Differentiation Of Honeys Research Articles

Multivariate Statistical Approach for the Discrimination of Honey Samples from Galicia (NW Spain) Using Physicochemical and Pollen Parameters.

Raw honey is a food with a close relation to the territory in which it is produced because of factors such as soil conditions, weather patterns, and plant communities living in the area together. Furthermore, beekeeping management affects the properties of honey. Protected Geographical Indication Miel de Galicia protects the honey produced in Galicia (Northwest Spain). Various types of honeys (362 samples) from this geographical area were analyzed using chemometric techniques. Principal component analysis was favorable to analyzing the physicochemical and pollen variables with the greatest weight in the differentiation of honey. The linear discriminant analysis correctly classified 89.8% of the samples according to the botanical origin using main pollen spectra and physicochemical attributes (moisture, pH, electrical conductivity, diastase content, phenols, flavonoids, and color). Regarding unifloral honey, blackberry, eucalyptus, and heather honeys were correctly grouped, while five chestnut honeys and fourteen samples of honeydew honeys were misclassified. The chestnut and honeydew honeys have similar physicochemical properties and frequently similar pollen spectra profiles complicating the differentiation. Experimental evidence suggests the potential of multivariate statistics in the characterization of honey of the same geographical origin. Therefore, the classification results were good, with electrical conductivity, total phenol content, total flavonoid content and dominant pollens Eucalyptus, Erica, Rubus and Castanea sativa as the variables of higher importance in the differentiation of botanical origin of honeys.

Differentiation of Honey from Melipona Species Using Differential Scanning Calorimetry

Differential scanning calorimetry (DSC) was used to study the thermal behavior of Colombian honeys produced by the honey-bee Apis mellifera and by three species of stingless bees: Melipona fuscipes, Melipona favosa favosa, and Melipona compressipes. The honey samples were collected every 2 months over the course of year (August 2014 to August 2015). Up to four thermal transitions (trs1–trs4a, trs4b) were found in the honey samples: M. fuscipes (trs1–trs4a), M. favosa (trs1–trs4a, trs4b), M. compressipes (trs1, trs3, trs4a), and A. mellifera (trs1, trs3, trs4a). Statistical analyses showed significant differences in enthalpies of each transition between species; therefore, DSC analysis can be used as a finger-print to differentiate the honeys of species.

Multi-Element Composition of Honey as a Suitable Tool for Its Authenticity Analysis

The aim of this study was to evaluate the composition of 36 honey samples of 4 different botanical origins (acacia, sun fl ower, tilia and honeydew) from the North East region of Romania. An inductively coupled plasma-mass spectrometry (ICP-MS) method was used to determine 27 elements in honey (Ag, Al, As, Ba, Be, Ca, Cd, Co, Cr, Cs, Cu, Fe, Ga, K, Li, Mg, Mn, Na, Ni, Pb, Rb, Se, Sr, Tl, U, V and Zn). We would like to achieve the following goal: to demonstrate that the qualitative and quantitative multi-element composition determination of honey can be used as a suitable tool to classify honey according to its botanical origin. The principal component analysis allowed the reduction of the 27 variables to 2 principal components which explained 74% of the total variance. The dominant elements which were strongly associated with the principal component were K, Mg and Ca. Discriminant models obtained for each kind of botanical honey confi rmed that the differentiation of honeys according to their botanical origin was mainly based on multi-element composition. A correct classifi cation of all samples was achieved with the exception of 11.1% of honeydew honeys.

Effect of country origin on physicochemical, sugar and volatile composition of acacia, sunflower and tilia honeys

The aim of this study was to evaluate the influence of country (Spain, Romania, and Czech Republic) and botanical origin, on the physicochemical (HMF, diastase activity, moisture content, electrical conductivity), color (Pfund scale and CIEL*a*b*), principal sugars (glucose, fructose and sucrose) and volatile composition of acacia, sunflower and tilia honeys. PCA analyses considering these variables showed that honey type had a far greater influence on the differentiation of samples (above all due to the presence of certain volatile compounds such as carvacrol and α-terpinene for tilia honey; α-pinene and 3-methyl-2-butanol for sunflower honey, and cis-linalool oxide for acacia honey) than geographical origin. Discriminant models obtained for each kind of botanical honey (classified 100% for acacia and tilia honeys and 93.8% for sunflower of the cross-validated cases) confirmed that differentiation of honeys according to their country was mainly based on volatile compounds (for instance: 2-methyl-2-butenal and 2-methyl-2-propanol, for acacia honeys; 1-hexanol and α-pinene, for sunflower honeys and 3-methyl-1-butanol and otrienol, for tilia honey) and to a lesser extent on certain physicochemical parameters such as diastase, sucrose and conductivity, respectively. Correct classification of all samples was achieved with the exception of 10% of the sunflower honeys from the Czech Republic. The results suggest that the presented models are potentially useful tools for the classification of acacia, sunflower and tilia honeys according to the country of origin.

Analysis of volatiles from Spanish honeys by solid-phase microextraction and gas chromatography-mass spectrometry.

Headspace solid-phase microextraction (SPME), followed by gas chromatography (GC)-mass spectrometry (MS) determination, has been used for the analysis of honey volatiles. Two SPME fibers were employed to study the composition of volatiles from various types of Spanish honeys. The best results were obtained with the Carboxen/PDMS fiber, using a homogenization time of 1 h at 70 degrees C and a sampling period of 30 min. A total of 35 compounds were detected, most of them identified by GC-MS and quantified using external standards. Differences in the composition of honey volatiles were obtained, and these results allowed the differentiation of honeys. However, further studies are necessary to confirm the utility of this technique as an alternative tool for the characterization of the floral origin of honeys.