Show simple item record
dc.contributor.author |
Surmová, Silvie
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dc.contributor.author |
Wiśniewska, Paulina
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dc.contributor.author |
Śliwińska, Magdalena
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dc.contributor.author |
Dymerski, Tomasz
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dc.contributor.author |
Wardencki, Waldemar
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dc.contributor.author |
Namieśnik, Jacek
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dc.contributor.author |
Ventura, Karel
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dc.contributor.author |
Adam, Martin
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dc.contributor.author |
Eisner, Aleš
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dc.date.accessioned |
2020-09-29T11:23:19Z |
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dc.date.available |
2020-09-29T11:23:19Z |
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dc.date.issued |
2020 |
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dc.identifier.isbn |
978-80-7560-322-7 |
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dc.identifier.issn |
1211-5541 |
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dc.identifier.uri |
https://hdl.handle.net/10195/76723 |
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dc.description.abstract |
Each alcoholic beverage has its own distinct aroma and unique flavor. An
Electronic nose (E-nose) is an instrumental tool which allows one to analyze the
aroma of samples. This work illustrates the use of E-nose for the determination of
characteristic aromas of seven different alcoholic beverages (bourbon, brandy,
cognac, vodka, liqueurs made from pears, and fruit spirits made from lemon). The
following chemometrics methods for the data analysis were employed for the
classification of alcoholic beverages: principal component analysis (PCA),
discriminant factorial analysis (DFA, and soft independent modelling of class
analogies (SIMCA). The results show that chemometrics methods PCA and DFA
allow us the determination of the individual alcoholic groups of fruit spirits,
bourbon, cognac, and brandy but there is a difficulty with separation of liqueur,
gin, and vodka points from one group. Only the SIMCA method allowed to
distinguish the point belonging to all groups without any approximation of graph
fragments. |
en |
dc.format |
p. 147 - 156 |
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dc.language.iso |
en |
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dc.publisher |
University of Pardubice |
en |
dc.relation.ispartof |
Scientific papers of the University of Pardubice. Series A, Faculty of Chemical Technology. 26/2020 |
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dc.rights |
open access |
en |
dc.subject |
alcohols |
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dc.subject |
gas chromatography |
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dc.subject |
chemometrics methods |
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dc.subject |
sensors |
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dc.title |
Classification of the alcoholic beverages by using electronic nose technique based on ultra-fast GC |
en |
dc.type |
Article |
en |
dc.peerreviewed |
yes |
en |
dc.publicationstatus |
published |
en |
dc.identifier.obd |
39885067 |
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