Floral Markers in Honey of Various Botanical and Geographic Origins: A Review

:  In view of the expanding global market, authentication and characterization of botanical and geographic origins of honey has become a more important task than ever. Many studies have been performed with the aim of evaluating the possibilities to characterize honey samples of various origins by us...

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Veröffentlicht in:Comprehensive reviews in food science and food safety 2010-11, Vol.9 (6), p.620-634
Hauptverfasser: Kaškonienė, Vilma, Venskutonis, Petras R.
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Sprache:eng
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Zusammenfassung::  In view of the expanding global market, authentication and characterization of botanical and geographic origins of honey has become a more important task than ever. Many studies have been performed with the aim of evaluating the possibilities to characterize honey samples of various origins by using specific chemical marker compounds. These have been identified and quantified for numerous honey samples. This article is aimed at summarizing the studies carried out during the last 2 decades. An attempt is made to find useful chemical markers for unifloral honey, based on the analysis of the compositional data of honey volatile compounds, phenolic acids, flavonoids, carbohydrates, amino acids, and some other constituents. This review demonstrates that currently it is rather difficult to find reliable chemical markers for the discrimination of honey collected from different floral sources because the chemical composition of honey also depends on several other factors, such as geographic origin, collection season, mode of storage, bee species, and even interactions between chemical compounds and enzymes in the honey. Therefore, some publications from the reviewed period have reported different floral markers for honey of the same floral origin. In addition, the results of chemical analyses of honey constituents may also depend on sample preparation and analysis techniques. Consequently, a more reliable characterization of honey requires the determination of more than a single class of compounds, preferably in combination with modern data management of the results, for example, principal component analysis or cluster analysis.
ISSN:1541-4337
1541-4337
DOI:10.1111/j.1541-4337.2010.00130.x