Classification of buckwheat honey produced in Kazakhstan according to their biochemical ingredients and bioactivities by chemometric approach

Herein, nineteen buckwheat honey samples collected from 19 stations of different ecological zones of Kazakhstan were analysed for their pollen density, physicochemical properties, chemical composition, antioxidant, anticholinesterase, tyrosinase inhibitory, and urease inhibitory activities with chemometric approaches. Twelve phenolic compounds and fumaric acid were identified using HPLC-DAD, and mainly fumaric, p-hydroxybenzoic, p-coumaric, trans-2-hydroxy cinnamic acids, and chrysin were detected in all samples. The honey samples collected from the Northern zone exhibited best antioxidant activity in lipid peroxidation inhibitory (IC50:8.65 ± 0.50 mg/mL), DPPH• (IC50:17.07 ± 1.49 mg/mL), ABTS•+ (IC50:8.90 ± 0.65 mg/mL), CUPRAC (A0.50:7.51 ± 0.30 mg/mL) and metal chelating assay (IC50:10.39 ± 0.71 mg/mL). In contrast, South-eastern zone samples indicated better acetylcholinesterase (55.57 ± 0.83%), butyrylcholinesterase (49.59 ± 1.09%), tyrosinase (44.40 ± 1.21%), and moderate urease (24.57 ± 0.33%) inhibitory activities at 20 mg/mL. The chemometric classification of nineteen buckwheat honey was performed using PCA and HCA techniques. Both were supported by correlation analysis. Thirteen compounds contributed significantly to the clustering of buckwheat honey based on geographical origin.

A chemometric approach for the differentiation of 15 monofloral honeys based on physicochemical parameters

BACKGROUND

Although the main method for authentication of monofloral honey is pollen analysis, other classification approaches have been also applied. However, the majority of the existing classification models so far have utilized a few honey types or a few honey samples of each honey type, which can lead to inaccurate results. Aiming at addressing this, the goal of the present study was to create a classification model by analysing in total 250 honey samples from 15 different monofloral honey types in ten physicochemical parameters and then, multivariate analysis [multivariate analysis of variance (MANOVA), principal component analysis (PCA) and multi-discriminant analysis (MDA)] was applied in an effort to distinguish and classify them.

RESULTS

Electrical conductivity and colour were found to have the highest discriminative power, allowing the classification of monofloral honey types, such as oak, knotgrass and chestnut honey, as well as the differentiation between honeydew and nectar honeys. The classification model had a high predictive power, as the 84.4% of the group cases was correctly classified, while for the cases of chestnut, strawberry tree and sunflower honeys the respective prediction was correct by 91.3%, 95% and 100%, allowing further determination of unknown honey samples.

CONCLUSION

It seems that the characterization of monofloral honeys based on their physicochemical parameters through the proposed model can be achieved and further applied on other honey types. The results could contribute to the development of methodologies for the determination of honey's botanical origin, based on simple techniques, so that these can be applied for routine analysis. © 2021 Society of Chemical Industry.

Quality evaluation and geographical classification of immature rape and acacia honeys in China

BACKGROUND

To reflect and understand the real situation regarding immature honey, the quality parameters of 141 honey samples from different regions of China were evaluated. The possibility of classifying Chinese honey from different geographical origins was also considered.

RESULTS

The results revealed that the values of diastase, sucrose, proline and 5-hydroxymethylfurfural (HMF) met the international honey standard, although moisture, total glucose and fructose, and invertase content in most of the honey samples failed to meet the standards. In addition, honey from different geographical locations could be well separated based on the contents of maltose, sucrose, HMF and glucose oxidase.

CONCLUSION

The maturity of honey has a great impact on its quality, and the geographical origin of immature honey could be classified according to the physicochemical parameters. © 2021 Society of Chemical Industry.

An attempt to classify the botanical origin of honey using visible spectroscopy

BACKGROUND

The production of honey, and especially the unifloral varieties, is limited by factors such as weather conditions or the availability of nectar flow and honeydew. This results in a deficit in supply leading to the adulteration of honey. If they are not properly labeled, customers cannot distinguish artificial / synthetic products from real honey. Currently, the basic, commonly used method for determining the varieties of honey (botanical origin) is palynological analysis. However, this procedure is quite difficult owing to the dearth of experienced staff in the field of melissopalynology.

RESULTS

A method for identifying and classifying natural honey accurately based on its botanical origin has therefore been proposed. This analysis would rely on the visible light spectra transmitted through a relatively thin layer of the substance of interest, regardless of deviations in thickness. We present algorithms for analyzing the transmittance spectra-parametrization based on polynomial approximation (PMA) and applying a method for spectra selection and reduction (SSR) and a classical classification model (decision tree). A comparison is presented of the classification of four varieties of honey, confirmed by pollen analysis, obtained from the analysis of optically measured transmittance spectra of the samples. The algorithms that are compared contain a decision tree that uses raw data, data reduced by principal component analysis (PCA), and data after calculations based on the proposed algorithms alone (PMA and SSR) and together with the PCA method.

CONCLUSION

This novel method produced outstanding results in comparison with the standard PCA method and is helpful in identifying the botanical origin of honey effectively. © 2021 Society of Chemical Industry.

Improved KS-GMM algorithm applied in classification and recognition of honey based on laser-induced fluorescence spectra

The laser-induced fluorescence (LIF) technique, which has been widely used for food testing, can be combined with various algorithms to classify and recognize different kinds of honey. This paper proposes the Kolmogorov-Smirnov test-Gaussian mixture model (KS-GMM) algorithm, which is coupled with the LIF technique to realize accurate classification and recognition of different types of pure honey. The experiments are designed and carried out to obtain a set of LIF spectrum data from various honey and syrup samples. The proposed KS-GMM algorithm is applied for classification and recognition, with GMM, k-nearest neighbor (kNN), and decision tree algorithms as cross-validation methods. By comparing recognition results of training sets containing different amounts of data, it is found that the KS-GMM algorithm exhibits a maximum recognition accuracy of 96.52%. The research results prove that the KS-GMM algorithm outperforms, to the best of our knowledge, the other three algorithms in classifying and recognizing the honey types.

Botanical origin discrimination of Greek honeys: physicochemical parameters versus Raman spectroscopy

BACKGROUND

The authenticity of honey is of high importance since it affects its commercial value. The discrimination of the origin of honey is of prime importance to reinforce consumer trust. In this study, four chemometric models were developed based on the physicochemical parameters according to European and Greek legislation and one using Raman spectroscopy to discriminate Greek honey samples from three commercial monofloral botanical sources.

RESULTS

The results of physicochemical (glucose, fructose, electrical activity) parameters chemometric models showed that the percentage of correct recognition fluctuated from 92.2% to 93.8% with cross-validation 90.6-92.2%, and the placement of test set was 79.0-84.3% successful. The addition of maltose content in the previous discrimination models did not significantly improve the discrimination. The corresponding percentages of the Raman chemometric model were 95.3%, 90.6%, and 84.3%.

CONCLUSION

The five chemometric models developed presented similar and very satisfactory results. Given that the recording of Raman spectra is simple, fast, a minimal amount of sample is needed for the analysis, no solvent (environmentally friendly) is used, and no specialized personnel are required, we conclude that the chemometric model based on Raman spectroscopy is an efficient tool to discriminate the botanical origin of fir, pine, and thyme honey varieties. © 2020 Society of Chemical Industry.

Chemical Analyses and Antimicrobial Activity of Nine Kinds of Unifloral Chinese Honeys Compared to Manuka Honey (12+ and 20+)

Honey has good antimicrobial properties and can be used for medical treatment. The antimicrobial properties of unifloral honey varieties are different. In this study, we evaluated the antimicrobial and antioxidant activities of nine kinds of Chinese monofloral honeys. In addition, headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS) technology was used to detect their volatile components. The relevant results are as follows: 1. The agar diffusion test showed that the diameter of inhibition zone against Staphylococcus aureus of Fennel honey (21.50 ± 0.41 mm), Agastache honey (20.74 ± 0.37 mm), and Pomegranate honey (18.16 ± 0.11 mm) was larger than that of Manuka 12+ honey (14.27 ± 0.10 mm) and Manuka 20+ honey (16.52 ± 0.12 mm). The antimicrobial activity of Chinese honey depends on hydrogen peroxide. 2. The total antioxidant capacity of Fennel honey, Agastache honey, and Pomegranate honey was higher than that of other Chinese honeys. There was a significant positive correlation between the total antioxidant capacity and the total phenol content of Chinese honey (r = 0.958). The correlation coefficient between the chroma value of Chinese honey and the total antioxidant and the diameter of inhibition zone was 0.940 and 0.746, respectively. The analyzed dark honeys had better antimicrobial and antioxidant activities. 3. There were significant differences in volatile components among Fennel honey, Agastache honey, Pomegranate honey, and Manuka honey. Hexanal-D and Heptanol were the characteristic components of Fennel honey and Pomegranate honey, respectively. Ethyl 2-methylbutyrate and 3-methylpentanoic acids were the unique compounds of Agastache honey. The flavor fingerprints of the honey samples from different plants can be successfully built using HS-GC-IMS and principal component analysis (PCA) based on their volatile compounds. Fennel honey, Agastache honey, and Pomegranate honey are Chinese honey varieties with excellent antimicrobial properties, and have the potential to be developed into medical grade honey.

Honey Volatiles as a Fingerprint for Botanical Origin-A Review on their Occurrence on Monofloral Honeys

Honeys have specific organoleptic characteristics, with nutritional and health benefits, being highly appreciated by consumers, not only in food but also in the pharmaceutical and cosmetic industries. Honey composition varies between regions according to the surrounding flora, enabling its characterization by source or type. Monofloral honeys may reach higher market values than multifloral ones. Honey's aroma is very specific, resulting from the combination of volatile compounds present in low concentrations. The authentication of honey's complex matrix, according to its botanical and/or geographical origin, represents a challenge nowadays, due to the different sorts of adulteration that may occur, leading to the search for reliable marker compounds for the different monofloral honeys. The existing information on the volatiles of monofloral honeys is scarce and disperse. In this review, twenty monofloral honeys and honeydews, from acacia, buckwheat, chestnut, clover, cotton, dandelion, eucalyptus, fir tree, heather, lavender, lime tree, orange, pine, rape, raspberry, rhododendron, rosemary, strawberry tree, sunflower and thyme, were selected for volatile comparison purposes. Taking into consideration the country of origin, the technique of isolation and analysis, the five main volatiles from each of the honeys are compared. Whereas some compounds were found in several types of monofloral honey, and thus not considered good volatile markers, some monofloral honeys revealed characteristic volatile compounds independently of their provenance.

Antibacterial potential of Swiss honeys and characterisation of their bee-derived bioactive compounds

BACKGROUND

Antibacterial activity of honey is not only crucial characteristic in selection of honey for medical usage but also an important honey quality marker. The aim of the study was to characterise the antibacterial potential of 29 honey samples representing the main types of multi-floral blossom and honeydew honeys produced in Switzerland. Antibacterial activity against Staphylococcus aureus and Pseudomonas aeruginosa was expressed as a minimum inhibitory and bactericidal concentrations (MIC and MBC). Furthermore, the content of bee-derived glucose oxidase (GOX) and its enzymatic product, H₂ O₂ , were also evaluated.

RESULTS

All honey samples successfully met basic defined criteria (moisture and hydroxymethylfurfural (HMF)) tested in this study. Honeydew honeys were the most effective honey samples and generated the highest levels of H₂ O₂ . A strong significant correlation was found between the overall antibacterial activity and the level of H₂ O₂ among all honey samples. Interestingly, the content of GOX in honey samples did not correlate with their antibacterial activity as well as H₂ O₂ production capacity. A weak antibacterial activity was determined in five floral honeys, most likely due to increased enzymatic activity of pollen-derived catalase.

CONCLUSION

This study showed that antibacterial effect of Swiss honey samples is associated mainly with H₂ O₂ . © 2019 Society of Chemical Industry.

Using an automatic pulse voltammetric electronic tongue to verify the origin of honey from Spain, Honduras, and Mozambique

BACKGROUND

The growing need to classify the origin of honey in a simple way is leading to the development of affordable analytical equipment that is in-line and manageable, enabling rapid on-site screening. The aim of this work was therefore to evaluate whether an electronic tongue (made of four metallic electrodes: Ir, Rh, Pt, Au), based on potential multistep pulse voltammetry with electrochemical polishing, is able to differentiate between honey samples from Spain, Honduras, and Mozambique.

RESULTS

It was demonstrated, for the first time, that automatic pulse voltammetry, in combination with principal component analysis (PCA) statistical analysis, was able to differentiate honey samples from these three countries. A partial least squares (PLS) analysis predicted the level of certain physicochemical parameters, the best results being for conductivity and moisture with correlation coefficients of 0.948 and 0.879, whereas the weakest correlation was for the sugars.

CONCLUSION

The tool proposed in this study could be applied to identify the country origin of the three types of multifloral honey considered here. It also offers promising perspectives for expanding knowledge of the provenance of honey. All of this could be achieved when a comprehensive database with the information generated by this electronic tongue has been created. © 2019 Society of Chemical Industry.

Untargeted and Targeted Discrimination of Honey Collected by Apis cerana and Apis mellifera Based on Volatiles Using HS-GC-IMS and HS-SPME-GC-MS

Fraudulent acts regarding honey authenticity that use Apis mellifera honey as a substitute for Apis cerana honey have garnered considerable concern in China and triggered a trust crisis from consumers. In this study, untargeted metabolomics analysis was carried out based on volatile fractions in honey from A. cerana and A. mellifera using headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS). Honey from A. cerana and A. mellifera was discriminated by HS-GC-IMS profiling, principal component analysis, and orthogonal partial least-squares discrimination analysis. Tentative markers were identified from p-values and the variable importance in projection analysis and confirmed using the retention index, mass fragments, and reference standards by gas chromatography-mass spectrometry (GC-MS). A targeted method was established using the headspace solid phase coupled with microextraction GC-MS (HS-SPME-GC-MS) to quantitate the markers. The results demonstrated that the developed untargeted and targeted metabolomics approach performed well when discriminating honey from A. cerana and A. mellifera.

Bioactive Components and Antioxidant and Antibacterial Activities of Different Varieties of Honey: A Screening Prior to Clinical Application

This study assessed 16 different honey samples in order to select the best one for therapeutic purposes. First, a study of honey's main bioactive compounds was carried out. Then phenolic profiles were determined and specific compounds quantified using a HPLC system coupled to a mass spectrometer. Then, antioxidant activity, by three in vitro methods, and antibacterial activity against reference strains and clinical isolates were evaluated. Great variability among samples was observed regarding ascorbic acid (between 0.34 ± 0.00 and 75.8 ± 0.41 mg/100 g honey; p < 0.001), total phenolic compounds (between 23.1 ± 0.83 and 158 ± 5.37 mg/100 g honey; p < 0.001), and total flavonoid contents (between 1.65 ± 0.11 and 5.93 ± 0.21 mg/100 g honey; p < 0.001). Forty-nine different phenolic compounds were detected, but only 46 of them were quantified by HPLC. The concentration of phenolic compounds and the phenolic profiles varied widely among samples (between 1.06 ± 0.04 and 18.6 ± 0.73 mg/100 g honey; p < 0.001). Antioxidant activity also varied significantly among the samples. All honey varieties exhibited antibacterial activity against both reference and clinical strains (effective concentrations ranged between 0.05 and 0.40 g/mL depending on the honey sample and bacteria tested). Overall, samples with better combinations of bioactive properties were avocado and chestnut honeys.

Terahertz time-domain attenuated total reflection spectroscopy applied to the rapid discrimination of the botanical origin of honeys

A new technique to identify the floral resources of honeys is demanded. Terahertz time-domain attenuated total reflection spectroscopy combined with chemometrics methods was applied to discriminate different categorizes (Medlar honey, Vitex honey, and Acacia honey). Principal component analysis (PCA), cluster analysis (CA) and partial least squares-discriminant analysis (PLS-DA) have been used to find information of the botanical origins of honeys. Spectral range also was discussed to increase the precision of PLS-DA model. The accuracy of 88.46% for validation set was obtained, using PLS-DA model in 0.5-1.5THz. This work indicated terahertz time-domain attenuated total reflection spectroscopy was an available approach to evaluate the quality of honey rapidly.

The determination of the botanical origin in honeys with over-represented pollen: combination of melissopalynological, sensory and physicochemical analysis

BACKGROUND

Pollen analysis of honey is the basic method for the determination of its botanical origin. However, the presence of over-represented pollen in honeys may lead the analysis to false results. This can be more severe if this pollen is present in unifloral under-represented honeys of commercial importance (e.g. thyme honey). In the present study, we investigated the abundance of over-represented pollen grains on several quality characteristics in honey samples. In particular, we mixed honeys characterised as over-represented, specifically chestnut and eucalyptus, with thyme honeys in different analogies, and we also analysed the melissopalynological, organoleptic, physicochemical (water content, electrical conductivity, colour) and volatile characteristics of the blends.

RESULTS

The most sensitive parameters were the microscopic characteristics, followed by the organoleptic ones. Blends of thyme honey with an originally low percentage of thyme pollen were the most influenced and could not be characterised as unifloral regarding their melissopalynological characteristics, even when they were mixed with small quantities of honeys with over-represented pollen (i.e. 5%).

CONCLUSION

The present study confirms that, in the case of presence of over-represented pollen in honeys, pollen analysis alone cannot give trustworthy results for the determination of the botanical origin, even though their exclusion during pollen analysis, when they are present in percentages of up to 30%, could provide more accurate results. Consequently, pollen analysis should also be combined with the other analyses, especially in honeys with under-represented and over-represented pollens, to give safer results for the botanical characterisation of honeys. © 2017 Society of Chemical Industry.

Honeydew Honeys: A Review on the Characterization and Authentication of Botanical and Geographical Origins

The commercial interest in honeydew honeys (from the secretions of plants or the excretions of plant-sucking insects found on plants) is increasing because of their higher therapeutic properties compared with those of most blossom honeys (from nectar). However, honeydew honeys have been less studied than blossom honeys. In this work, studies carried out to characterize and authenticate honeydew honeys by their botanical and geographical origins have been reviewed. The identification of honey origins has been approached by two ways: by the analysis of chemical markers and by the development of analytical methodologies combined with multivariate analyses. Some compounds have been suggested as specific botanical markers of several honeydew honeys, such as quercitol and trans-oak lactone for oak honey, 2-aminoacetophenone and propylanisol for holm oak honey, and 1-chloro-octane and tridecane for pine honey. The presence of 3-carene and an unidentified compound in samples was proposed as a way discriminate between Greek and Turkish pine honeys. Chemometric analyses have been applied on chemical compositions and on physicochemical, microscopic, and spectral parameters and have proved to be valuable methods for authenticating honeydew honeys. Analytical methods based on spectral information are suitable for the routine control of honeydew-honey origins because they are fast and require easy sample preparations.

"More than Honey": Investigation on Volatiles from Monovarietal Honeys Using New Analytical and Sensory Approaches

Eight monovarietal honeys from dandelion, fir tree, linden tree, chestnut tree, robinia, orange, lavender, and rape were investigated with respect to their volatile compounds and sensory properties. Analysis of the volatile compounds was performed by gas chromatographic techniques (one-dimensional GC-MS as well as comprehensive GC×GC-MS). For sensory evaluation Napping in combination with ultraflash profiling was applied using sensory experts. For dandelion honey, 34 volatile compounds are described for the first time to be present in dandelion honey. PCA and cluster analysis of the volatile compounds, respectively, show high correlation with the PCA obtained from sensory evaluation. Lavender and linden honey showed sensory characteristics that were not expected from these honey types. Analysis of the volatile compounds resulted in the identification of odor-active compounds that are very likely derived from sources other than the respective honeyflow. Contamination with essential oils used in apiculture is very likely to be the reason for the occurrence of these compounds in the investigated honeys.

Characterization of Chinese Unifloral Honeys Based on Proline and Phenolic Content as Markers of Botanical Origin, Using Multivariate Analysis

The phenolic and proline content were determined in honey samples of different floral origins (rapeseed, sunflower, buckwheat and Codonopsis) from five different regions of China. The phenolic and proline profile of these samples were used to construct a statistical model to distinguish honeys from different floral origins. Significant differences were identified among the studied honey samples from multivariate chemometric methods. The proline content varied among the four types of honeys, with the values decreasing in the order: buckwheat > Codonopsis > sunflower > rapeseed. Rapeseed honeys contained a high level of benzoic acid, while rutin, p-coumaric acid, p-hydroxybenzoic acid were present at relatively high levels in buckwheat honeys. Principal component analysis (PCA) revealed that rapeseed honey could be distinguished from the other three unifloral honeys, and benzoic acid, proline and kaempferol could serve as potential floral markers. Using 18 phenolic compounds and proline the honey samples were satisfactorily classified according to floral origin at 94% correct prediction by linear discriminant analysis (LDA). The results indicated that phenolic compounds and proline were useful for the identification of the floral origin of the four type honeys.

Antioxidant activity and physico-chemical parameters for the differentiation of honey using a potentiometric electronic tongue

BACKGROUND

This work evaluates the capacity of a potentiometric electronic tongue to differentiate between types of honey (orange blossom, rosemary, thyme, sunflower, winter savory and honeydew honey) according to their antioxidant level. The classical procedures used to evaluate the antioxidant potential of honey are inappropriate for in situ monitoring on reception of batches of raw honey in the packaging industry. They are also destructive, time-consuming and very tedious, requiring highly expert analysts and specialised equipment.

RESULTS

The electronic tongue system made with Ag, Ni, Co, Cu and Au was able to not only differentiate between types of honey but also to predict their total antioxidant capacity. The discrimination ability of the system was proved by means of a fuzzy ARTMAP type ANN, with 100% classification success. A prediction multiple linear regression model showed that the best correlation coefficient was for antioxidant activity (0.9666), then for electrical conductivity (0.8959) and to a lesser extent for a_w , moisture and colour.

CONCLUSION

The proposed measurement system could be a quick, easy option for the honey packaging sector to provide continuous in-line information about a characteristic as important as the antioxidant level. © 2016 Society of Chemical Industry.

Discrimination of honeys using colorimetric sensor arrays, sensory analysis and gas chromatography techniques

Aroma profiles of six honey varieties of different botanical origins were investigated using colorimetric sensor array, gas chromatography-mass spectrometry (GC-MS) and descriptive sensory analysis. Fifty-eight aroma compounds were identified, including 2 norisoprenoids, 5 hydrocarbons, 4 terpenes, 6 phenols, 7 ketones, 9 acids, 12 aldehydes and 13 alcohols. Twenty abundant or active compounds were chosen as key compounds to characterize honey aroma. Discrimination of the honeys was subsequently implemented using multivariate analysis, including hierarchical clustering analysis (HCA) and principal component analysis (PCA). Honeys of the same botanical origin were grouped together in the PCA score plot and HCA dendrogram. SPME-GC/MS and colorimetric sensor array were able to discriminate the honeys effectively with the advantages of being rapid, simple and low-cost. Moreover, partial least squares regression (PLSR) was applied to indicate the relationship between sensory descriptors and aroma compounds.

Fluorescence markers in some New Zealand honeys

The fluorescence characteristics of various New Zealand honeys were investigated to establish if this technique might detect signatures unique to manuka (Leptospermum scoparium) and kanuka (Kunzea ericoides) honeys. We found unique fluorescence profiles for these honeys which distinguished them from other New Zealand honey floral types. Two excitation-emission (ex-em) marker wavelengths each for manuka and kanuka honeys were identified; manuka honey at 270-365 (MM1) and 330-470 (MM2) nm and kanuka honey at 275-305 (KM1) and 445-525 (KM2) nm. Dilution of manuka and kanuka honeys with other honey types that did not possess these fluorescence profiles resulted in a proportional reduction in fluorescence signal of the honeys at the marker wavelengths. By comparison, rewarewa (Knightia excelsa), kamahi (Weinmannia racemosa), and clover (Trifolium spp.) honeys did not exhibit unique fluorescence patterns. These findings suggests that a fluorescence-based screening approach has potential utility for determining the monoflorality status of manuka and kanuka honeys.

Classification of Chinese Honeys According to Their Floral Origins Using Elemental and Stable Isotopic Compositions

The objective of this study is to test the feasibility of multi-isotopic and elemental analyses combined with chemometric techniques for differentiating the botanical origins of major honey products in China. The stable isotope and elemental compositions of 57 honey samples from four major floral origins in China (i.e., rape honey, acacia honey, vitex honey, and jujube honey) were analyzed using stable isotope ratio mass spectrometry (IRMS) and inductively coupled plasma mass spectrometry (ICP-MS), respectively. The results showed that hydrogen and oxygen isotopes could be more suitable than the carbon isotope for discriminating the floral origins of major honeys in China. There were significant differences in the contents of most elements between or among different floral origins. The combination of IRMS and ICP-MS methods provides the most effective and accurate approach (in most cases close to 100% accuracy) for classifying Chinese honeys according to their floral origins.

Activities of different types of Thai honey on pathogenic bacteria causing skin diseases, tyrosinase enzyme and generating free radicals

BACKGROUND

Honey is a natural product obtained from the nectar that is collected from flowers by bees. It has several properties, including those of being food and supplementary diet, and it can be used in cosmetic products. Honey imparts pharmaceutical properties since it has antibacterial and antioxidant activities. The antibacterial and antioxidant activities of Thai honey were investigated in this study.

RESULTS

The honey from longan flower (source No. 1) gave the highest activity on MRSA when compared to the other types of honey, with a minimum inhibitory concentration of 12.5% (v/v) and minimum bactericidal concentration of 25% (v/v). Moreover, it was found that MRSA isolate 49 and S. aureus were completely inhibited by the 50% (v/v) longan honey (source No. 1) at 8 and 20 hours of treatment, respectively. Furthermore, it was observed that the honey from coffee pollen (source No. 4) showed the highest phenolic and flavonoid compounds by 734.76 mg gallic/kg of honey and 178.31 mg quercetin/kg of honey, respectively. The antioxidant activity of the honey obtained from coffee pollen was also found to be the highest, when investigated using FRAP and DPPH assay, with 1781.77 mg FeSO4•7H2O/kg of honey and 86.20 mg gallic/kg of honey, respectively. Additionally, inhibition of tyrosinase enzyme was found that honey from coffee flower showed highest inhibition by 63.46%.

CONCLUSIONS

Honey demonstrates tremendous potential as a useful source that provides anti-free radicals, anti-tyrosinase and anti-bacterial activity against pathogenic bacteria causing skin diseases.

[Application of ICP-MS method in the determination of mineral elements in vitex honey for the classification of their geographical origins with chemometric approach]

In the present work, the contents of 38 elements of 65 vitex (Vitex negundo var. heterophylla Rehd. ) honey samples from Shunyi of Beijing, Fuping and Pingshan of Hebei province were determined by inductively coupled plasma mass spectrometry (ICP-MS). Among them, B, Na, Mg, P, K, Ca, Fe and Zn were the most abundant elements with mean contents more than 1 mg kg-1. It can be found that there were relationships between the contents of elements and the geographical origin of vitex honey samples. Taking the contents of 29 out of 38 mineral elements (Na, Mg, Al, K, Ti, V, Mn, Fe, Ni, Cu, Zn, Ga, As, Sr, Y, Mo, Cd, Ba, La, Ce, Pr, Nd, Sm, Gd, Dy, Ho, T1, Pb and U) as variables, the chemometric methods, such as principal component analysis (PCA) and back-propagation artificial neural network (BP-ANN), were applied to classify vitex honey samples according to their geographical origins. PCA reduced all of the variables to four principal components and could explain 81. 6% of the total variances. The results indicated that PCA could mainly classify the vitex honey samples into three groups. BP-ANN was explored to construct classification model of vitex honeys according to their geographical origin. For the whole data set, the overall correct classification rate and cross-validation (leave one out method) rate of proposed BP-ANN model was 100% and 95. 4%, respectively. To further test the stability of the model developed for prediction, 75% of honey samples of each geographical origin were randomly selected for the model training set, and the remaining samples were classified with the use of the constructed model. Both the overall correct classification rate and prediction rate of proposed BP-ANN model were 100%. It is concluded that the profiles of multi-element by ICP-MS with chemometric methods could be a potential and powerful tool for the classification of vitex honey samples from different geographical origins.

[Application of inductively coupled plasma mass spectrometry with chemometric methods in classification of honeys according to their types]

In order to identify honeys according to their floral origin, inductively coupled plasma mass spectrometry (ICP-MS) combined with principal component analysis (PCA) and discriminant analysis (DA) were employed in the present study. Three kinds of honeys such as acacia honey samples, sunflower honey samples and rape honey samples were selected. It was pretreated by wet-acid digestionand measured 20 kinds of mineral elements in honey samples by ICP-MS. The result showed that the accuracy of the inductively coupled plasma mass spectrometrymeted the requirements. The result of principal component analysis demonstrated that the acacia honey samples were performed a trend of certain gather. The trend of the sunflower honey samples and the rape honey samples are not obvious. Ten kinds of mineral elements including Na, Mg, K, Ca, Sr, Ba, V, Fe, Ni, Sb can be regarded as honey varieties of characteristic elements. Seven kinds of mineral elements such as Mg, Sr, Ba, Sb, Ni, Cr and Na could be selected through stepwise discriminant analysis. Using bayes discriminant analysis, A linear discriminant function can be recieved. The discrimination rate of honey samples such as acacia honey samples, sunflower samples and rape honey samples were 100%, 80% and 90. 9% respectively. Two sunflower honey samples was misclassified into rape honey samples an-done rape honey samples are also misclassified into acacia honey sample. The total rate of discriminant model cross validation was 90. 3%. It is concluded that the mineral elements in honey varieties with good classification. The present study can provide theoretical basis and the relationship between thetypes of honey samples with mineral elements. The method what this study used had simple, accurate and stablecharacteristics, which can be used as a reliable method of honey sample identification.

The identification of the relationship between chemical and electrical parameters of honeys using artificial neural networks

A number of significant scientific studies have confirmed the health benefits of honey. Due to the high price of natural honey, it is a common target for adulteration which reduces its medicinal value. Adulteration detection methods require specific laboratory equipment and are very expensive. The development of measurement techniques enables the measurement of electrical characteristics of strained honey. Honey electrical parameters can possibly be used for its quality assessment. The identification of the relationship between chemical and electrical parameters of honeys and analysis to determine if there are frequency-dependent changes, can help in developing of that group of methods. The aim of this research was to determine how the chemical parameters of certain honeys influence the dielectric loss factor and the permittivity of strained honey measured in various frequencies. Another aim was to determine whether the percentage influence of certain chemical parameters of honeys on electrical characteristics significantly depends on frequency value. The research was based on neural network models and sensitivity analysis. The percentage influence of certain chemical parameters on electrical characteristics significantly depends on frequency value.

Chemometrics as a tool of origin determination of Polish monofloral and multifloral honeys

The aim of this study was to evaluate the application of chemometrics studies to determine the botanical origin of Polish monofloral honeys using NMR spectroscopy. Aqueous extracts of six kinds of honeys, namely, heather (Calluna vulgaris L.), buckwheat (Fagopyrum esculentum L), lime (Tilia L), rape (Brassica napus L. var. napus), acacia (Acacia Mill.), and multifloral ones, were analyzed. Multivariate chemometric data analysis was performed using principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLS-DA). Chemometric analysis supported by pollen analysis revealed the incorrect classification of acacia honeys by the producers. Characteristic motives for each honey were identified, which allowed chemical profiles of tested honeys to be built. Thus, phenylacetic acid and dehydrovomifoliol (4-hydroxy-4-[3-oxo-1-butenyl]-3,5,5-trimethylcyclohex-2-en-1-one) were proposed to be markers of Polish heather honey. Formic acid and tyrosine were found to be the most characteristic compounds of buckwheat honey, whereas 4-(1-hydroxy-1-methylethyl)cyclohexane-1,3-dienecarboxylic acid was confirmed as a marker of lime honey.

Investigating C-4 sugar contamination of manuka honey and other New Zealand honey varieties using carbon isotopes

Carbon isotopes (δ(13)C honey and δ(13)C protein) and apparent C-4 sugar contents of 1023 New Zealand honeys from 15 different floral types were analyzed to investigate which New Zealand honey is prone to failing the AOAC 998.12 C-4 sugar test and evaluate the occurrence of false-positive results. Of the 333 honey samples that exceeded the 7% C-4 sugar threshold, 324 samples of these were New Zealand manuka honey (Leptospermum scoparium, 97.2% of all fails found in the study). Three monofloral honeys (ling, kamahi, and tawari) had nine samples (2.8% of all fails found in the study) with apparent C-4 sugars exceeding 7%. All other floral types analyzed did not display C-4 sugar fails. False-positive results were found to occur for higher activity New Zealand manuka honey with a methylglyoxal content >250 mg/kg or a nonperoxide activity >10+, and for some ling, kamahi and tawari honeys. Recommendations for future interpretation of the AOAC 998.12 C-4 sugar method are proposed.

The unique manuka effect: why New Zealand manuka honey fails the AOAC 998.12 C-4 sugar method

Conversion of dihydroxyacteone (DHA) to methylglyoxal (MGO) has been shown to be the key mechanism for the growth in "apparent" C-4 sugar content in nonperoxide activity (NPA) manuka honey. This reaction is enhanced by heating and storage time and is demonstrated for the first time in clover honey adulterated with DHA purchased from a chemical supplier and in manuka honey containing naturally occurring DHA and MGO. After heating at 37 °C for 83 days, pure clover honey with no added DHA has the same apparent C-4 sugar content as at t = 0 days. The same clover honey adulterated with synthetic DHA added at t = 0 days and heated at 37 °C over the same time scale shows a change in apparent C-4 sugars from 2.8 to 5.0%. Four NPA manuka honeys heated over longer periods show an increase in apparent C-4 sugars of up to 280% after 241 days. This study strongly suggests that a protein fractionation effect occurs in the conversion of DHA to MGO in higher NPA manuka honey, rendering the remaining δ(13)C protein value more negative and falsely indicating C-4 sugar addition when using the AOAC 998.12 method.

Chemometric determination of the botanical origin for Chinese honeys on the basis of mineral elements determined by ICP-MS

In this work, the potential of mineral elements and chemometric methods as a tool to classify Chinese honeys according to their botanical origin was examined. Twelve mineral elements (Na(23), Mg(24), P(31), K(39), Ca(43), Mn(55), Fe(56), Cu(63), Zn(66), Rb(85), Sr(88), and Ba(137)) of 163 Chinese honey samples, including linden, vitex, rape, and acacia, collected from Heilongjiang, Beijing, Hebei, and Shaanxi, China, in 2013 were determined by the ICP-MS method. Principal component analysis (PCA) reduced 10 variables to four principal components and could explain 93.06% of the total variance. Partial least-squares discriminant analysis (PLS-DA) and back-propagation artificial neural network (BP-ANN) were explored to construct a classification model. By PLS-DA, the total correct classification rates for model training and cross-validation were 90.9 and 88.4%, respectively. By BP-ANN, the total correct classification rates for model training and cross-validation were 100 and 92.6%, respectively. The performance of BP-ANN was better than that of PLS-DA. The validation of the developed BP-ANN model was tested by the independent test set of 42 honey samples. Linden, vitex, and rape honey samples were predicted with an accuracy of 100%, whereas one acacia honey was predicted as rape honey with an accuracy of 92.3%. It is concluded that the profiles of mineral elements by ICP-MS with chemometric methods could be a potential and powerful tool for the classification of Chinese honey samples from different botanical origins.

Antibacterial activity of different natural honeys from Transylvania, Romania

Honey is used in food industry and medicine due to its nutritive, therapeutic and dietetic qualities. The microbiological characteristics of 10 unpasteurized honey samples of known origin, collected from Transylvania beekeepers (Romania) were determined. The antibacterial activity of these types of honey against Escherichia coli, Staphylococcus aureus, Staphylococcus epidermidis, Salmonella enteritidis, Salmonella anatum, Salmonella choleraesuis, Bacillus cereus, Bacillus subtilis subsp. spizizenii and Listeria monocytogenes strains was studied. The most sensitive to the antibacterial activity were the two staphylococus strains (the largest diameter of inhibition zone was 18 mm) and B. subtilis strains (13.5 mm). The strains of B. cereus, E. coli, L. monocytogenes and Salmonella spp. were found to present resistance to some of the honey samples. Manna, sunflower and polyfloral honeys presented high antibacterial activity while acacia and linden honeys had a lower activity in terms of the number of sensible strains. Statistical analysis shows that the type of strains and the type of honey have influence on the diameter of inhibition.

Contribution of botanical origin and sugar composition of honeys on the crystallization phenomenon

The present work provides information regarding the statistical relationships among the palynological characteristics, sugars (fructose, glucose, sucrose, melezitose and maltose), moisture content and sugar ratios (F+G, F/G and G/W) of 136 different honey types (including bramble, chestnut, eucalyptus, heather, acacia, lime, rape, sunflower and honeydew). Results of the statistical analyses (multiple comparison Bonferroni test, Spearman rank correlations and principal components) revealed the valuable significance of the botanical origin on the sugar ratios (F+G, F/G and G/W). Brassica napus and Helianthus annuus pollen were the variables situated near F+G and G/W ratio, while Castanea sativa, Rubus and Eucalyptus pollen were located further away, as shown in the principal component analysis. The F/G ratio of sunflower, rape and lime honeys were lower than those found for the chestnut, eucalyptus, heather, acacia and honeydew honeys (>1.4). A lower value F/G ratio and lower water content were related with a faster crystallization in the honey.

Amino acids profile of Serbian unifloral honeys

BACKGROUND

The free amino acids profile of 192 samples of seven different floral types of Serbian honey (acacia, linden, sunflower, rape, basil, giant goldenrod, and buckwheat) from six different regions was analysed in order to distinguish honeys by their botanical origin.

RESULTS

The most abundant amino acids were proline, alanine, phenylalanine, threonine and arginine. Based on the established amino acids profiles, some important differences have been identified among studied honey samples relying on the basic descriptive statistics data, and confirmed by multivariate chemometric methods. Principal component analysis revealed that basil honey samples form a well-defined cluster imposed with phenylalanine content. The model obtained by linear discriminant analysis might be used to distinguish basil honey from the rest of the samples, and has moderate predictive power to separate genuine acacia, linden, sunflower and rape honeys. New data for the amino acids profile of giant goldenrod and buckwheat honey samples are presented.

CONCLUSIONS

The floral origin of honey could be successfully evaluated by its amino acids profile coupled with chemometric analysis.

Floral markers of cornflower (Centaurea cyanus) honey and its peroxide antibacterial activity for an alternative treatment of digital dermatitis

Cornflower (Centaurea cyanus) honey can be characterized by a greenish yellow color and an intense flavor with a bitter aftertaste. Because cornflower honey contains only a limited amount of pollen for the verification of its floral origin, one objective was the characterization of its polyphenol and norisoprenoid contents to assign floral markers. Here, lumichrome (18.8-43.5 mg/kg), 7-carboxylumichrome, (Z/E)-3-oxo-retro-α-ionol, and 3-oxo-α-ionol appeared to be quite suitable for distinguishing cornflower honey from other unifloral honeys. Additionally, due to its comparably high hydrogen peroxide content (0.5-0.9 mM/h) and the associated antibacterial activity, cornflower honey was used as an alternative treatment of digital dermatitis on an organic dairy farm. Cows affected by this hoof disease often show severe lameness and a subsequent decline in milk yield and loss of body condition. The cows' hooves treated with cornflower honey showed significantly faster healing than the control group without any treatment.

Classification and characterization of manuka honeys based on phenolic compounds and methylglyoxal

Manuka honey from New Zealand is often considered to be a medicinal product of special value due to its high level of antimicrobial activity. Therefore, the distinct authentication of its botanical origin is of great importance. Aside from the common pollen analysis, it is in this respect particularly the analysis of the phenolic acids, flavonoids, and norisoprenoids that is described as useful. In the present study, numerous manuka honeys were analyzed by UPLC-PDA-MS/MS after solid-phase extraction and compared to other kinds of honey to define marker substances characteristic for manuka honeys. The PDA profiles obtained differed markedly from each other so that the individual honey samples could be assigned to three groups. For the honeys of group 1 the comparably high concentrations of 4-hydroxybenzoic acid, dehydrovomifoliol, and benzoic acid proved to be typical, whereas the profiles of group 2 showed high kojic acid and 2-methoxybenzoic acid intensities. The manuka honeys of group 3, on the other hand, yielded high amounts of syringic acid, 4-methoxyphenyllactic acid, and methyl syringate. Furthermore, the comprehensive comparison of manuka honeys to other unifloral honeys revealed that especially kojic acid, 5-methyl-3-furancarboxylic acid, leptosin, unedone, 2-methoxybenzoic acid, 4-methoxyphenyllactic acid, 3-hydroxy-1-(2-methoxyphenyl)penta-1,4-dione, and methyl syringate were useful for distinguishing manuka honeys from the other kinds of investigated honeys. Moreover, kojic acid, unedone, 5-methyl-3-furancarboxylic acid, 3-hydroxy-1-(2-methoxyphenyl)penta-1,4-dione, and lumichrome were identified in manuka honey for the first time.

Volatile compounds in honey: a review on their involvement in aroma, botanical origin determination and potential biomedical activities

Volatile organic compounds (VOCs) in honey are obtained from diverse biosynthetic pathways and extracted by using various methods associated with varying degrees of selectivity and effectiveness. These compounds are grouped into chemical categories such as aldehyde, ketone, acid, alcohol, hydrocarbon, norisoprenoids, terpenes and benzene compounds and their derivatives, furan and pyran derivatives. They represent a fingerprint of a specific honey and therefore could be used to differentiate between monofloral honeys from different floral sources, thus providing valuable information concerning the honey's botanical and geographical origin. However, only plant derived compounds and their metabolites (terpenes, norisoprenoids and benzene compounds and their derivatives) must be employed to discriminate among floral origins of honey. Notwithstanding, many authors have reported different floral markers for honey of the same floral origin, consequently sensory analysis, in conjunction with analysis of VOCs could help to clear this ambiguity. Furthermore, VOCs influence honey's aroma described as sweet, citrus, floral, almond, rancid, etc. Clearly, the contribution of a volatile compound to honey aroma is determined by its odor activity value. Elucidation of the aroma compounds along with floral origins of a particular honey can help to standardize its quality and avoid fraudulent labeling of the product. Although only present in low concentrations, VOCS could contribute to biomedical activities of honey, especially the antioxidant effect due to their natural radical scavenging potential.

Volatile fraction composition and physicochemical parameters as tools for the differentiation of lemon blossom honey and orange blossom honey

BACKGROUND

Volatile fraction profile and physicochemical parameters were studied with the aim of evaluating their effectiveness for the differentiation between lemon blossom honey (Citrus limon L.) and orange blossom honey (Citrus spp.). They would be useful complementary tools to the traditional analysis based on the percentage of pollen.

RESULTS

A stepwise discriminant analysis constructed using 37 volatile compounds (extracted by purge and trap and analysed by gas chromatography-mass spectrometry), and physicochemical and colour parameters (diastase, conductivity, Pfund colour and CIE L a b) together provided a model that permitted the correct classification of 98.3% of the original and 96.6% of the cross-validated cases, indicating its efficiency and robustness. This model proved its effectiveness in the differentiation of both types of honey with another set of batches from the following year.

CONCLUSION

This model, developed from the volatile compounds, physicochemical and colour parameters, has been useful for the differentiation of lemon and orange blossom honeys. Furthermore, it may be of particular interest for the attainment of a suitable classification of orange honey in which the pollen count is very low. These capabilities imply an evident marketing advantage for the beekeeping sector, since lemon blossom honey could be commercialized as unifloral honey and not as generic citrus honey and orange blossom honey could be correctly characterized.

Honey: its medicinal property and antibacterial activity

Indeed, medicinal importance of honey has been documented in the world's oldest medical literatures, and since the ancient times, it has been known to possess antimicrobial property as well as wound-healing activity. The healing property of honey is due to the fact that it offers antibacterial activity, maintains a moist wound condition, and its high viscosity helps to provide a protective barrier to prevent infection. Its immunomodulatory property is relevant to wound repair too. The antimicrobial activity in most honeys is due to the enzymatic production of hydrogen peroxide. However, another kind of honey, called non-peroxide honey (viz., manuka honey), displays significant antibacterial effects even when the hydrogen peroxide activity is blocked. Its mechanism may be related to the low pH level of honey and its high sugar content (high osmolarity) that is enough to hinder the growth of microbes. The medical grade honeys have potent in vitro bactericidal activity against antibiotic-resistant bacteria causing several life-threatening infections to humans. But, there is a large variation in the antimicrobial activity of some natural honeys, which is due to spatial and temporal variation in sources of nectar. Thus, identification and characterization of the active principle(s) may provide valuable information on the quality and possible therapeutic potential of honeys (against several health disorders of humans), and hence we discussed the medicinal property of honeys with emphasis on their antibacterial activities.

Antiradical activity of natural honeys and antifungal effect against Penicillium genera

The purpose of the study was to examine the antiradical activity of 11 natural honeys and to evaluate the antifungal properties of honey. Honey samples (10) were collected from different locations of Slovak Republic. Honeys were native to different plant species of Robinia pseudoacaccia, Brassica napus subs. napus, Castanea sativa Mill. Thymus serpyllum vulgaris and the other samples had multifloral origin. The low antiradical activitity in honey samples was determined. The best results were found in thyme honey from Rhodos (11.84 %) and Castanea honey from Nitra (10.61 %). The lowest antiradical activity was found in Acacia honey and determined to be 7.62 %. Statistically significant differences (P< 0.001) were found among thyme/Rhodos and Castanea/Nitra. The antifungal activities of honey samples were tested by 10 %, 25 % and 50 % (by mass per volume) concentration against fungi Penicillium crustosum, P. expansum, P. griseofulvum, P. raistrickii and P. verrucosum and by the agar well diffusion method. The solutions containing 10 % (by mass per volume) of honey did not have any effect on the growth of fungi. The strongest antifungal effect was shown by 50 % honey concentration against P. raistrickii.

[Nutritional and functional properties of honey]

Due to its high carbohydrate content honey is an excellent energy source and possesses some functional effects. It is especially valuable for children and sportsmen. The glycemic index of honey varies from 32 to 91 depending on botanical origin. Honey contains also a great number of other constituents in small and trace amounts. This composition possesses numerous nutritional and biological effects: antimicrobial, antioxidant, prebiotic, immunomodulating activities. There is a suggestion on consumption rates.

Application of total reflection X-ray spectrometry in combination with chemometric methods for determination of the botanical origin of Slovenian honey

This work on the botanical origin of various types of honey produced in Slovenia and based on the mineral content analyses by the total reflection X-ray spectrometry (TXRF) is a continuation of this group's preliminary work (Golob, T.; Doberšek, U.; Kump, P.; Nečemer, M. Food Chem. 2005, 91, 593-600), which introduced the analytical methodology and employed only a simple statistical evaluation and which examined the possibility to determine the botanical origin of honey samples via elemental content. A much more comprehensive study on a total of 264 major types of honey samples harvested in 2004, 2005, and 2006 and interpreting the results with up to date chemometric methods was performed in this work. Slovenia is a small country by surface area, but it is pedologically and climatically diverse, therefore offering interesting possibilities for studying the influence of these diversities on the elemental content of natural products. By employing principal component analysis (PCA) and regularized discriminant analysis (RDA) it was established that from all of the measured elements only the four characteristic key elements Cl, K, Mn, and Rb could be used to best discriminate the types of honey. It was established that the employed combination of a simple, fast, and inexpensive multielement TXRF analytical approach and the evaluation of data by chemometric methods has the potential to discriminate the botanical origins of various types of honey.

Methyl syringate: a chemical marker of asphodel (Asphodelus microcarpus Salzm. et Viv.) monofloral honey

During the liquid chromatographic study of the phenolic fraction of monofloral honeys was detected in the asphodel honey ( Asphodelus microcarpus Salzm. et Viv.) chromatogram a distinctive peak not detected in other monofloral honeys such as Arbutus unedo L., Hedysarum coronarium , Eucalyptus spp., and Galactites tomentosa . After thin layer chromatography (TLC) purification and characterization by NMR and LC-MS/MS, the compound was identified as methyl syringate (MSYR) and confirmed against an original standard. Levels of MSYR were measured in honeys of 2005, 2006, and 2007 by HPLC-DAD analysis. Level determination of MSYR was repeated in 2008 for 2006 and 2007 honeys to evaluate chemical stability of this phenolic compound. Levels of MSYR measured 1 year after the sampling did not show significant statistical differences (p < 0.05). The stability of MSYR was also confirmed by 12 asphodel honey samples collected in 2005 that showed amounts of methyl syringate comparable with those found in fresh honey. For the evaluation of MSYR origin, samples of nectars were collected from flowers and the content of MSYR was measured. Levels of MSYR in honeys are originated from the nectar with an average contribution of the nectar to the honey of 80%. Melissopalinological analysis did not allow the attribution of the honey monofloral origin because levels of asphodel pollen were <6% for all analyzed samples. Previously reported levels of MSYR for robinia, rape, chestnut, clover, linden blossom, dandelion, sunflower, thyme, manuka, and fir honeys were <5 mg/kg. For this reason, a minimum level of 122.6 mg/kg for MSYR in asphodel honeys can be considered as a chemical marker and, unlike the melissopalynological analysis, can be used for the origin attribution and to evaluate the percent of asphodel nectar in the honey.

Profiling Turkish honeys to determine authenticity using physical and chemical characteristics

Seventy authentic honey samples of 9 different floral types (rhododendron, chestnut, honeydew, Anzer (thymus spp.), eucalyptus, gossypium, citrus, sunflower, and multifloral) from 15 different geographical regions of Turkey were analyzed for their chemical composition and for indicators of botanical and geographical origin. The profiles of free amino acids, oligosaccharides, and volatile components together with water activity were determined to characterize chemical composition. The microscopic analysis of honey sediment (mellissopalynology) was carried out to identify and count the pollen to provide qualitative indicators to confirm botanical origin. Statistical analysis was undertaken using a bespoke toolbox for Matlab called Metabolab. Discriminant analysis was undertaken using partial least-squares (PLS) regression followed by linear discriminant analysis (LDA). Four data models were constructed and validated. Model 1 used 51 variables to predict the floral origin of the honey samples. This model was also used to identify the top 5 variable important of projection (VIP) scores, selecting those variables that most significantly affected the PLS-LDA calculation. These data related to the phthalic acid, 2-methylheptanoic acid, raffinose, maltose, and sucrose. Data from these compounds were remodeled using PLS-LDA. Model 2 used only the volatiles data, model 3 the sugars data, and model 4 the amino acids data. The combined data set allowed the floral origin of Turkish honey to be accurately predicted and thus provides a useful tool for authentication purposes. However, using variable selection techniques a smaller subset of analytes have been identified that have the capability of classifying Turkish honey according to floral type with a similar level of accuracy.

Additive activity of royal jelly and honey against Pseudomonas aeruginosa

As natural products garner attention in the medical field, the emergence of antibiotic-resistant strains of bacteria has confounded the current use of antibiotic therapy, leading to the re-examination of earlier remedies such as honey and royal jelly (RJ). Four varieties of honey and one variety of freshly reaped RJ were used to evaluate the additive antimicrobial action against Pseudomonas aeruginosa (ATCC 27853). Initially, honey and RJ were used separately to determine their minimum inhibitory concentration (MIC) against the tested strain. Next, sub-MIC concentrations of honey and RJ were incorporated into media to determine the minimum additive inhibitory concentration. When tested separately, the MIC of the four varieties of honey ranged from 12-18 percent (volume/volume; v/v), and that of RJ was 4 percent (v/v). When combined with RJ, each honey variety tested showed a greater than 90-percent drop in MIC using 3-percent (v/v) RJ, a 66.6-percent drop in MIC using 2-percent (v/v) RJ, and a 50-percent MIC drop with 1-percent (v/v) RJ. The MIC of RJ dropped by 75 percent when used with the half concentration of honey that alone provides the MIC and by 50 percent when used with one-third the concentration of honey that alone provides the MIC. A strong linear correlation exists between the MIC drop of each variety of honey and RJ. With increasing interest in the use of alternative therapies and as the development of antibiotic-resistant bacteria spreads, honey and RJ may receive renewed recognition as wound healers.

Evaluation of the botanical origin of estonian uni- and polyfloral honeys by amino acid content

The free amino acid content of 61 honey samples from Estonia has been determined by HPLC-UV with precolumn derivatization with diethyl ethoxymethylenemalonate. Analyzed samples were seven types of unifloral honeys and polyfloral honeys. The main amino acids found in Estonian honeys were proline and phenylalanine. The resulting data have been analyzed by t test and principal component analysis (PCA). t Test revealed that some amino acids (alpha-alanine, beta-alanine, asparagine, gamma-aminobutyric acid, glutamine, glycine, histidine, ornithine, phenylalanine, proline, serine, and tryptophan) are more potent for assigning honey botanical origin than others. PCA enabled differentiation of some honey types by their botanical origin. In the space of the two first principal components, heather honeys form a cluster that is clearly separable from, for example, polyfloral honeys. It is concluded that analysis of the free amino acid profile may serve as a useful tool to assess the botanical origin of Estonian honeys.

Multivariate analysis of attenuated total reflection-Fourier transform infrared spectroscopic data to confirm the origin of honeys

Fourier transform infrared (FT-IR) spectroscopy and chemometrics were used to verify the origin of honey samples (n=150) from Europe and South America. Authentic honey samples were collected from five sources, namely unfiltered samples from Mexico in 2004, commercially filtered samples from Ireland and Argentina in 2004, commercially filtered samples from the Czech Republic in 2005 and 2006, and commercially filtered samples from Hungary in 2006. Samples were diluted with distilled water to a standard solids content (70 degrees Brix) and their spectra (2500-12 500 nm) recorded at room temperature using an FT-IR spectrometer equipped with a germanium attenuated total reflection (ATR) accessory. First- and second-derivative and standard normal variate (SNV) data pretreatments were applied to the recorded spectra, which were analyzed using partial least squares (PLS) regression analysis, factorial discriminant analysis (FDA), and soft independent modeling of class analogy (SIMCA). In general, when an attenuated wavelength range (6800-11 500 nm) rather than the whole spectrum (2500-12 500 nm) was studied, higher correct classification rates were achieved. An overall correct classification of 93.3% was obtained for honeys by PLS discriminant analysis, while FDA techniques correctly classified 94.7% of honey samples. Correct classifications of up to 100% were achieved using SIMCA, but models describing some classes had very high false positive rates.

Geographical characterization of polyfloral and acacia honeys by nuclear magnetic resonance and chemometrics

The importance of geographical origin determination is an increasing and pressing requirement for all foods. Honey is one of the largest studied foods due to its nutritional and medicinal properties in a correct diet. In this paper, a total of 41 honey samples (polyfloral and acacia) from different countries have been analyzed in terms of (1)H NMR spectroscopy coupled with multivariate statistical methods. Unsupervised principal component analysis resulted as an efficient tool in distinguishing (1)H NMR spectra of polyfloral and acacia honey samples and for geographical characterization of the latter ones. Hierarchical projection to latent structures discriminant analysis was successfully applied for the discrimination among polyfloral honey samples of different geographical origins. (13)C NMR spectroscopy was applied to honey samples with the aim to investigate possible sugar isoforms differentiation. Our preliminary data indicated a different isoforms ratio between betaFP and betaFF only for polyfloral Argentinean samples, while Hungarian samples showed resonance shifts for some carbons of alphaFF, betaFP, betaFF, and alphaGP isoforms for both varieties. These data confirmed the potentiality of (13)C spectroscopy in food characterization, especially in sugar-based foods.

Analysis of phenolic and other aromatic compounds in honeys by solid-phase microextraction followed by gas chromatography-mass spectrometry

The solid-phase microextraction (SPME) followed by gas chromatography-mass spectrometry (GC-MS) was used for the analysis of phenolic and other aromatic compounds in honey samples from different floral origin. Different parameters affecting the efficiency of the extraction, such as the type of the stationary phase of the fiber, NaCl and acetic acid addition, and extraction time, were optimized for the detection of the maximum number of compounds in the shortest analysis time. A total of 31 compounds were detected, with most of them identified and quantified by GC-MS. The principal component analysis (PCA) was applied to the data matrix; the results allowed for the differentiation between honeydew and nectar honeys on the basis of the salicylic acid concentration. It was found that this acid has a high contribution in the honeydew group (71.2-705.9 microg/100 g of honey) compared to the nectar honey group (0-47.6 microg/100 g of honey). The comparison of data in each honey group enabled us to characterize the floral source of some honeys using some aromatic compounds as markers.

Application of cryoprobe 1H nuclear magnetic resonance spectroscopy and multivariate analysis for the verification of corsican honey

Proton nuclear magnetic resonance spectroscopy ((1)H NMR) and multivariate analysis techniques have been used to classify honey into two groups by geographical origin. Honey from Corsica (Miel de Corse) was used as an example of a protected designation of origin product. Mathematical models were constructed to determine the feasibility of distinguishing between honey from Corsica and that from other geographical locations in Europe, using (1)H NMR spectroscopy. Honey from 10 different regions within five countries was analyzed. (1)H NMR spectra were used as input variables for projection to latent structures (PLS) followed by linear discriminant analysis (LDA) and genetic programming (GP). Models were generated using three methods, PLS-LDA, two-stage GP, and a combination of PLS and GP (PLS-GP). The PLS-GP model used variables selected by PLS for subsequent GP calculations. All models were generated using Venetian blind cross-validation. Overall classification rates for the discrimination of Corsican and non-Corsican honey of 75.8, 94.5, and 96.2% were determined using PLS-LDA, two-stage GP, and PLS-GP, respectively. The variables utilized by PLS-GP were related to their (1)H NMR chemical shifts, and this led to the identification of trigonelline in honey for the first time.

Classification of Italian honeys by 2D HR-NMR

The importance of honey has been recently increased because of its nutrient and therapeutic effects, but the adulteration of honey in terms of botanical origin has increased, too. The floral origin of honeys is usually determined using melisso-palynological analysis and organoleptic characteristics, but the application of these techniques requires some expertise. A number of papers have confirmed the possibility of characterizing honey samples by selected chemical parameters. In this study high-resolution nuclear magnetic resonance (HR-NMR) and multivariate statistical analysis methods were used to identify and classify honeys of five different floral sources. The 71 honey samples (robinia, chestnut, citrus, eucalyptus, polyfloral) were analyzed by HR-NMR using both 1H NMR and heteronuclear multiple bond correlation spectroscopy (HMBC). Spectral data were analyzed by application of unsupervised and supervised pattern recognition and multivariate statistical techniques such as principal component analysis (PCA) and general discriminant analysis (GDA). The use of 1H-(13)C HMBC coupled with appropriate statistical analysis seems to be an efficient technique for the classification of honeys.

Geographical classification of honey samples by near-infrared spectroscopy: a feasibility study

The potential of near-infrared (NIR) spectroscopy to determine the geographical origin of honey samples was evaluated. In total, 167 unfiltered honey samples (88 Irish, 54 Mexican, and 25 Spanish) and 125 filtered honey samples (25 Irish, 25 Argentinean, 50 Czech, and 25 Hungarian) were collected. Spectra were recorded in transflectance mode. Following preliminary examination by principal component analysis (PCA), modeling methods applied to the spectral data set were partial least-squares (PLS) regression and soft independent modeling of class analogy (SIMCA); various pretreatments were investigated. For unfiltered honey, best SIMCA models gave correct classification rates of 95.5, 94.4, and 96% for the Irish, Mexican, and Spanish samples, respectively; PLS2 discriminant analysis produced a 100% correct classification for each of these honey classes. In the case of filtered honey, best SIMCA models produced correct classification rates of 91.7, 100, 100, and 96% for the Argentinean, Czech, Hungarian, and Irish samples, respectively, using the standard normal variate (SNV) data pretreatment. PLS2 discriminant analysis produced 96, 100, 100, and 100% correct classifications for the Argentinean, Czech, Hungarian, and Irish honey samples, respectively, using a second-derivative data pretreatment. Overall, while both SIMCA and PLS gave encouraging results, better correct classification rates were found using PLS regression.