Characterisation of tequila according to their major volatile composition using multilayer perceptron neural networks

► Higher alcohols and furaldehydes as chemical descriptors to differentiate tequilas. ► Higher alcohols were determined by HS-SPME-GC–MS. ► Furaldehydes were determined by HPLC. ► BP-MLP-ANN allows complete differentiation between aged and not aged tequilas. Differentiation of silver, gold, aged and...

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Veröffentlicht in:Food chemistry 2013-02, Vol.136 (3-4), p.1309-1315
Hauptverfasser: Ceballos-Magaña, Silvia G., de Pablos, Fernando, Jurado, José Marcos, Martín, María Jesús, Alcázar, Ángela, Muñiz-Valencia, Roberto, Gonzalo-Lumbreras, Raquel, Izquierdo-Hornillos, Roberto
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Sprache:eng
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Zusammenfassung:► Higher alcohols and furaldehydes as chemical descriptors to differentiate tequilas. ► Higher alcohols were determined by HS-SPME-GC–MS. ► Furaldehydes were determined by HPLC. ► BP-MLP-ANN allows complete differentiation between aged and not aged tequilas. Differentiation of silver, gold, aged and extra-aged tequila using 1-propanol, ethyl acetate, 2-methyl-1-propanol, 3-methyl-1-butanol and 2-methyl-1-butanol and furan derivatives like 5-(hydroxymethyl)-2-furaldehyde and 2-furaldehyde has been carried out. The content of 1-propanol, ethyl acetate, 2-methyl-1-propanol, 3-methyl-1-butanol and 2-methyl-1-butanol was determined by means of head space solid phase microextraction gas chromatography mass-spectrometry. 5-(Hydroxymethyl)-2-furaldehyde and 2-furaldehyde were determined by high performance liquid chromatography with diode array detection. Kruskal–Wallis test was used to highlight significant differences between types of tequila. Principal component analysis was applied as visualisation technique. Linear discriminant analysis and multilayer perceptron artificial neural networks were used to construct classification models. The best classification performance was obtained when multilayer perceptron model was applied.
ISSN:0308-8146
1873-7072
DOI:10.1016/j.foodchem.2012.09.048