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Treball de fi de grau

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cc-by-nc-nd (c) Torres, 2018
Si us plau utilitzeu sempre aquest identificador per citar o enllaçar aquest document: https://hdl.handle.net/2445/125792

Characterization of sparkling wines by liquid chromatography

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Cava is an exceptional kind of sparkling wine with a protected designation of origin (PDO) status from Spain. This beverage is made by the Champanoise method, which requires a secondary fermentation in the bottle. Polyphenols are one of the principal components of Cava. These substances not only are responsible for some of the unique properties of Cava but, also, can be used as chemical descriptors to discriminate among samples of different varieties and compositions. In the present project, 10 types of Cavas from different varieties of grapes were characterized according to their polyphenolic profile, which was obtained by high performance liquid chromatography with UV-visible detection at different wavelengths (250, 280, 310, 370 nm). A total of 18 polyphenols were studied. Two different approaches (chromatograms and integrated peak areas, also referred to as fingerprinting and profiling approaches, respectively) were used to build principal component analysis (PCA) models focused on the differentiation among the samples. Both models presented an excellent discriminant ability. Besides, with the profiling model the most characteristic polyphenolic compounds of each kind of Cava were identified. Finally, the chromatograms registered at 310 nm were used to build partial least squares discriminant analysis (PLS-DA) models which allowed the classification of the Cava samples according to their type, and “unknown” samples belonging to a new test set were correctly assigned to their corresponding classes

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Treballs Finals de Grau de Química, Facultat de Química, Universitat de Barcelona, Any: 2018, Tutor: Xavier Saurina Purroy

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TORRES COBOS, Berta. Characterization of sparkling wines by liquid chromatography. [consulted: 22 of May of 2026]. Available at: https://hdl.handle.net/2445/125792

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