Authentication of the botanical and geographical origin of honey by mid-infrared spectroscopy

The potential of Fourier transform mid-infrared spectroscopy (FT-MIR) using an attenuated total reflectance (ATR) cell was evaluated for the authentication of 11 unifloral (acacia, alpine rose, chestnut, dandelion, heather, lime, rape, fir honeydew, metcalfa honeydew, oak honeydew) and polyfloral honey types (n = 411 samples) previously classified with traditional methods such as chemical, pollen, and sensory analysis. Chemometric evaluation of the spectra was carried out by applying principal component analysis and linear discriminant analysis, the error rates of the discriminant models being calculated by using Bayes' theorem. The error rates ranged from <0.1% (polyfloral and heather honeys as well as honeydew honeys from metcalfa, oak, and fir) to 8.3% (alpine rose honey) in both jackknife classification and validation, depending on the honey type considered. This study indicates that ATR-MIR spectroscopy is a valuable tool for the authentication of the botanical origin and quality control and may also be useful for the determination of the geographical origin of honey.     

Authentication of the botanical and geographical origin of honey by front-face fluorescence spectroscopy

Front-face fluorescence spectroscopy, directly applied on honey samples, was used for the authentication of 11 unifloral and polyfloral honey types (n = 371 samples) previously classified using traditional methods such as chemical, pollen, and sensory analysis. Excitation spectra (220-400 nm) were recorded with the emission measured at 420 nm. In addition, emission spectra were recorded between 290 and 500 nm (excitation at 270 nm) as well as between 330 and 550 nm (excitation at 310 nm). A total of four different spectral data sets were considered for data analysis. Chemometric evaluation of the spectra included principal component analysis and linear discriminant analysis; the error rates of the discriminant models were calculated by using Bayes' theorem. They ranged from <0.1% (polyfloral and chestnut honeys) to 9.9% (fir honeydew honey) by using single spectral data sets and from <0.1% (metcalfa honeydew, polyfloral, and chestnut honeys) to 7.5% (lime honey) by combining two data sets. This study indicates that front-face fluorescence spectroscopy is a promising technique for the authentication of the botanical origin of honey and may also be useful for the determination of the geographical origin within the same unifloral honey type.     

Authentication of the botanical origin of honey by front-face fluorescence spectroscopy. A preliminary study

The potential of front-face fluorescence spectroscopy for the authentication of unifloral and polyfloral honey types (n = 57 samples) previously classified using traditional methods such as chemical, pollen, and sensory analysis was evaluated. Emission spectra were recorded between 280 and 480 nm (excit: 250 nm), 305 and 500 nm (excit: 290 nm), and 380 and 600 nm (excit: 373 nm) directly on honey samples. In addition, excitation spectra (290-440 nm) were recorded with the emission measured at 450 nm. A total of four different spectral data sets were considered for data analysis. After normalization of the spectra, chemometric evaluation of the spectral data was carried out using principal component analysis (PCA) and linear discriminant analysis (LDA). The rate of correct classification ranged from 36% to 100% by using single spectral data sets (250, 290, 373, 450 nm) and from 73% to 100% by combining these four data sets. For alpine polyfloral honey and the unifloral varieties investigated (acacia, alpine rose, honeydew, chestnut, and rape), correct classification ranged from 96% to 100%. This preliminary study indicates that front-face fluorescence spectroscopy is a promising technique for the authentication of the botanical origin of honey. It is nondestructive, rapid, easy to use, and inexpensive. The use of additional excitation wavelengths between 320 and 440 nm could increase the correct classification of the less characteristic fluorescent varieties.     

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.     

Determination by near-infrared spectroscopy of perseitol used as a marker for the botanical origin of avocado (Persea americana Mill.) honey

This paper reports the application of near-infrared (NIR) reflectance spectroscopy to determine the concentration in honey of perseitol, a sugar that is specific to avocado honey. Reference values for perseitol were obtained by high-performance liquid chromatography analysis in 109 honey samples. Although the average concentration of perseitol in honey samples was only 0.48%, accurate prediction equations were successfully developed. The regression model of modified partial least squares was superior to that of principal component regressions. Calibrations based on the first or second derivative of Log(1/R) were equally good (R(2) > 0.95). Using half of the samples for calibration and the second half for validation, the correlation between actual and predicted values of the second half was satisfactory (R(2) = 0.87), the slope did not differ from 1, bias was low (0.005%), and the standard error of prediction was relatively low (0.13%). It was concluded that NIRS analysis may be used to detect to what extent honeybees have harvested avocado nectar but not to authenticate avocado honey as unifloral.     

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.     

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.     

Lumichrome and phenyllactic acid as chemical markers of thistle (Galactites tomentosa Moench) honey

HPLC-DAD-MS/MS chromatograms of thistle (Galactites tomentosa Moench) unifloral honeys, previously selected by sensory evaluation and melissopalynological analysis, showed high levels of two compounds. One was characterized as phenyllactic acid, a common acid found in honeys, but the other compound was very unusual for honeys. This compound was extracted from honey with ethyl acetate and purified by SPE using C(18), SiOH, and NH(2) phases. Its structure was elucidated on the basis of extensive 1D and 2D NMR experiments as well as HPLC-MS/MS and Q-TOF analysis, and it was identified as lumichrome (7,8-dimethylalloxazine). Lumichrome is known to be the main product of degradation obtained in acid medium from riboflavin (vitamin B(2)), and this is the first report of the presence of lumichrome in honeys. Analysis of the G. tomentosa raw honey and flowers extracts confirmed the floral origin of this compound. The average amount of lumichrome in thistle honey was 29.4 ± 14.9 mg/kg, while phenyllactic acid was 418.6 ± 168.9 mg/kg. Lumichrome, along with the unusual high level of phenyllactic acid, could be used as a marker for the botanical classification of unifloral thistle (G. tomentosa) honey.     

NMR characterization of saccharides in Italian honeys of different floral sources

The saccharide profiles of 5 different botanical species in 86 Italian honey samples were investigated by 1H and 1H-13C NMR spectroscopy. Nineteen saccharides were identified in the aqueous extracts, namely, fructose, glucose, gentiobiose, isomaltose, kojibiose, maltose, maltulose, melibiose, nigerose, palatinose, sucrose, turanose, erlose, isomaltotriose, kestose, maltotriose, melezitose, raffinose, and maltotetraose. PCA performed on NMR spectral regions, in particular between 4.400 and 5.700 ppm and the fructose signal at 4.050 ppm, revealed a partial sample grouping. The score contribution plots derived from PCA performed using the mean values for the buckets of the anomeric region for each floral source allowed the identification of saccharides characterizing different honeys. OPLS-DA models were further evaluated to confirm the previous findings. OPLS-DA models were also built to highlight differences between polyfloral and high mountain polyfloral honeys and between high mountain polyfloral and rhododendron honeys, both collected at high altitude; S-plots highlighted the characteristic saccharides.     

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.     

Usefulness of amino acid composition to discriminate between honeydew and floral honeys. Application to honeys from a small geographic area

With the aim of finding methods that could constitute a solid alternative to melissopalynological and physicochemical analyses to determine the botanical origin (floral or honeydew) of honeys, the free amino acid content of 46 honey samples has been determined. The honeys were collected in a small geographic area of approximately 2000 km(2) in central Spain. Twenty-seven honey samples were classified as floral and 19 as honeydew according to their palynological and physicochemical analyses. The resulting data have been subjected to different multivariant analysis techniques. One hundred percent of honey samples have been correctly classified into either the floral or the honeydew groups, according to their content in glutamic acid and tryptophan. It is concluded that free amino acids are good indicators of the botanical origin of honeys, saving time compared with more tedious analyses.     

Determination of polarimetric parameters of honey by near-infrared transflectance spectroscopy.

NIR transflectance spectroscopy was used to determine polarimetric parameters (direct polarization, polarization after inversion, specific rotation in dry matter, and polarization due to nonmonosaccharides) and sucrose in honey. In total, 156 honey samples were collected during 1992 (45 samples), 1995 (56 samples), and 1996 (55 samples). Samples were analyzed by NIR spectroscopy and polarimetric methods. Calibration (118 samples) and validation (38 samples) sets were made up; honeys from the three years were included in both sets. Calibrations were performed by modified partial least-squares regression and scatter correction by standard normal variation and detrend methods. For direct polarization, polarization after inversion, specific rotation in dry matter, and polarization due to nonmonosaccharides, good statistics (bias, SEV, and R(2)) were obtained for the validation set, and no statistically (p = 0.05) significant differences were found between instrumental and polarimetric methods for these parameters. Statistical data for sucrose were not as good as those of the other parameters. Therefore, NIR spectroscopy is not an effective method for quantitative analysis of sucrose in these honey samples. However, NIR spectroscopy may be an acceptable method for semiquantitative evaluation of sucrose for honeys, such as those in our study, containing up to 3% of sucrose. Further work is necessary to validate the uncertainty at higher levels.     

Botanical origin causes changes in nutritional profile and antioxidant activity of fermented products obtained from honey

Honey as rich source of enzymatic and nonenzymatic antioxidants serves as health-promoting nutrient in the human body. Here, we present the first time a comparative study of nutritional profiles (e.g., acidities, sugar, organic acid profile, total polyphenolic, flavonoid content) for different unifloral, multifloral honeys and their fermented products, in correlation with their antioxidant activity. Additionally, an optimized method for HPLC separation of organic acids from honey was established. The total phenolic content of honey samples varied widely among the honey types compared to fermented products. High amounts of total flavonoids were quantified in heather honey, followed by raspberry, multifloral, black locust, and linden honey. A positive correlation between the content of polyphenols, flavonoids, and antioxidant activity was observed in honey samples. After fermentation, the flavonoid content of dark honey fermented products decreased significantly. Black locust and linden honeys are more suitable for fermentation because the decrease in antioxidant substances is less pronounced.     

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.     

Multivariate correlation between color and mineral composition of honeys and by their botanical origin

The mineral content and color characteristics of 77 honey samples were analyzed. Eighteen minerals were quantified for each honey. Multiple linear regression (MLR) was used to establish equations relating the colorimetric CIELAB coordinates to the mineral data. The results obtained shown that lightness (L) was significantly correlated with S, Ca, Fe, As, Pb, and Cd for the dark honey types (avocado, heather, chestnut, and honeydew). For the light and brown honey types (citrus, rosemary, lavender, eucalyptus, and thyme), C(ab) and b showed the lower correlation with the mineral content of the honeys; their regression functions involve a few independent variables (Mg and Al for b and only Al for C(ab)). Furthermore, by means of application of linear discriminant analysis to the mineral content, it was possible to obtain a model that classifies the honeys by their lightness. The prediction ability of the built model, determined with the test set method, was 85%.     

Quantitative high-performance liquid chromatography analyses of flavonoids in Australian Eucalyptus honeys

Flavonoids of nine Australian monofloral Eucalyptus honeys have been analyzed and related to their botanical origins. The mean content of total flavonoids varied from 1.90 mg/100 g of honey for stringybark (E. globoidia) honey to 8.15 mg/100 g of honey for narrow-leaved ironbark (E. crebra) honey, suggesting that species-specific differences occur quantitatively among these Eucalyptus honeys. All of the honey samples analyzed in this study have a common flavonoid profile comprising tricetin (5,7,3',4',5'-pentahydroxyflavone), quercetin (3,5,7,3',4'-pentahydroxyflavone), and luteolin (5,7,3',4'-tetrahydroxyflavone), which, together with myricetin (3,5,7,3',4',5'-hexahydroxyflavone) and kaempferol (3,5,7,4'-tetrahydroxyflavone), were previously suggested as floral markers for European Eucalyptus honeys. Thus, flavonoid analysis could be used as an objective method for the authentication of the botanical origin of Eucalyptus honeys. Moreover, species-specific differences can also be found in the composition of honey flavonoid profiles. Among these honeys, bloodwood (E. intermedia) honey contains myricetin and tricetin as the main flavonoid compounds, whereas there is no myricetin detected in yapunyah (E. ochrophloia), narrow-leaved ironbark (E. crebra), and black box (E. largiflorens) honeys. Instead, these types of Eucalyptus honeys may contain tricetin, quercetin, and/or luteolin as their main flavonoid compounds. Compared to honeys from other geographical origins, the absence or minor presence of propolis-derived flavonoids such as pinobanksin, pinocembrin, and chrysin in Australian honeys is significant. In conclusion, these results demonstrate that a common flavonoid profile exists for all of the Eucalyptus honeys, regardless of their geographical origins; the individual species-specific floral types of Eucalyptus honey so common in Australia could be possibly differentiated by their flavonoid profile differences, either qualitatively or quantitatively or both.     

Flavonoids in monospecific eucalyptus honeys from Australia

The HPLC analyses of Australian unifloral Eucalyptus honeys have shown that the flavonoids myricetin (3,5,7,3',4', 5'-hexahydroxyflavone), tricetin (5,7,3',4',5'-pentahydroxyflavone), quercetin (3,5,7,3',4'-pentahydroxyflavone), luteolin (5,7,3', 4'-tetrahydroxyflavone), and kaempferol (3,5,7, 4'-tetrahydroxyflavone) are present in all samples. These compounds were previously suggested as floral markers of European Eucalyptus honeys. The present results confirm the use of flavonoid analysis as an objective method for the botanical origin determination of eucalyptus honey. Honeys from E. camaldulensis (river red gum honey) contain tricetin as the main flavonoid marker, whereas in honeys from E. pilligaensis (mallee honey), luteolin is the main flavonoid marker, suggesting that species-specific differences can be detected with this analysis. The main difference between the flavonoid profiles of Australian and European Eucalyptus honeys is that in the Australian honeys, the propolis-derived flavonoids (pinobanksin (3,5, 7-trihydroxyflavanone), pinocembrin (5,7-dihydroxyflavanone), and chrysin (5,7-dihydroxyflavone)) are seldom found and in much smaller amounts.     

Assessment of the floral origin of honey by SDS-page immunoblot techniques

We report on the development of a novel alternative method for the assessment of floral origin in honey samples based on the study of honey proteins using immunoblot assays. The main goal of our work was to evaluate the use of honey proteins as chemical markers of the floral origin of honey. Considering that honeybee proteins should be common to all types of honey, we decided to verify the usefulness of pollen proteins as floral origin markers in honey. We used polyclonal anti-pollen antibodies raised in rabbits by repeated immunization of Sunflower (Elianthus annuus) and Eucalyptus (Eucalyptus sp.) pollen extracts. The IgG fraction was purified by immunoaffinity. These antibodies were verified with nitrocellulose blotted pollen and unifloral honey protein extracts. The antibodies anti-Sunflower pollen, bound to the 36 and 33 kDa proteins of Sunflower unifloral honey and to honey containing Sunflower pollen; and the antibodies anti-Eucalyptus sp. pollen bound to the 38 kDa proteins of Eucalyptus sp. unifloral honey in immunoblot assays. Satisfactory results were obtained in differentiating between the types of pollen analyzed and between Sunflower honey and Eucalyptus honey with less cross reactivity with other types of honey from different origin and also with good sensitivity in the detection. This immunoblot method opens an interesting field for the development of new antibodies from different plants, which could serve as an alternative or complementary method to the usual melissopalynological analysis to assess honey floral origin.     

A new methodology based on GC-MS to detect honey adulteration with commercial syrups

Honey adulterations can be carried out by addition of inexpensive sugar syrups, such as high fructose corn syrup (HFCS) and inverted syrup (IS). Carbohydrate composition of 20 honey samples (16 nectar and 4 honeydew honeys) and 6 syrups has been studied by GC and GC-MS in order to detect differences between both sample groups. The presence of difructose anhydrides (DFAs) in these syrups is described for the first time in this paper; their proportions were dependent on the syrup type considered. As these compounds were not detected in any of the 20 honey samples analyzed, their presence in honey is proposed as a marker of adulteration. Detection of honey adulteration with HFCS and IS requires a previous enrichment step to remove major sugars (monosaccharides) and to preconcentrate DFAs. A new methodology based on yeast (Saccharomyces cerevisiae) treatment has been developed to allow the detection of DFAs in adulterated honeys in concentrations as low as 5% (w/w).     

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.