Cluster Analysis Classification of Honey from Two Different Climatic Zones Based on Selected Physicochemical and of Microbiological Parameters

Abstract

The geographical origin of honey affects its composition, which is of key importance for the health-promoting properties and safety of the product. European regulations clearly define the physicochemical requirements for honey that determine the microbiological quality. On the other hand, legislation abolishes microbiological criteria. In the study 40 honey samples originating from two different climatic zones were analyzed. The water content, pH, water activity analysis and the microbiological quality of honey samples have been tested using the reference plate method (total viable count, yeast and molds, lactic acid bacteria, Bacillus spp.). The cluster classification showed that total viable count of bacteria could be used as a measure alternative to the count of Bacillus spp. and 70% of honeys from the tropical climate zone had different microbiological quality than honeys from the temperate climate zone but still under the level 3.0 log cfu/g. The study has revealed that geographical origin of honey may significantly affect the quality and safety of honey. It was considered that water content can be the most informative and handy marker of the microbiological quality of honeys. Analysis of lactic acid bacteria showed temperate climate zone honeys as a source of beneficial bacteria in the diet.

A New Approach for Determination of the Botanical Origin of Monofloral Bee Honey, Combining Mineral Content, Physicochemical Parameters, and Self-Organizing Maps

“…The application of these methods naturally requires the application of appropriate statistical analyses—cluster analysis [ 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 ], principal component analysis [ 11 , 12 , 13 , 14 , 16 , 17 , 21 , 22 , 23 , 25 , 26 , 27 ], etc. Combining the results of classical analytical methods for determining components in various types of monofloral honey with intelligent multivariate analyses, such as neural networks, is a new opportunity for the reliable identification of the botanical [ 17 , 20 , 22 ] and geographical [ 14 , 20 , 28 ] origin of monofloral honey.…”