Data Fusion Approaches for the Characterization of Musts and Wines Based on Biogenic Amine and Elemental Composition.

Samples from various winemaking stages of the production of sparkling wines using different grape varieties were characterized based on the profile of biogenic amines (BAs) and the elemental composition. Liquid chromatography with fluorescence detection (HPLC-FLD) combined with precolumn derivatization with dansyl chloride was used to quantify BAs, while inductively coupled plasma (ICP) techniques were applied to determine a wide range of elements. Musts, base wines, and sparkling wines were analyzed accordingly, and the resulting data were subjected to further chemometric studies to try to extract information on oenological practices, product quality, and varieties. Although good descriptive models were obtained when considering each type of data separately, the performance of data fusion approaches was assessed as well. In this regard, low-level and mid-level approaches were evaluated, and from the results, it was concluded that more comprehensive models can be obtained when joining data of different natures.

Characterization of Sparkling Wines According to Polyphenolic Profiles Obtained by HPLC-UV/Vis and Principal Component Analysis.

Cava is a sparkling wine obtained by a secondary fermentation in its own bottle. Grape skin contains several compounds, such as polyphenols, which act like natural protectors and provide flavor and color to the wines. In this paper, a previously optimized method based on reversed phase high performance liquid chromatography (HPLC) with ultraviolet/visible (UV/Vis) detection has been applied to determine polyphenols in cava wines. Compounds have been separated in a C18 core-shell column using 0.1% formic acid aqueous solution and methanol as the components of the mobile phase. Chromatograms have been recorded at 280, 310 and 370 nm to gain information on the composition of benzoic acids, hidroxycinnamic acids and flavonoids, respectively. HPLC-UV/vis data consisting of compositional profiles of relevant analytes has been exploited to characterize cava wines produced from different base wine blends using chemometrics. Other oenological variables, such as vintage, aging or malolatic fermentation, have been fixed over all the samples to avoid their influence on the description. Principal component analysis and other statistic methods have been used to extract of the underlying information, providing an excellent discrimination of samples according to grape varieties and coupages.