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The objective of the present study is to establish regression models defining the relations between physicochemical parameters of bee honey and the type of honey. 89 samples of bee honey (acacia honey, coriander honey, limetree honey, rapeseed honey, sunflower honey, and multifloral honey) collected from different regions of Bulgaria were used in the study. The following parameters have been defined: water content (WC); content of fructose (F), glucose (G), electrical conductivity (EC), refractive index (RI), and pH. Moderate to strong negative correlation between WC and RI has been found for all studied types of bee honey. In the samples from lime tree, coriander, and multifloral honey, positive but different in strength correlation has been observed - from weak to moderate correlation between pH and EC. The analysis of the samples with acacia honey showed differences in strength and direction of: lime tree and multifloral honey in terms of the correlations between pH and total F + G content; of lime tree, rapeseed, and sunflower honey in the correlations between F+G and RI and between WC and F + G. General Linear Models (1-5) have been compiled based on the connections between the considered physicochemical parameters and the different types of honey, which would allow subsequent estimation of the studied parameters. [ABSTRACT FROM AUTHOR]

The objective of the present study is to examine samples of bee honey of different origin and create models for their classification through spectral analysis in the nearinfrared spectrum. Representative samples unifloral (sunflower, acacia, lime and coriander), multifloral and honeydew honey are used. The origin of the above honey samples has been determined in advance by pollen analysis. The spectral measurement (NIR spectroscopy) of each sample was done non-destructively, by measuring the diffuse reflection of the honey samples using the spectral device NIRQuest512 within the range 900-1700 nm. The spectral differences between the different types of bee honey have been studied. For classification of the samples based on their spectra the SIMCA method (Soft Independent Modeling of Class Analogy) was used. Models for distinguishing different types of bee honey- unifloral, multifloral and honeydew - have been obtained. The results show 100% accuracy of classification of the samples from the three groups based on the received spectral information. The most compact is the group of honeydew honey. [ABSTRACT FROM AUTHOR]