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Si us plau utilitzeu sempre aquest identificador per citar o enllaçar aquest document: https://hdl.handle.net/2445/191926
Data fusion approaches for the characterization of musts and wines based on biogenic amine and elemental composition
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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.
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MIR-CERDÀ, Aina, et al. Data fusion approaches for the characterization of musts and wines based on biogenic amine and elemental composition. Sensors. 2022. Vol. 22, num. 6, pags. 1-13. ISSN 1424-8220. [consulted: 7 of October of 2026]. Available at: https://hdl.handle.net/2445/191926