engleski

Characterization and Classification of Croatian Honey by Physicochemical Parameters

The aim of this study was to characterise 8 different monofloral/multifloral types of Croatian honey (a total of 254 samples – 2003, 2004, and 2005 harvesting seasons) based on 11 common physicochemical parameters (water content, total reducing sugar content, sucrose content, ash content, electrical conductivity, acidity, diastase and invertase activity, HMF content, proline content and optical rotation). Differences in the abovementioned parameters, established between the honey samples, are influenced by different factors, such as botanical origin, climate and regional circumstances. The results obtained within the frame of our study are as follows: 13.9 – 20.6 % for water content ; 61.0 – 77.0 % for total reducing sugars ; 0.0 – 10.7 % for sucrose content ; 0.01 – 1.13 % for ash content ; 0.11 – 1.62 mS/cm for electrical conductivity ; 5.0 – 37.7 mmol/kg for acidity ; 0.1 – 34.7 IN for invertase activity ; 6.2 – 42.3 DN for diastase activity ; 24.0 – 1020.8 mg/kg for proline content ; 0.4 – 99.8 mg/kg for hydroxymethyl-furfural (HMF) content, and -3.6 – 3.9 ˚ for optical rotation. Subsequent to the sample characterisation, results obtained with 2 monofloral [acacia (Robinia pseudoacacia) and chestnut (Aesculus hippocastanum)], and 2 multifloral (flower and meadow) honey types were subjected to the pattern recognition procedures. In this regard, unsupervised methods such as cluster and principal component analysis were employed, to the goal of evaluating the possibility of differentiation of Croatian honey stemming from different botanical origins, based on their physicochemical profile. Cluster analysis (CA) revealed the existence of two clusters, out of which the first correspondent to the best-grouped acacia honey, and the second correspondent to the dispersed group constituted of the remaining three honey types under investigation (chestnut, flower, and meadow). Principal component analysis (PCA), i.e. its first two components, stood for the average of 50.5 % of the data variance. PCA and cluster analysis had shown that physicochemical parameters are able to provide enough information to allow for the classification and distinction of the honey originating from four botanical origins under investigation (acacia, chestnut, flower, meadow).

honey; physicochemical parameters; botanical origin; Cluster Analysis; Principal component analysis (PCA)

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