Characterisation and classification of Greek pine honeys according to their geographical origin based on volatiles, physicochemical parameters and chemometrics
| dc.contributor.author | I.K. Karabagias, | en |
| dc.contributor.author | A. Badeka, | en |
| dc.contributor.author | S. Kontakos, | en |
| dc.contributor.author | S. Karabournioti | en |
| dc.contributor.author | M.G. Kontominas | en |
| dc.date.accessioned | 2015-11-24T16:53:36Z | |
| dc.date.available | 2015-11-24T16:53:36Z | |
| dc.identifier.uri | https://olympias.lib.uoi.gr/jspui/handle/123456789/10041 | |
| dc.rights | Default Licence | - |
| dc.subject | Pine honey | en |
| dc.subject | Classification | en |
| dc.subject | Volatile compounds | en |
| dc.subject | Physicochemical parameters | en |
| dc.subject | Chemometrics | en |
| dc.title | Characterisation and classification of Greek pine honeys according to their geographical origin based on volatiles, physicochemical parameters and chemometrics | en |
| heal.abstract | The aim of the present study was to characterise and classify Greek pine honeys according to geographical origin, based on the determination of volatile compounds and physicochemical parameters using MANOVA and Linear Discriminant Analysis. Thirty-nine pine honey samples were collected during the harvesting period 2011 from 4 different regions in Greece known to produce good quality pine honey. The analysis of volatile compounds was performed by Headspace Solid Phase Microextraction-Gas Chromatography/Mass Spectroscopy. Fifty-five volatile compounds were tentatively identified and semi quantified. Physicochemical parameter analysis included the determination of pH, free, lactonic and total acidity, electrical conductivity, moisture, ash, lactonic/free acidity ratio and colour parameters L�, a�, b�. Using 8 selected volatile compounds and 11 physicochemical parameters, the honey samples were satisfactorily classified according to geographical origin using volatile compounds (84.6% correct prediction), physicochemical parameters (79.5% correct prediction) and the combination of both (74.4% correct prediction). | en |
| heal.access | campus | - |
| heal.fullTextAvailability | TRUE | - |
| heal.identifier.primary | http://dx.doi.org/10.1016/j.foodchem.2013.09.105 | - |
| heal.identifier.secondary | http://www.sciencedirect.com/science/article/pii/S0308814613013708 | - |
| heal.journalName | Food Chemistry | en |
| heal.journalType | peer reviewed | - |
| heal.language | en | - |
| heal.publicationDate | 2014 | - |
| heal.publisher | Elsevier | en |
| heal.recordProvider | Πανεπιστήμιο Ιωαννίνων. Σχολή Θετικών Επιστημών. Τμήμα Χημείας | el |
| heal.type | journalArticle | - |
| heal.type.el | Άρθρο Περιοδικού | el |
| heal.type.en | Journal article | en |
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