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This article reports a method for determining organic acids by CE in order to obtain a characteristic fingerprint with a view to classifying white wine samples with the aid of multivariate statistics. The proposed method was optimized for the determination of the most abundant organic acids in wine (viz. succinic, malic, tartaric, citric, acetic and lactic). The acids were separated in a running buffer consisting of 180 mM disodium hydrogen phosphate, 0.5 mM CTAB and 10% methanol, adjusted to pH 7.5. The applied voltage was 10 kV and the working temperature 251C. The precision of the method was assessed by replicate analysis of a wine sample; the resulting RSD was less than 5.2% in peak area and less than 1% in migration time for all organic acids. Calibration curves exhibited good linearity throughout the studied concentration range for all acids. Principal component analysis and linear discriminant analysis allowed accurate classification of wine samples with variable alcohol contents from their electrophoretic fingerprints. The discriminant potential of various electropherogram regions was examined. Based on the results, the proposed method is an effective choice for classifying wine samples. IntroductionThe winemaking sector is one of the main motors of the economy in Spain. Spanish white wines are high-quality products much appreciated by consumers inside the country and also, increasingly, abroad [1]. Therefore, being able to confirm their authenticity is of paramount importance with a view to assuring their quality to an expanding international market. Multivariate analysis has been widely used for this purpose in recent years.Wines [11,12] or nuclear magnetic resonance spectroscopy [13]. In this context, conventional methods have been supplemented with electronic tongues, noses and other sensor array devices for wine-monitoring purposes [14][15][16][17]. These instrumental techniques have been used in combination with chemometric tools such as artificial neural networks in order to classify white wines [18]. Separation techniques such as CE have also been used to classify wines [19][20][21][22]. To our knowledge, electropherogram profiles, which are constructed from the CE response of organic acids, have never, to date, been used as fingerprints for white wines and their classification with chemometric models. In this study, we used electropherogram fingerprints obtained with CE to classify white wines for the first time.Organic acids present in grape juices and wines are important because they influence the sensory properties (flavour, colour and aroma), and the physical and microbiological stability, of the product. Acetic, lactic, succinic, malic, citric and tartaric are the most abundant organic acids in wines. Tartaric, malic and citric acid are obtained directly from the grape, whereas succinic, lactic and acetic acid form during the fermentation process. These organic acids are also very useful for detecting wine alteration and/ or disease [23].Malic acid is present in large amounts in green gra...

Simulation results for liquids composed of linear molecules interacting through dispersion forces and off-center dipoles are presented. Remarkable differences are found on the vapor-liquid equilibrium respect to that of centered dipole molecules. Even more remarkable is the appearance of additional short-range liquid structure at relatively large dipoles and aspect ratios. The existence of dipole dimers is clearly established, and some suggestions allowing for the correspondence between a particular macroscopic phenomenology and a particular dispersion potential function are presented.

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Atmospheric pressure glow discharges have been widely used in the last decade as ion sources in ambient mass spectrometry analyses. Here, an in-house flowing atmospheric pressure afterglow (FAPA) has been developed as an alternative ion source for differential mobility analysis (DMA). The discharge source parameters (inter-electrode distance, current and helium flow rate) determining the atmospheric plasma characteristics have been optimized in terms of DMA spectral simplicity with the highest achievable sensitivity while keeping an adequate plasma stability and so the FAPA working conditions finally selected were: 35 mA, 1 L min(-1) of He and an inter-electrode distance of 8 mm. Room temperature in the DMA proved to be adequate for the coupling and chemical analysis with the FAPA source. Positive and negative ions for different volatile organic compounds were tested and analysed by FAPA-DMA using a Faraday cup as a detector and proper operation in both modes was possible (without changes in FAPA operational parameters). The FAPA ionization source showed simpler ion mobility spectra with narrower peaks and a better, or similar, sensitivity than conventional UV-photoionization for DMA analysis in positive mode. Particularly, the negative mode proved to be a promising field of further research for the FAPA ion source coupled to ion mobility, clearly competitive with other more conventional plasmas such as corona discharge.