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.     

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.     

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.     

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.     

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 origin of honey by near-infrared spectroscopy

Fourier transform near-infrared spectroscopy (FT-NIR) was evaluated for the authentication of eight unifloral and polyfloral honey types (n = 364 samples) previously classified using 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 corresponding error rates were calculated according to Bayes' theorem. NIR spectroscopy enabled a reliable discrimination of acacia, chestnut, and fir honeydew honey from the other unifloral and polyfloral honey types studied. The error rates ranged from <0.1 to 6.3% depending on the honey type. NIR proved also to be useful for the classification of blossom and honeydew honeys. The results demonstrate that near-infrared spectrometry is a valuable, rapid, and nondestructive tool for the authentication of the above-mentioned honeys, but not for all varieties studied.     

Multivariate analysis of NMR and FTIR data as a potential tool for the quality control of beer

In this work, principal component analysis (PCA) is applied to the FTIR-ATR and the (1)H NMR spectra of 50 beers differing in label and type (ale, lager, alcohol-free), to identify the spectral parameters that may provide rapid information about factors affecting beer production. PCA of FTIR data resulted in the separation of beers mainly according to their alcoholic content, providing little information on components other than ethanol contributing to the variability within the samples. PCA of (1)H NMR spectra, performed on the region where major beer components resonate (3.0-6.0 ppm), resulted in the separation of samples into four groups: two groups characterized by the predominance of dextrins, one group of alcohol-free beers characterized by the predominance of maltose, and one group where glucose was found to predominate. By performing PCA on aliphatic and aromatic regions, the contribution of minor components was highlighted. In particular, most ales, lagers, and alcohol-free samples could be distinguished based on their aromatic composition, thus reflecting the high sensitivity of the low-field NMR region toward different types of beer fermentation.     

Antimutagenic effect of various honeys and sugars against Trp-p-1

Honey has been used since ancient times as a flavorful sweetener and for its therapeutic and medicinal effects. Consumers' demand for natural, healthy products has driven renewed interest in honey's health benefits. The commonly encountered food mutagen, Trp-p-1, has been demonstrated to be mutagenic in bacteria and carcinogenic in animals. Chemically, honey is quite complex. Honey is comprised primarily of sugars; however, it contains many other potentially biologically active components, such as antioxidants. Sugars have been reported to display both mutagenic and antimutagenic effects in different systems; antioxidants often display antimutagenic activity. Little information exists about potential antimutagenic effects of honey. Antimutagenicity of honeys from seven different floral sources against Trp-p-1 was tested via the Ames assay and compared to that of a sugar analogue and to individually tested simple sugars. All honeys exhibited significant inhibition of Trp-p-1 mutagenicity; most demonstrated a linear correlation between percentage inhibition and log transformed honey concentration from 10 microg/mL to 20 mg/mL. Each displayed significant degrees of inhibition of mutagenicity above concentrations of 1 mg/mL, with individual variations in degree of effectiveness. Buckwheat honey displayed the greatest inhibition at 1 mg/mL, with slightly less effectiveness at higher concentrations. A sugar analogue demonstrated a pattern of inhibition similar to that of the honeys, with enhanced antimutagenicity at concentrations greater than 1 mg/mL. Glucose and fructose were also similar to honeys and were more antimutagenic than maltose and sucrose.     

Quantification of saccharides in multiple floral honeys using fourier transform infrared microattenuated total reflectance spectroscopy

Fourier transform infrared (FTIR) spectroscopy with microattenuated total reflectance (mATR) sampling accessory and chemometrics (partial least squares and principal component regression) was used for the simultaneous determination of saccharides such as fructose, glucose, sucrose, and maltose in honey. Two calibration models were developed. The first model used a set of 42 standard mixtures of fructose, glucose, sucrose, and maltose prepared over the range of concentrations normally present in honey, whereas the second model used a set of 45 honey samples from various floral and regional sources. The developed models were validated with different data sets and verified by high-performance liquid chromatography (HPLC) measurements. The R (2) values between the FTIR-mATR predicted and HPLC results of the different sugars were between 0.971 and 0.993, demonstrating the predictive ability and accuracy of the procedure.     

Effect of oxygen on volatile and sensory characteristics of Cabernet Sauvignon during secondary shelf life

The oxidation of Cabernet Sauvignon wines during secondary shelf life was studied by headspace solid-phase microextraction (HS-SPME) coupled to gas chromatography-quadrupole mass spectrometry (GC-qMS) and sensory tests, with the support of multivariate statistical analyses such as OPLS-DA loading plot and PCA score plot. Four different oxidation conditions were established during a 1-week secondary shelf life. Samples collected on a regular basis were analyzed to determine the changes of volatile chemicals, with sensory characteristics evaluated through pattern recognition models. During secondary shelf life the separation among collected samples depended on the degree of oxidation in wine. Isoamyl acetate, ethyl decanoate, nonanoic acid, n-decanoic acid, undecanoic acid, 2-furancarboxylic acid, dodecanoic acid, and phenylacetaldehyde were determined to be associated with the oxidation of the wine. PCA sensory evaluation revealed that least oxidized wine and fresh wine was well-separated from more oxidized wines, demonstrating that sensory characteristics of less oxidized wines tend toward "fruity", "citrous", and "sweetness", while those of more oxidized wines are positively correlated with "animal", "bitterness", and "dairy". The study also demonstrates that OPLS-DA and PCA are very useful statistical tools for the understanding of wine oxidation.     

Metabolite profiling of Angelica gigas from different geographical origins using 1H NMR and UPLC-MS analyses

Angelica gigas obtained from different geographical regions was characterized using (1)H nuclear magnetic resonance (NMR) spectroscopy and ultraperformance liquid chromatography-mass spectrometry (UPLC-MS) followed by multivariate data analyses. Principal component analysis (PCA) and orthogonal partial least-squares-discriminant analysis (OPLS-DA) score plots from (1)H NMR and UPLC-MS data sets showed a clear distinction among A. gigas from three different regions in Korea. The major metabolites that contributed to the discrimination factor were primary metabolites including acetate, choline, citrate, 1,3-dimethylurate, fumarate, glucose, histamine, lactose, malate, N-acetylglutamate, succinate, and valine and secondary metabolites including decursin, decursinol, nodakenin, marmesin, 7-hydroxy-6-(2R-hydroxy-3-methylbut-3-ethyl)coumarin in A. gigas roots. The results demonstrate that (1)H NMR and UPLC-MS-based metabolic profiling coupled with chemometric analysis can be used to discriminate the geographical origins of various herbal medicines and to identify primary and secondary metabolites responsible for discrimination.     

Identification of the production chain of Asiago d'Allevo cheese by nuclear magnetic resonance spectroscopy and principal component analysis

In the present work, a rapid and simple NMR method to discriminate Asiago d'Allevo cheese samples from different production chains is described. A fast and reproducible extraction of the organic fraction was employed. By applying chemometric analysis to NMR data, it is possible to differentiate PDO Asiago cheese produced in alpine farms from that produced in lowland and mountain industrialized factories. PCA of both (1)H and (13)C NMR spectra showed a good separation of alpine farm products from the other ones, whereas the lowland and mountain industrialized cheeses are undistinguishable. The samples were differentiated on the basis of a higher content of unsaturated fatty acids, principally oleic, linoleic, linolenic, and conjugated linoleic acids for the alpine farm cheeses and a higher content of saturated fatty acids for the industrialized products. Conjugated linoleic acid and 1-pentene are also discriminating components.     

1H NMR based metabolic profiling in the evaluation of Japanese green tea quality

Classification of tea quality is now mainly performed according to the sensory results by professional tea tasters. However, this evaluation method is inconsistent in differentiating their qualities. A combination of a (1)H NMR technique and a multivariate analysis was introduced to the quality evaluation of green tea by means of a metabolomic technique. A broad range of metabolites were detected by (1)H NMR spectrometry. The principal component analysis (PCA) was used to reduce the complexity of the (1)H NMR spectra data set and provided the quality discrimination result. It offered an extensive clue for classification and quality assessment without any prepurification method. A set of green teas from a Japanese tea contest were analyzed by (1)H NMR to classify the quality with respect to that judged by tea tasters and to conceive a quality prediction model. Metabolic profiling and fingerprinting of (1)H NMR spectra of green teas with different quality were studied. PCA showed a separation between the high- and the low-quality green teas. The taste marker compounds contributing to the discrimination of tea quality were identified. Reliable prediction models were obtained by the partial least-squares projection to latent structure (PLS) analysis together with a preprocessing filter of both orthogonal signal correction (OSC) and a combination between OSC and wavelet transform algorithms.     

Major components of honey analysis by near-infrared transflectance spectroscopy

NIR transflectance spectroscopy was used to analyze fructose, glucose, and moisture in honey. A total of 161 honey samples were collected during 1992 (46), 1995 (58), and 1996 (57). Samples were analyzed by instrumental, enzymatic (fructose and glucose), and refractometric (moisture) methods. Initially, different calibrations were performed for each of the 3 years of sampling. Good predictions were obtained for all three components with equations of the particular year. But good predictions were not always obtained when the equations calculated one year were applied to samples from another year. To perform a lasting calibration, unique calibration (121 samples) and validation (40 samples) sets were built; honeys of the 3 years were included in both sets. Good statistics (bias, standard error of validation (SEV), and R(2)) were obtained for all three components of the validation set. No statistically significant differences (p = 0.05) were found between instrumental and reference methods.     

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.     

Metabolic dependence of green tea on plucking positions revisited: a metabolomic study

The dependence of global green tea metabolome on plucking positions was investigated through (1)H nuclear magnetic resonance (NMR) analysis coupled with multivariate statistical data set. Pattern recognition methods, such as principal component analysis (PCA) and orthogonal projection on latent structure-discriminant analysis (OPLS-DA), were employed for a finding metabolic discrimination among fresh green tea leaves plucked at different positions from young to old leaves. In addition to clear metabolic discrimination among green tea leaves, elevations in theanine, caffeine, and gallic acid levels but reductions in catechins, such as epicatechin (EC), epigallocatechin (EGC), epicatechin-3-gallate (ECG), and epigallocatechin-3-gallate (EGCG), glucose, and sucrose levels were observed, as the green tea plant grows up. On the other hand, the younger the green tea leaf is, the more theanine, caffeine, and gallic acid but the lesser catechins accumlated in the green tea leaf, revealing a reverse assocation between theanine and catechins levels due to incorporaton of theanine into catechins with growing up green tea plant. Moreover, as compared to the tea leaf, the observation of marked high levels of theanine and low levels of catechins in green tea stems exhibited a distinct tea plant metabolism between the tea leaf and the stem. This metabolomic approach highlights taking insight to global metabolic dependence of green tea leaf on plucking position, thereby providing distinct information on green tea production with specific tea quality.     

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.     

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).     

Origin of the high-frequency resonances in 1H NMR spectra of muscle tissue: an in vitro slow magic-angle spinning study

High-resolution slow magic-angle spinning (150 Hz) 1H PASS NMR spectroscopy is performed on intact excised rat m. tibialis anterior. Untreated muscles and muscles in vitro incubated in Krebs-Ringers buffer based on deuterium oxide are investigated. In the high-frequency region of the 1H NMR spectra, resonances from H4 (approximately 7.1-7.2 ppm) and H2 (approximately 8.2-8.5 ppm) in histidine are observed. In addition, a resonance appears at 6.7 ppm for the untreated muscles. However, this resonance is absent in muscles following incubation in deuterium oxide. On the basis of its behavior in deuterium oxide combined with supplementary measurements for creatine solutions, the 6.7 ppm resonance is ascribed to the amino protons in creatine. Moreover, the present study demonstrates that the observation of the 6.7 ppm resonance depends on pH, which explains earlier reports stating its occasional appearance. Finally, measurements on solutions of ATP/AMP and histidine indicate that both ATP/AMP and histidine contribute to the resonances at approximately 8.2-8.5 ppm in the 1H NMR spectra of muscle tissue.     

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.