1H nuclear magnetic resonance spectra of chloroform extracts of honey for chemometric determination of its botanical origin

Development of a LC-QTOF-MS based dilute-and-shoot approach for the botanical discrimination of honeys

Honeys of particular botanical origins can be associated with premium market prices, a trait which also makes them susceptible to fraud. Currently available authenticity testing methods for botanical classification of honeys are either time-consuming or only target a few "known" types of markers. Simple and effective methods are therefore needed to monitor and guarantee the authenticity of honey. In this study, a 'dilute-and-shoot' approach using liquid chromatography (LC) coupled to quadrupole time-of-flight-mass spectrometry (QTOF-MS) was applied to the non-targeted fingerprinting of honeys of different floral origin (buckwheat, clover and blueberry). This work investigated for the first time the impact of different instrumental conditions such as the column type, the mobile phase composition, the chromatographic gradient, and the MS fragmentor voltage (in-source collision-induced dissociation) on the botanical classification of honeys as well as the data quality. Results indicated that the data sets obtained for the various LC-QTOF-MS conditions tested were all suitable to discriminate the three honeys of different floral origin regardless of the mathematical model applied (random forest, partial least squares-discriminant analysis, soft independent modelling by class analogy and linear discriminant analysis). The present study investigated different LC-QTOF-MS conditions in a "dilute and shoot" method for honey analysis, in order to establish a relatively fast, simple and reliable analytical method to record the chemical fingerprints of honey. This approach is suitable for marker discovery and will be used for the future development of advanced predictive models for honey botanical origin.

Enabling honey quality and authenticity with NMR and LC-IRMS based platform

Honey has been known for economically motivated adulteration around the world, because of its high demand and short supply. As consequence increasing honey production using the deliberate addition of sugar syrups while claiming a fictitious origin and diversifying it to increase its value. Generally, honey testing is supervised by a set of guidelines and quality parameters to ensure its quality and authenticity. As per the many regulatory bodies, current honey scams have been challenging to identify with conventional methods, so quality control labs require sophisticated technology. With these paradigm shifts, the aim of the present review is focused on the authenticity of honey through two important cutting-edge methods viz LC-IRMS and NMR. The LC-IRMS aids in the detection of added C₃ and C₄ sugars. Whereas NMR has provided a potent solution by allowing the classification of botanical varieties and geographical origin along with the quantification of a set of quality parameters in a single experiment.

Automatic nmr-based protocol for assessment of honey authenticity

¹H NMR analysis of organic extracts of honey is a powerful technique to confirm its botanical origin, thanks to the presence of signals that are specific to each floral typology. Similarly, signals from bee metabolites provide an important tool to verify honey entomological origin. Here, we present a method for honey screening that does not require any detailed analysis of the NMR spectrum for the detection and quantification of such markers. Our approach is based on the measurement of two spectral parameters, named entomological factor (EF) and aromatic factor (AF), calculated by integration of well-defined regions of the NMR spectrum. The values of EF and AF can reveal direct or indirect dilution of honey with sugar syrups. This method was tested on honeys of different floral origins and could identify all adulterated samples previously recognized by official techniques. Notably, several samples found compliant by official methods were proven non-genuine by the proposed approach.

A non-targeted metabolomic strategy for characterization of the botanical origin of honey samples using headspace gas chromatography-ion mobility spectrometry

In this work, characterization of the botanical origin of honey was carried out using headspace gas chromatography coupled to ion mobility spectrometry (HS-GC-IMS). The proposed methodology was applied for the analysis of 89 samples from ten different botanical origins. A total of 15 volatile compounds could be identified, namely, 3-methyl-1-butanol, heptanal, valeraldehyde, octanal, trans-2-hexenal, nonanal, hexanal, benzaldehyde, 2-heptanone, 2-butanone, 2-hexanone, 6-methyl-5-hepten-2-one, 2-pentanone, ethyl acetate and linalool. The analytical method was characterized in terms of limits of detection and quantification, and precision, in order to quantify the identified compounds. Compounds were quantified using the sum of the protonated monomer and proton-bound dimer and logarithmic regression (R² > 0.98), although the establishment of a concentration threshold that would allow creation of classification rules was not possible since there was variability within the group. Consequently, the establishment of chemometric models was necessary. A non-targeted strategy using 275 features is proposed. Orthogonal partial least squares-discriminant analysis (OPLS-DA) allowed the differentiation of five botanical origins: thousand flowers, rosemary, albaida, orange blossom, and "others" (rest of the investigated botanical origins, since a limited number of samples was available). A success validation rate of 100% allowed the classification of 14 honeys with unknown botanical origin.

NMR-Based Approaches in the Study of Foods

In this review, the three different NMR-based approaches usually used to study foodstuffs are described, reporting specific examples. The first approach starts with the food of interest that can be investigated using different complementary NMR methodologies to obtain a comprehensive picture of food composition and structure; another approach starts with the specific problem related to a given food (frauds, safety, traceability, geographical and botanical origin, farming methods, food processing, maturation and ageing, etc.) that can be addressed by choosing the most suitable NMR methodology; finally, it is possible to start from a single NMR methodology, developing a broad range of applications to tackle common food-related challenges and different aspects related to foods.

Honey compositional convergence and the parallel domestication of social bees

Honey collection evolved from simple honey hunting to the parallel and independent domestication of different species of bees in various parts of the world. In this study, we investigate the extent to which the composition of Apis and stingless bee honeys has been a driver in the selection of different bee species for domestication in Mesoamerica (Mexico) and Asia (Thailand) using a sampling design that combines peak honey profiling by H1 NMR spectroscopy with the collection of honeys from domesticated and undomesticated bee species. Our results show that, independently of the region of the world considered, domesticated stingless bees produce honey whose compositional profiles differ from those of the non-domesticated species and exhibit more similarities towards honeys produced by the domesticated Apis species. Our results provide evidence for the first time that the search for natural sweeteners in the environment by our ancestors led to the parallel and independent domestication of social bees producing honeys with similar compositional profiles.

NMR Metabolite Profiling in the Quality and Authentication Assessment of Greek Honey—Exploitation of STOCSY for Markers Identification

Honey is a natural, healthy commodity and is probably among the most complex foods produced by nature. It is the oldest recorded and certainly the only natural sweetener that can be used by humans without any further processing. Nowadays, the increase in honey’s value, along with its growing list of healthy attributes, has made the present raw material a prime target for adulteration. In the current study, NMR-based metabolite profiling in combination with chemometrics was applied in the quality control of Greek honeys from northeastern Aegean islands. Moreover, statistical total correlation spectroscopy (STOCSY) was employed for the first time as a dereplication and structural elucidation tool in the honey biomarker identification process. A total of 10 compounds were successfully identified in honey total extracts via 1H NMR spectroscopy. Compounds such as 5-(hydroxymethyl)furfural, methyl syringate, a mono-substituted glycerol derivative and 3-hydroxy-4-phenyl-2-butanone, among others, were identified as potential biomarkers related to the botanical and geographical origin of the samples. High-Resolution Mass Spectrometry (HRMS) was used as an additional verification tool on the identified compounds.

NMR Tracing of Food Geographical Origin: The Impact of Seasonality, Cultivar and Production Year on Data Analysis

The traceability of typical foodstuffs is necessary to protect high quality of traditional products. It is well-known that several factors could influence metabolites content in certified foods, but soil composition, altitude, latitude and coded production protocols constitute the territorial conditions responsible for the peculiar organoleptic and nutritional properties of labelled foods. Instead, regardless of origin, seasonality, cultivar, collection year can affect all agricultural products, so it is appropriate to include them in data analysis in order to obtain a correct interpretation of the differences linked to growing areas alone. Therefore, it is useful to use a flexible all-round technique, and NMR spectroscopy coupled with multivariate statistical analysis is considered a powerful means of assessing food authenticity. The purpose of this review is to investigate the relevance of year, cultivar, and seasonal period in the determination of food geographical origin using NMR spectroscopy. The strategy for testing these three factors may differ from author to author, but a preliminary study of cultivar or collection year effects on NMR spectra is the most popular method before starting the geographical characterization of samples. In summary, based on the available literature, the most significant influence is due to cultivar, followed by harvesting year, however seasonality is not considered a source of variability in data analysis.

Floral origin modulates the content of a lipid marker in Apis mellifera honey

The compound DAGE (DiAcyl Glyceryl Ether, 1-stearyl-2,3-dioleoyl glycerol), present in Apis mellifera honey, is a lipidic entomological marker secreted by the salivary glands of worker bees. Its content was determined by NMR, analyzing the organic extracts of a number of Italian honeys of different floral typology. We have found that the DAGE content is related to the botanical origin of honey. This dependence on floral typology was further confirmed by a linear correlation (R² > 0.83) observed between the content of DAGE and the enzymatic activity of invertase and diastase in honey. Also these enzymes originate from bee salivary secretions and their concentrations in honey are known to depend on the floral source. DAGE content appears to be a sensitive parameter to some forms of honey manipulations, as indicated by the results of artificial bee-feeding experiments. This suggests its possible use as indicator of honey authenticity.

ICP-MS-based ionomics method for discriminating the geographical origin of honey of Apis cerana Fabricius

The identification of geographical origin is an important factor in evaluating the authenticity of honey. However, at present, there are few studies concerning the honey of Apis cerana Fabricius (A. cerana, Asiatic honeybee). To identify geographical origin, we used two common methods (multi-physicochemical parameters and phenolic chromatographic fingerprints) but achieved only poor identification. To compensate for this shortcoming, we established an ICP-MS-based ionomics method using 18 elements in 27 A. cerana honey samples from three different areas in Shaanxi Province, China. Multivariate analysis showed that significant differences in contents can be used to discriminate the geographical origin of A. cerana honey. The method was further validated using an independent test set of 11 samples with 90.91% accuracy, demonstrating its potential for the identification and prediction of the geographical origin of honey.

Determination of the Geographical Origin of Maltese Honey Using 1H NMR Fingerprinting

The price of honey, as a highly consumed natural product, depends on its botanical source and its production environment, causing honey to be vulnerable to adulteration through mislabeling and inappropriate, fraudulent production. In this study, a fast and simple approach is proposed to tackle this issue through non-target one dimensional zg30 and noesypr1d 1H NMR fingerprint analysis, in combination with multivariate data analysis. Results suggest that composition differences in sugars, amino acids, and carboxylic acid were sufficient to discriminate between the tested honey of Maltese origin and that of non-local origin. Indeed, all chemometric models based on noesypr1d analysis of the whole fraction honey showed better prediction in geographical discrimination. The possibility of discrimination was further investigated through analysis of the honey's phenolic extract composition. The partial least squares models were deemed unsuccessful to discriminate, however, some of the linear discriminant analysis models achieved a prediction accuracy of 100%. Lastly, the best performing models of both the whole fraction and the phenolic extracts were tested on five samples of unknown geographic for market surveillance, which attained a high agreement within the models. Thus, suggesting the use of non-target 1H NMR coupled with the multivariate-data analysis and machine learning as a potential alternative to the current time-consuming analytical methods.

The potentiality of NMR-based metabolomics in food science and food authentication assessment

In the last years, there was an increasing interest on nuclear magnetic resonance (NMR) spectroscopy, whose applications experienced an exponential growth in several research fields, particularly in food science. NMR was initially developed as the elective technique for structure elucidation of single molecules and nowadays is playing a dominant role in complex mixtures investigations. In the era of the "omics" techniques, NMR was rapidly enrolled as one of the most powerful methods to approach metabolomics studies. Its use in analytical routines, characterized by rapid and reproducible measurements, would provide the identification of a wide range of chemical compounds simultaneously, disclosing sophisticated frauds or addressing the geographical origin, as well as revealing potential markers for other authentication purposes. The great economic value of high-quality or guaranteed foods demands highly detailed characterization to protect both consumers and producers from frauds. The present scenario suggests metabolomics as the privileged approach of modern analytical studies for the next decades. The large potentiality of high-resolution NMR techniques is here presented through specific applications and using different approaches focused on the authentication process of some foods, like tomato paste, saffron, honey, roasted coffee, and balsamic and traditional balsamic vinegar of Modena, with a particular focus on geographical origin characterization, ageing determination, and fraud detection.

Phytochemical profiles and classification of Agave syrups using 1H-NMR and chemometrics

BACKGROUND

Agave syrups are natural sweeteners that are highly desirable for human consumption because they have low glycemic index. In this work, we explored the potential of 1H-NMR-Chemometrics as a useful tool in the identification and differentiation of Agave syrups. Also, we evaluated the phytochemical screening and antioxidant capacity of Agave syrup compared to other natural sweeteners.

RESULTS

The phytochemical screening stands out for Agave syrups containing higher levels of metabolites with antioxidant activity, mainly saponins, glycosides, and terpenoids. Agave syrup antioxidant activity was in a range from 10% to 53%, while the total phenolic content was from 24 to 300 EAG/100 g, and condensed tannins were between 240 and 1,900 mg CE/g. Additionally, 1H-NMR spectroscopy was used to characterize syrup profiles and chemometrics. PCA group analyses allowed the sweeteners' classification by origin and kind of Agave.

CONCLUSION

Thus, we conclude that 1H-NMR and chemometrics can be used for identifying, differentiating, and classifying Agave syrups. Besides, Agave syrups contain significant amounts of antioxidative components and can be considered as an effective source of antioxidant.

Nuclear Magnetic Resonance (NMR) Spectroscopy in Food Science: A Comprehensive Review

Nuclear magnetic resonance (NMR) spectroscopy is a robust method, which can rapidly analyze mixtures at the molecular level without requiring separation and/or purification steps, making it ideal for applications in food science. Despite its increasing popularity among food scientists, NMR is still an underutilized methodology in this area, mainly due to its high cost, relatively low sensitivity, and the lack of NMR expertise by many food scientists. The aim of this review is to help bridge the knowledge gap that may exist when attempting to apply NMR methodologies to the field of food science. We begin by covering the basic principles required to apply NMR to the study of foods and nutrients. A description of the discipline of chemometrics is provided, as the combination of NMR with multivariate statistical analysis is a powerful approach for addressing modern challenges in food science. Furthermore, a comprehensive overview of recent and key applications in the areas of compositional analysis, food authentication, quality control, and human nutrition is provided. In addition to standard NMR techniques, more sophisticated NMR applications are also presented, although limitations, gaps, and potentials are discussed. We hope this review will help scientists gain some of the knowledge required to apply the powerful methodology of NMR to the rich and diverse field of food science.

Classification of Raw Stingless Bee Honeys by Bee Species Origins Using the NMR- and LC-MS-Based Metabolomics Approach

The official standard for quality control of honey is currently based on physicochemical properties. However, this method is time-consuming, cost intensive, and does not lead to information on the originality of honey. This study aims to classify raw stingless bee honeys by bee species origins as a potential classifier using the NMR-LCMS-based metabolomics approach. Raw stingless bee honeys were analysed and classified by bee species origins using proton nuclear magnetic resonance (¹H-NMR) spectroscopy and an ultra-high performance liquid chromatography-quadrupole time of flight mass spectrometry (UHPLC-QTOF MS) in combination with chemometrics tools. The honey samples were able to be classified into three different groups based on the bee species origins of Heterotrigona itama, Geniotrigona thoracica, and Tetrigona apicalis. d-Fructofuranose (H. itama honey), β-d-Glucose, d-Xylose, α-d-Glucose (G. thoracica honey), and l-Lactic acid, Acetic acid, l-Alanine (T. apicalis honey) ident d-Fructofuranose identified via ¹H-NMR data and the diagnostic ions of UHPLC-QTOF MS were characterized as the discriminant metabolites or putative chemical markers. It could be suggested that the quality of honey in terms of originality and purity can be rapidly determined using the classification technique by bee species origins via the ¹H-NMR- and UHPLC-QTOF MS-based metabolomics approach.

Recent developments in the food quality detected by non-invasive nuclear magnetic resonance technology

Nuclear magnetic resonance (NMR) is a rapid, accurate and non-invasive technology and widely used to detect the quality of food, particularly to fruits and vegetables, meat and aquatic products. This review is a survey of recent developments in experimental results for the quality of food on various NMR technologies in processing and storage over the past decade. Following a discussion of the quality discrimination and classification of food, analysis of food compositions and detection of physical, chemical, structural and microbiological properties of food are outlined. Owing to high cost, low detection limit and sensitivity, the professional knowledge involved and the safety issues related to the maintenance of the magnetic field, so far the practical applications are limited to detect small range of food. In order to promote applications for a broader range of foods further research and development efforts are needed to overcome the limitations of NMR in the detection process. The needs and opportunities for future research and developments are outlined.

1H-NMR Profiling and Chemometric Analysis of Selected Honeys from South Africa, Zambia, and Slovakia

Honey is the natural sweet substance produced by honeybee from nectar or honeydew, exhibiting several nutritional and health benefits. It contains a complex mixture of compounds in different proportions, with sugars being the main component. The physicochemical characteristics of ten honeys were evaluated; represented by five, three, and two from South Africa, Slovakia, and Zambia, respectively. The range of values for the pH (3.75–4.38), electrical conductivity (99–659 µS/cm), and moisture content (14.2–17.7%) are within the recommended limits for quality honeys. ¹H-NMR (Nuclear Magnetic Resonance) profiling of the honeys in D₂O was determined, and the data were analysed by chemometrics. This method is fast, reproducible, and sample pre-treatment is not necessary. The ¹H-NMR fingerprints of various chemical shift regions showed similarity or dissimilarity across geographical origins that are useful for identification, detection of adulteration, and quality control. The principal component analysis PCA and partial linear square discriminant analysis PLS-DA of the ¹H-NMR profiles successively categorises the honeys into two chemically related groups. The R² values are higher than the corresponding Q² values for all samples, confirming the reliability of the model. Honeys in the same cluster contain similar metabolites and belong to the same botanic or floral origin.

Real-Time Monitoring of Chemical Changes in Three Kinds of Fermented Milk Products during Fermentation Using Quantitative Difference Nuclear Magnetic Resonance Spectroscopy

Fermented milk products are rising in popularity throughout the world as a result of their health benefits, including improving digestion, normalizing the function of the immune system, and aiding in weight management. This study applies an in situ quantitative nuclear magnetic resonance method to monitor chemical changes in three kinds of fermented milk products, Bulgarian yogurt, Caspian Sea yogurt, and kefir, during fermentation. As a result, the concentration changes in nine organic compounds, α/β-lactose, α/β-galactose, lactic acid, citrate, ethanol, lecithin, and creatine, were monitored in real time. This revealed three distinct metabolic processes in the three fermented milk products. Moreover, pH changes were also determined by variations in the chemical shift of citric acid during the fermentation processes. These results can be applied to estimate microbial metabolism in various flora and help guide the fermentation and storage of various fermented milk products to improve their quality, which may directly influence human health.

Quantitation of Minor Components in Mango Juice with Band-Selective Excitation NMR Spectroscopy

¹H NMR-based metabolic analysis of foods has been widely applied. However, dynamic range problems frequently impede its application because foodstuffs are composed of various organic compounds in a wide range of concentrations. Band-selective excitation ¹H NMR spectroscopy has been found to be a useful tool for observing the minor components in foods. Because quantitative information is important for metabolic analysis of foods and complete metabolome data, quantitation with the band-selective excitation ¹H NMR method was carefully investigated in the present study. As a result, the concentrations of minor components in mango juice of the "Carabao" cultivar were successfully quantitated by band-selective excitation ¹H NMR using standard curves that exhibited good linearity. The band-selective excitation ¹H NMR technique was therefore effective for determining the concentrations of minor components in foods.

Objective Definition of Monofloral and Polyfloral Honeys Based on NMR Metabolomic Profiling

In this paper, a remarkably precise, simple, and objective definition of monofloral and polyfloral honey based on NMR metabolomics is proposed. The spectra of organic extracts of 983 samples of 16 botanical origins were used to derive one-versus-all OPLS-DA classification models. The predictive components of the statistical models reveal not only the principal but also the secondary floral origins present in a sample of honey, a novel feature with respect to the methods present in the literature that are able to confirm the authenticity of monofloral honeys but not to characterize a mixture of honey types. This result descends from the peculiar features of the chloroform spectra that show diagnostic resonances for almost each botanical origin, making these NMR spectra suitable fingerprints. The reliability of the method was tested with an additional 120 samples, and the class assignments were compared with those obtained by traditional analysis. The two approaches are in excellent agreement in identifying the floral species present in honeys and in the botanical classification. Therefore, this NMR method may prove to be a valid solution to the huge limitations of traditional classification, which is very demanding and complex.

1H NMR-based metabolic profiling for evaluating poppy seed rancidity and brewing

Poppy seeds are widely used in household and commercial confectionery. The aim of this study was to demonstrate the application of metabolic profiling for industrial monitoring of the molecular changes which occur during minced poppy seed rancidity and brewing processes performed on raw seeds. Both forms of poppy seeds were obtained from a confectionery company. Proton nuclear magnetic resonance (1H NMR) was applied as the analytical method of choice together with multivariate statistical data analysis. Metabolic fingerprinting was applied as a bioprocess control tool to monitor rancidity with the trajectory of change and brewing progressions. Low molecular weight compounds were found to be statistically significant biomarkers of these bioprocesses. Changes in concentrations of chemical compounds were explained relative to the biochemical processes and external conditions. The obtained results provide valuable and comprehensive information to gain a better understanding of the biology of rancidity and brewing processes, while demonstrating the potential for applying NMR spectroscopy combined with multivariate data analysis tools for quality control in food industries involved in the processing of oilseeds. This precious and versatile information gives a better understanding of the biology of these processes.

Influence of Different Drying Treatments and Extraction Solvents on the Metabolite Profile and Nitric Oxide Inhibitory Activity of Ajwa Dates

This study aimed to examine the variation in the metabolite profiles and nitric oxide (NO) inhibitory activity of Ajwa dates that were subjected to 2 drying treatments and different extraction solvents. (1)H NMR coupled with multivariate data analysis was employed. A Griess assay was used to determine the inhibition of the production of NO in RAW 264.7 cells treated with LPS and interferon-γ. The oven dried (OD) samples demonstrated the absence of asparagine and ascorbic acid as compared to the freeze dried (FD) dates. The principal component analysis showed distinct clusters between the OD and FD dates by the second principal component. In respect of extraction solvents, chloroform extracts can be distinguished by the absence of arginine, glycine and asparagine compared to the methanol and 50% methanol extracts. The chloroform extracts can be clearly distinguished from the methanol and 50% methanol extracts by first principal component. Meanwhile, the loading score plot of partial least squares analysis suggested that beta glucose, alpha glucose, choline, ascorbic acid and glycine were among the metabolites that were contributing to higher biological activity displayed by FD and methanol extracts of Ajwa. The results highlight an alternative method of metabolomics approach for determination of the metabolites that contribute to NO inhibitory activity.

PRACTICAL APPLICATION

The association between metabolite profiles and nitric oxide (NO) inhibitory activity of the various extracts of Ajwa dates was evaluated by utilizing partial least squares (PLS) model. The validated PLS model can be employed to predict the NO inhibitory activity of new samples of date fruits based on their NMR spectra which was important for assessing fruit quality. The information gained might be used as guidance for quality control, nutritional values and as a basis for the preparation of any food supplements for human health that employs date palm fruit as the raw material.

Preliminary Characterization of Monofloral Coffea spp. Honey: Correlation between Potential Biomarkers and Pollen Content

To determine the botanical origin of Coffea honey, a new method using proton nuclear magnetic resonance ((1)H NMR) is proposed. Integration of the aromatic region of the NMR spectrum of Coffea honey diluted in deuterated water allowed us to simultaneously quantify caffeine, theobromine, and trigonelline, as well as other compounds. The amounts of the three markers listed are significantly higher than those previously reported for Citrus spp. honey: caffeine ranged from 15 to 98 mg/kg, theobromine from 25 to 160 mg/kg, and trigonelline from 23 to 86 mg/kg. The concurrent presence of these three substances is proposed as an indicator of the botanical origin of Coffea honey. Excellent correlation was found between these markers and the relative amounts of Coffea pollen measured in the same samples.

Comprehensive NMR analysis of compositional changes of black garlic during thermal processing

Black garlic is a processed food product obtained by subjecting whole raw garlic to thermal processing that causes chemical reactions, such as the Maillard reaction, which change the composition of the garlic. In this paper, we report a nuclear magnetic resonance (NMR)-based comprehensive analysis of raw garlic and black garlic extracts to determine the compositional changes resulting from thermal processing. (1)H NMR spectra with a detailed signal assignment showed that 38 components were altered by thermal processing of raw garlic. For example, the contents of 11 l-amino acids increased during the first step of thermal processing over 5 days and then decreased. Multivariate data analysis revealed changes in the contents of fructose, glucose, acetic acid, formic acid, pyroglutamic acid, cycloalliin, and 5-(hydroxymethyl)furfural (5-HMF). Our results provide comprehensive information on changes in NMR-detectable components during thermal processing of whole garlic.

Physicochemical Properties of Honey from Marche, Central Italy: Classification of Unifloral and Multifloral Honeys by Multivariate Analysis

The purpose of this study was the physicochemical characterization and classification of Italian honey from Marche Region with a chemometric approach. A total of 135 honeys of different botanical origins [acacia ( Robinia pseudoacacia L.), chestnut ( Castanea sativa), coriander ( Coriandrum sativum L.), lime ( Tilia spp.), sunflower ( Helianthus annuus L.), Metcalfa honeydew and multifloral honey] were considered. The average results of electrical conductivity (0.14 – 1.45 mS cm−1), pH (3.89 – 5.42), free acidity (10.9 – 39.0 meqNaOH kg−1), lactones (2.4 – 4.5 meqNaOH kg−1), total acidity (14.5 – 40.9 meqNaOH kg−1), proline (229–665 mg kg−1) and 5-(hydroxy-methyl)-2-furaldehyde (0.6–3.9 mg kg−1) content show wide variability among the analysed honey types, with statistically significant differences between the different honey types. Pattern recognition methods such as principal component analysis and discriminant analysis were performed in order to find a relationship between variables and types of honey and to classify honey on the basis of its physicochemical properties. The variables of electrical conductivity, acidity (free, lactones), pH and proline content exhibited higher discriminant power and provided enough information for the classification and distinction of unifloral honey types, but not for the classification of multifloral honey (100% and 85% of samples correctly classified, respectively).

¹H and ¹³C NMR-based sugar profiling with chemometric analysis and antioxidant activity of herbhoneys and honeys

BACKGROUND

Herbhoneys, relatively new bee products, are expected to have interesting medicinal properties. However, there is still a lack of data concerning their composition and antioxidant properties. ¹H and ¹³C NMR spectroscopy coupled with chemometric analysis (PCA and PLS-DA) and antioxidant assays (DPPH-ESR and ORAC-FL) were used to study 25 samples of Polish herbhoneys and honeys.

RESULTS

Antioxidant activity varied among the samples. The best properties were exhibited by cocoa and instant coffee herbhoneys. The contents of total polyphenols and total carotenoids in the studied samples were found to be 70-1340 mg GAE kg⁻¹ and 0-28.05 mg kg⁻¹ respectively. No significant differences between herbhoney and honey samples were found in their sugar profiles. The PCA of ¹³C NMR spectra of the samples in DMSO-d6 resulted in sample clustering due to sucrose content.

CONCLUSION

Herbhoneys have similar antioxidant properties to traditional honeys, being therefore of equal nutritional value. There was a noticeable influence of the extract concentration on the observed antioxidant effect. For samples with high antioxidant activity, polyphenols were responsible for the observed effect. Sample clustering due to sucrose content in the NMR-PCA study allowed effortless detection of adulteration.

Qualitative and Quantitative Control of Honeys Using NMR Spectroscopy and Chemometrics

400 MHz nuclear magnetic resonance (NMR) spectroscopy and multivariate data analysis techniques were used in the context of food surveillance to measure 328 honey samples with 1H and 13C NMR. Using principal component analysis (PCA), clusters of honeys from the same botanical origin were observed. The chemical shifts of the principal monosaccharides (glucose and fructose) were found to be mostly responsible for this differentiation. Furthermore, soft independent modeling of class analogy (SIMCA) and partial least squares discriminant analysis (PLS-DA) could be used to automatically classify spectra according to their botanical origin with 95–100% accuracy. Direct quantification of 13 compounds (carbohydrates, aldehydes, aliphatic and aromatic acids) was additionally possible using external calibration curves and applying TSP as internal standard. Hence, NMR spectroscopy combined with chemometrics is an efficient tool for simultaneous identification of botanical origin and quantification of selected constituents of honeys.

Characterization of markers of botanical origin and other compounds extracted from unifloral honeys

The possibility of tracing the botanical and geographical origin of products such as honey has become more important because of market globalization. As a consequence, numerous analytical methods have been applied to the determination of honey authenticity. The scope of the present work is to chromatographically purify and characterize 23 compounds from organic extracts of unifloral (chestnut, linden, orange, acacia, eucalyptus, honeydew) and polyfloral honeys. Of these compounds, 17 were identified as specific markers and were used for botanical discrimination in a previous study based on multivariate statistical analysis of proton nuclear magnetic resonance ((1)H NMR) data. Together with the botanical markers, 6 other substances were isolated and characterized using NMR and mass spectrometry. These phytochemicals belong to several classes, that is, terpenes, organic acids, flavonoids, and others. For the first time, a diacylglyceryl ether and 5 other compounds present in different types of honey were identified and characterized.

Traceability of Italian garlic (Allium sativum L.) by means of HRMAS-NMR spectroscopy and multivariate data analysis

(1)H High Resolution Magic Angle Spinning-Nuclear Magnetic Resonance (HRMAS-NMR) spectroscopy was used to analyse garlic (Allium sativum L.) belonging to red and white varieties and collected in different Italian regions, in order to address the traceability issue. 1D and 2D NMR spectra, performed directly on untreated small pieces of garlic, so without any sample manipulation, allowed the assignment of several compounds: organic acids, sugars, fatty acids, amino acids and the nutritionally important fructo-oligosaccharides and allyl-organosulphur compounds. Application of Partial Least Squares projections to latent structures-Discrimination Analysis provided an excellent model for the discrimination of both the variety and, most important, the place origin, allowing the identification of the metabolites contributing to such classifications. The presence of organosulphurs, allicin and some allyl-organosulphurs found by HRMAS-NMR, was confirmed also by SPME-GC-MS; 11 molecules were identified, containing from one up to three sulphur atoms and with and without allyl moieties.

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.