Profiling turkish honeys to determine authenticity using physical and chemical characteristics

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dc.citation.epage3919en_US
dc.citation.issueNumber9en_US
dc.citation.spage3911en_US
dc.citation.volumeNumber57en_US
dc.contributor.authorSenyuva H.Z.en_US
dc.contributor.authorGilbert J.en_US
dc.contributor.authorSilici, S.en_US
dc.contributor.authorCharlton, A.en_US
dc.contributor.authorDal, C.en_US
dc.contributor.authorGürel, N.en_US
dc.contributor.authorCimen, D.en_US
dc.date.accessioned2016-02-08T10:04:20Z
dc.date.available2016-02-08T10:04:20Z
dc.date.issued2009en_US
dc.departmentDepartment of Chemistryen_US
dc.description.abstractSeventy authentic honey samples of 9 different floral types (rhododendron, chestnut, honeydew, Anzer (thymus spp.), eucalyptus, gossypium, citrus, sunflower, and multifloral) from 15 different geographical regions of Turkey were analyzed for their chemical composition and for indicators of botanical and geographical origin. The profiles of free amino acids, oligosaccharides, and volatile components together with water activity were determined to characterize chemical composition. The microscopic analysis of honey sediment (mellissopalynology) was carried out to identify and count the pollen to provide qualitative indicators to confirm botanical origin. Statistical analysis was undertaken using a bespoke toolbox for Matlab called Metabolab. Discriminant analysis was undertaken using partial least-squares (PLS) regression followed by linear discriminant analysis (LDA). Four data models were constructed and validated. Model 1 used 51 variables to predict the floral origin of the honey samples. This model was also used to identify the top 5 variable important of projection (VIP) scores, selecting those variables that most significantly affected the PLS-LDA calculation. These data related to the phthalic acid, 2-methylheptanoic acid, raffinose, maltose, and sucrose. Data from these compounds were remodeled using PLS-LDA. Model 2 used only the volatiles data, model 3 the sugars data, and model 4 the amino acids data. The combined data set allowed the floral origin of Turkish honey to be accurately predicted and thus provides a useful tool for authentication purposes. However, using variable selection techniques a smaller subset of analytes have been identified that have the capability of classifying Turkish honey according to floral type with a similar level of accuracy. © 2009 American Chemical Society.en_US
dc.identifier.doi10.1021/jf900039sen_US
dc.identifier.issn218561
dc.identifier.urihttp://hdl.handle.net/11693/22754
dc.language.isoEnglishen_US
dc.relation.isversionofhttp://dx.doi.org/10.1021/jf900039sen_US
dc.source.titleJournal of Agricultural and Food Chemistryen_US
dc.subjectAmino acidsen_US
dc.subjectChemometricsen_US
dc.subjectDisaccharidesen_US
dc.subjectFloral typesen_US
dc.subjectTurkish honeyen_US
dc.subjectamino aciden_US
dc.subjectoligosaccharideen_US
dc.subjectwateren_US
dc.subjectarticleen_US
dc.subjectclassificationen_US
dc.subjectdiscriminant analysisen_US
dc.subjecthoneyen_US
dc.subjectmass fragmentographyen_US
dc.subjectodoren_US
dc.subjectTurkey (republic)en_US
dc.subjectvolatilizationen_US
dc.subjectAmino Acidsen_US
dc.subjectDiscriminant Analysisen_US
dc.subjectGas Chromatography-Mass Spectrometryen_US
dc.subjectHoneyen_US
dc.subjectOdorsen_US
dc.subjectOligosaccharidesen_US
dc.subjectTurkeyen_US
dc.subjectVolatilizationen_US
dc.subjectWateren_US
dc.subjectCitrusen_US
dc.subjectCucumis melo var. inodorusen_US
dc.subjectEucalyptusen_US
dc.subjectGossypiumen_US
dc.subjectGossypium hirsutumen_US
dc.subjectHelianthusen_US
dc.subjectRhododendronen_US
dc.titleProfiling turkish honeys to determine authenticity using physical and chemical characteristicsen_US
dc.typeArticleen_US

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