region in Brazil. Slash-and-burn and pasture samples collected after fire events and unburned forest soil samples submitted to heating (250-800 °C) were investigated. Energy-dispersive X-ray fluorescence (EDXRF) was used to acquire chemical data. The experimental procedure is rapid and requires minimal sample preparation and no hazardous chemical reagents. The EDXRF data, combined with partial least squares regression, were applied in controlled-heated samples from five different sites of forest, pasture, and slash-and-burn areas. Estimated temperatures for burned samples ranged from 317 to 609 °C. Considering the instrumental advantages and the achieved results, the use of EDXRF combined with multivariate analysis is a feasible alternative technology to evaluate fire effects in soil.

Characterization of Brazilian banknotes using portable X-ray fluorescence and Raman spectroscopy.

As technology advances, counterfeiters improve their techniques reproducing banknotes with more accuracy. Spectroscopic techniques may be applied for characterization of these forgeries. The aim of this study was to develop a methodology for banknotes characterization employing portable X-ray fluorescence (pXRF) and portable Raman spectroscopy (RS) equipment for measurements in genuine and counterfeit Real (Brazilian currency) banknotes. Quantification of the metals in the ink and paper was carried out with pXRF data, using a sensitivity curve. pXRF spectral analysis was effective to discriminate between genuine and counterfeit bills. Moreover, the quantification of the metals enriched the analysis, since it was possible to compare elements concentration that are commonly found in genuine and counterfeit banknotes. The use of partial least square discriminant analysis (PLS-DA) applied to pXRF data was efficacious to identify fake banknotes and it may be used for further investigation about the provenance of forgeries. Principal component analysis (PCA) grouped forgeries from different seizures based on similarities in the elemental composition. The spectra obtained by RS allowed identification of characteristic bands of two pigments from the inks: phthalocyanine and diarylide. For the RS data, PLS-DA and PCA successfully discriminated R$ 50 genuine and fake banknotes.