Please use this identifier to cite or link to this item:https://hdl.handle.net/20.500.12259/37745
Type of publication: Straipsnis Clarivate Analytics Web of Science ar/ir Scopus / Article in Clarivate Analytics Web of Science or / and Scopus (S1)
Field of Science: Chemija / Chemistry (N003)
Author(s): Kaškonienė, Vilma;Kaškonas, Paulius;Maruška, Audrius;Kubilienė, Loreta
Title: Chemometric analysis of volatiles of propolis from different regions using static headspace GC-MS
Is part of: Central European journal of chemistry. Warsaw : Versita, Vol. 12, iss. 6 (2014)
Extent: p. 736-746
Date: 2014
Keywords: Propolis;Statinės viršerdvės DC-MS;Chemometrija;Propolis;Static headspace GC-MS;Data pre-processing;Hierarchical cluster analysis;K-Means cluster analysis
Abstract: Six samples of propolis were analyzed in the paper: a sample from Brazil, Estonia, China and three samples from different locations of Uruguay. Static headspace technique coupled with gas chromatography-mass spectrometry analysis has been applied for the determination of the characteristic volatile profile with the aim to differentiate the propolis from different regions. Monoterpenes (α- and β-pinenes) were predominant in all samples, except the sample from China. This sample separated itself by the alcohols 3-methyl- 3-buten-1-ol and 3-methyl-2-buten-1-ol, (40.33% and 11.57%, respectively) and ester 4-penten-1-yl acetate (9.04%). α-Pinene and β-pinene composed 64.59-77.56% of volatiles in Brazilian and Uruguayan propolis, and 29.43% in Estonian propolis. Brazilian propolis was distinguished by a high amount of β-methyl crotonaldehyde (10.11%), one of Uruguayan samples – by limonene (15.58%), and the Estonian sample – by eucalyptol (25.95%). Statistical investigation of the samples was made applying principal component, hierarchical cluster and K-Means cluster analyses. Various data pre-processing techniques were proposed and used to study and obtain the important volatile compounds contributed to the differentiation of the propolis samples from different regions to separate clusters
Internet: http://link.springer.com/article/10.2478%2Fs11532-014-0521-7
Affiliation(s): Biochemijos katedra
Kauno technologijos universitetas
Lietuvos sveikatos mokslų universitetas
Vytauto Didžiojo universitetas
Appears in Collections:Universiteto mokslo publikacijos / University Research Publications

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