Paper-based diffusive gradients in thin films technique coupled to energy dispersive X-ray fluorescence spectrometry for the determination of labile Mn, Co, Ni, Cu, Zn and Pb in river water

The diffusive gradients in thin films (DGT) technique has shown enormous potential for labile metal monitoring in fresh water due to the preconcentration, time-integrated, matrix interference removal and speciation analytical features. In this work, the coupling of energy dispersive X-ray fluorescence (EDXRF) with paper-based DGT devices was evaluated for the direct determination of Mn, Co. Ni, Cu, Zn and Pb in fresh water. The DGT samplers were assembled with cellulose (Whatman 3 MM chromatography paper) as the diffusion layer and a cellulose phosphate ion exchange membrane (Whatman P 81 paper) as the binding agent. The diffusion coefficients of the analytes on 3 MM chromatography paper were calculated by deploying the DGT samplers in synthetic solutions containing 500 mu g L-1 of Mn. Co, Ni, Cu, Zn and Pb (4 L at pH 5.5 and ionic strength at 0.05 mol L-1). After retrieval, the DGT units were disassembled and the P81 papers were dried and analysed by EDXRF directly. The 3 MM chromatographic paper diffusion coefficients of the analytes ranged from 1.67 to 1.87 x 10(-6) cm(2) s(-1). The metal retention and phosphate group homogeneities on the P81 membrane was studied by a spot analysis with a diameter of 1 mm. The proposed approach (DGT-EDXRF coupling) was applied to determine the analytes at five sampling sites (48 h in situ deployment) on the Piracicaba river basin, and the results (labile fraction) were compared with 0.45 mu m dissolved fractions determined by synchrotron radiation-excited total reflection X-ray fluorescence (SR-TXRF). The limits of detection of DGT-EDXRF coupling for the analytes (from 7.5 to 26 mu g L-1) were similar to those obtained by the sensitive SR-TXRF technique (3.8 to 9.1 mu g L-1). (C) 2012 Elsevier B.V. All rights reserved.

Multi-element determination in Brazilian honey samples by inductively coupled plasma mass spectrometry and estimation of geographic origin with data mining techniques

Multi-element analysis of honey samples was carried out with the aim of developing a reliable method of tracing the origin of honey. Forty-two chemical elements were determined (Al, Cu, Pb, Zn, Mn, Cd, Tl, Co, Ni, Rb, Ba, Be, Bi, U, V, Fe, Pt, Pd, Te, Hf, Mo, Sn, Sb, P, La, Mg, I, Sm, Tb, Dy, Sd, Th, Pr, Nd, Tm, Yb, Lu, Gd, Ho, Er, Ce, Cr) by inductively coupled plasma mass spectrometry (ICP-MS). Then, three machine learning tools for classification and two for attribute selection were applied in order to prove that it is possible to use data mining tools to find the region where honey originated. Our results clearly demonstrate the potential of Support Vector Machine (SVM), Multilayer Perceptron (MLP) and Random Forest (RF) chemometric tools for honey origin identification. Moreover, the selection tools allowed a reduction from 42 trace element concentrations to only 5. (C) 2012 Elsevier Ltd. All rights reserved.