Chemometric Studies on zNose™ and Machine Vision Technologies for Discrimination of Commercial Extra Virgin Olive Oils

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dc.contributor.authorKadiroglu, Pinar
dc.contributor.authorKorel, Figen
dc.date.accessioned2025-01-06T17:37:47Z
dc.date.available2025-01-06T17:37:47Z
dc.date.issued2015
dc.description.abstractThe aim of this study was to classify Turkish commercial extra virgin olive oil (EVOO) samples according to geographical origins by using surface acoustic wave sensing electronic nose (zNose (TM)) and machine vision system (MVS) analyses in combination with chemometric approaches. EVOO samples obtained from north and south Aegean region were used in the study. The data analyses were performed with principal component analysis class models, partial least squares-discriminant analysis (PLS-DA) and hierarchical cluster analysis (HCA). Based on the zNose (TM) analysis, it was found that EVOO aroma profiles could be discriminated successfully according to geographical origin of the samples with the aid of the PLS-DA method. Color analysis was conducted as an additional sensory quality parameter that is preferred by the consumers. The results of HCA and PLS-DA methods demonstrated that color measurement alone was not an effective discriminative factor for classification of EVOO. However, PLS-DA and HCA methods provided clear differentiation among the EVOO samples in terms of electronic nose and color measurements. This study is significant from the point of evaluating the potential of zNose (TM) in combination with MVS as a rapid method for the classification of geographically different EVOO produced in industry.
dc.identifier.doi10.1007/s11746-015-2697-1
dc.identifier.endpage1242
dc.identifier.issn0003-021X
dc.identifier.issn1558-9331
dc.identifier.issue9
dc.identifier.scopus2-s2.0-84941315064
dc.identifier.scopusqualityQ2
dc.identifier.startpage1235
dc.identifier.urihttps://doi.org/10.1007/s11746-015-2697-1
dc.identifier.urihttps://hdl.handle.net/20.500.14669/2361
dc.identifier.volume92
dc.identifier.wosWOS:000360934700001
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherSpringer
dc.relation.ispartofJournal of The American Oil Chemists Society
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_20241211
dc.subjectExtra virgin olive oil
dc.subjectElectronic nose
dc.subjectMachine vision system
dc.subjectChemometrics
dc.titleChemometric Studies on zNose™ and Machine Vision Technologies for Discrimination of Commercial Extra Virgin Olive Oils
dc.typeArticle

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