Laser-induced breakdown spectroscopy; LIBS; wines; matrix effect; trace elements;ATOMIC-ABSORPTION-SPECTROMETRY; X-RAY-FLUORESCENCE; LIQUID-LIQUID MICROEXTRACTION; QUANTITATIVE-DETERMINATION; SAMPLE INTRODUCTION; AQUEOUS-SOLUTIONS; TRACE-ELEMENTS; SINGLE-PULSE; ICP-OES; CLASSIFICATION

We developed a method for sensitive elemental analysis of wines using laser-induced breakdown spectroscopy (LIBS). In order to overcome the inefficiency of direct ablation of bulk wine (an organic liquid), a thin layer of wine residue was prepared on a metallic target according to an appropriated heating procedure applied to an amount of liquid wine dropped on the target surface. The obtained ensemble was thus ablated. Such a sample preparation procedure used a very small volume of 2mL of wine and took only 30min without reagent or solvent. The results show the detection of tens of metal and non-metal elements including majors (Na, Mg, K, Ca), minors, and traces (Li, B, Si, P, Ti, Mn, Fe, Cu, Zn, Rb, Sr, Ba, and Pb) in wines purchased from local supermarkets and from different production places in France. Commercially available wines were then spiked with certified standard solutions of Ti and Fe. Three series of laboratory reference samples were thus prepared using three different wines (a red wine and a white wine from a same production region and a red wine from another production region) with concentrations of Ti and Fe in the range of 1-40mg/L. Calibration graphs established with the spiked samples allowed extracting the figures-of-merit parameters of the method for wine analysis such as the coefficient of determination (R-2) and the limits of detection and quantification (LOD and LOQ). The calibration curves built with the three wines were then compared. We studied the residual matrix effect between these wines in the determination of the concentrations of Ti and Fe.

Wines; LIBS; Classification; Principal component analysis; Random forest; Matrix effect;LIQUID-LIQUID MICROEXTRACTION; ICP-MS; GEOGRAPHICAL ORIGIN; PROTECTED DESIGNATION; MULTIELEMENT ANALYSIS; SINGLE-PULSE; IDENTIFICATION; SAMPLES; LIBS; METALS

Laser-induced breakdown spectroscopy (LIBS) has been applied to classify French wines according to their production regions. The use of the surface-assisted (or surface-enhanced) sample preparation method enabled a sub-ppm limit of detection (LOD), which led to the detection and identification of at least 22 metal and nonmetal elements in a typical wine sample including majors, minors and traces. An ensemble of 29 bottles of French wines, either red or white wines, from five production regions, Alsace, Bourgogne, Beaujolais, Bordeaux and Languedoc, was analyzed together with a wine from California, considered as an outlier. A non-supervised classification model based on principal component analysis (PCA) was first developed for the classification. The results showed a limited separation power of the model, which however allowed, in a step by step approach, to understand the physical reasons behind each step of sample separation and especially to observe the influence of the matrix effect in the sample classification. A supervised classification model was then developed based on random forest (RF), which is in addition a nonlinear algorithm. The obtained classification results were satisfactory with, when the parameters of the model were optimized, a classification accuracy of 100% for the tested samples. We especially discuss in the paper, the effect of spectrum normalization with an internal reference, the choice of input variables for the classification models and the optimization of parameters for the developed classification models. (C) 2017 Elsevier B.V. All rights reserved.