Impact of processing steps (filtration, creaming and pasteurization) on the botanical classification of honey using LC-QTOF-MS.

The present study investigated the impact of filtration, creaming and pasteurization on the authentication of the botanical origin of honey using the dilute-and-shoot method in liquid chromatography coupled to mass spectrometry (LC-MS). The analytical method performances were satisfactory (analyte recoveries ranging from 95 % to 103 % and inter-day precision below 12 %). Three types of raw honeys including blueberry, canola and clover were processed under controlled conditions. Filtration, creaming and pasteurization had no impact on honey botanical classification based on the LC-MS fingerprint, and the key molecular fingerprints were retained after processing. However, results revealed that testing the impact of processing is essential when selecting honey authenticity markers because some candidates (e.g. adenosine) are not stable or can be removed during honey processing. The results of the present study also highlighted the suitability of the dilute-and-shoot approach to both develop authentication tools for honey and study the impact of processing methods on specific chemicals in honeys.

Electrical impedance spectroscopy for potassium content analysis and botanical origin identification of honey.

Minerals are reported to dominate the electrical properties of honey and indicate its botanical and geographical origins. In this study, Electrochemical Impedance Spectroscopy (EIS) was used to assess the relation between mineral elements, electrical properties and botanical origin using three honey varieties - Citrus sp., Eucalyptus sp., and Erica sp. These varieties are identified through pollen analysis and market labelling. Flame atomic absorption and emission spectroscopies were used to quantify the concentrations of eight elements (potassium, sodium, calcium, magnesium, manganese, zinc, copper, and iron). Among all the mineral elements, potassium showed a consistent correlation with impedance. The potassium estimation in honey and standard solutions (calibration curve) had similar sensitivities of 153.43 nF/mM and 132.68 nF/mM, respectively. Additionally, the analysis revealed that potassium dominates the mineral composition, with the other species present in minimal quantities. The EIS technique showed high sensitivity to potassium and other ionisable species, making it possible to classify the botanical origin of these three honey types. The EIS technique proved to be both time and cost effective, yielding a classification rate higher than that achieved by analysing mineral composition.

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

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

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

BACKGROUND: Although the main method for authentication of monofloral honey is pollen analysis, other classification approaches have been also applied. However, the majority of the existing classification models so far have utilized a few honey types or a few honey samples of each honey type, which can lead to inaccurate results. Aiming at addressing this, the goal of the present study was to create a classification model by analysing in total 250 honey samples from 15 different monofloral honey types in ten physicochemical parameters and then, multivariate analysis [multivariate analysis of variance (MANOVA), principal component analysis (PCA) and multi-discriminant analysis (MDA)] was applied in an effort to distinguish and classify them. RESULTS: Electrical conductivity and colour were found to have the highest discriminative power, allowing the classification of monofloral honey types, such as oak, knotgrass and chestnut honey, as well as the differentiation between honeydew and nectar honeys. The classification model had a high predictive power, as the 84.4% of the group cases was correctly classified, while for the cases of chestnut, strawberry tree and sunflower honeys the respective prediction was correct by 91.3%, 95% and 100%, allowing further determination of unknown honey samples. CONCLUSION: It seems that the characterization of monofloral honeys based on their physicochemical parameters through the proposed model can be achieved and further applied on other honey types. The results could contribute to the development of methodologies for the determination of honey's botanical origin, based on simple techniques, so that these can be applied for routine analysis. © 2021 Society of Chemical Industry.

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

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

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

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

Bioactive compounds in Apis mellifera monofloral honeys.

Honey is a natural product with a sweet flavor. Honey is made by the honeybee (Apis mellifera L.) from the nectar of flowers or other plant secretions that are collected near the hive. These products are mixed with bee saliva and stored. Several studies have demonstrated that honey exhibits antioxidant, antimicrobial, nematicidal, antifungal, anticancer, and anti-inflammatory activities. These properties are influenced by the plants from which the secretions are harvested, from the naturally occurring compounds present in the nectar. Studies of the properties and applications of honey have distinguished honey from other natural products due to the presence of certain compounds and due its bioactive properties. The focus of this review is to discuss the identified and isolated compounds from monofloral honey produced by A. mellifera, with specific emphasis on antioxidant and antimicrobial properties of honey and its therapeutic health benefits.

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

BACKGROUND: The production of honey, and especially the unifloral varieties, is limited by factors such as weather conditions or the availability of nectar flow and honeydew. This results in a deficit in supply leading to the adulteration of honey. If they are not properly labeled, customers cannot distinguish artificial / synthetic products from real honey. Currently, the basic, commonly used method for determining the varieties of honey (botanical origin) is palynological analysis. However, this procedure is quite difficult owing to the dearth of experienced staff in the field of melissopalynology. RESULTS: A method for identifying and classifying natural honey accurately based on its botanical origin has therefore been proposed. This analysis would rely on the visible light spectra transmitted through a relatively thin layer of the substance of interest, regardless of deviations in thickness. We present algorithms for analyzing the transmittance spectra-parametrization based on polynomial approximation (PMA) and applying a method for spectra selection and reduction (SSR) and a classical classification model (decision tree). A comparison is presented of the classification of four varieties of honey, confirmed by pollen analysis, obtained from the analysis of optically measured transmittance spectra of the samples. The algorithms that are compared contain a decision tree that uses raw data, data reduced by principal component analysis (PCA), and data after calculations based on the proposed algorithms alone (PMA and SSR) and together with the PCA method. CONCLUSION: This novel method produced outstanding results in comparison with the standard PCA method and is helpful in identifying the botanical origin of honey effectively. © 2021 Society of Chemical Industry.

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

BACKGROUND: To reflect and understand the real situation regarding immature honey, the quality parameters of 141 honey samples from different regions of China were evaluated. The possibility of classifying Chinese honey from different geographical origins was also considered. RESULTS: The results revealed that the values of diastase, sucrose, proline and 5-hydroxymethylfurfural (HMF) met the international honey standard, although moisture, total glucose and fructose, and invertase content in most of the honey samples failed to meet the standards. In addition, honey from different geographical locations could be well separated based on the contents of maltose, sucrose, HMF and glucose oxidase. CONCLUSION: The maturity of honey has a great impact on its quality, and the geographical origin of immature honey could be classified according to the physicochemical parameters. © 2021 Society of Chemical Industry.

The Use of UV Spectroscopy and SIMCA for the Authentication of Indonesian Honeys According to Botanical, Entomological and Geographical Origins.

As a functional food, honey is a food product that is exposed to the risk of food fraud. To mitigate this, the establishment of an authentication system for honey is very important in order to protect both producers and consumers from possible economic losses. This research presents a simple analytical method for the authentication and classification of Indonesian honeys according to their botanical, entomological, and geographical origins using ultraviolet (UV) spectroscopy and SIMCA (soft independent modeling of class analogy). The spectral data of a total of 1040 samples, representing six types of Indonesian honey of different botanical, entomological, and geographical origins, were acquired using a benchtop UV-visible spectrometer (190-400 nm). Three different pre-processing algorithms were simultaneously evaluated; namely an 11-point moving average smoothing, mean normalization, and Savitzky-Golay first derivative with 11 points and second-order polynomial fitting (ordo 2), in order to improve the original spectral data. Chemometrics methods, including exploratory analysis of PCA and SIMCA classification method, was used to classify the honey samples. A clear separation of the six different Indonesian honeys, based on botanical, entomological, and geographical origins, was obtained using PCA calculated from pre-processed spectra from 250-400 nm. The SIMCA classification method provided satisfactory results in classifying honey samples according to their botanical, entomological, and geographical origins and achieved 100% accuracy, sensitivity, and specificity. Several wavelengths were identified (266, 270, 280, 290, 300, 335, and 360 nm) as the most sensitive for discriminating between the different Indonesian honey samples.

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

BACKGROUND: The authenticity of honey is of high importance since it affects its commercial value. The discrimination of the origin of honey is of prime importance to reinforce consumer trust. In this study, four chemometric models were developed based on the physicochemical parameters according to European and Greek legislation and one using Raman spectroscopy to discriminate Greek honey samples from three commercial monofloral botanical sources. RESULTS: The results of physicochemical (glucose, fructose, electrical activity) parameters chemometric models showed that the percentage of correct recognition fluctuated from 92.2% to 93.8% with cross-validation 90.6-92.2%, and the placement of test set was 79.0-84.3% successful. The addition of maltose content in the previous discrimination models did not significantly improve the discrimination. The corresponding percentages of the Raman chemometric model were 95.3%, 90.6%, and 84.3%. CONCLUSION: The five chemometric models developed presented similar and very satisfactory results. Given that the recording of Raman spectra is simple, fast, a minimal amount of sample is needed for the analysis, no solvent (environmentally friendly) is used, and no specialized personnel are required, we conclude that the chemometric model based on Raman spectroscopy is an efficient tool to discriminate the botanical origin of fir, pine, and thyme honey varieties. © 2020 Society of Chemical Industry.

Fast Classification of Geographical Origins of Honey Based on Laser-Induced Breakdown Spectroscopy and Multivariate Analysis.

Traceability of honey is highly required by consumers and food administration with the consideration of food safety and quality. In this study, a technique named laser-induced breakdown spectroscopy (LIBS) was used to fast trace geographical origins of acacia honey and multi-floral honey. LIBS emissions from elements of Mg, Ca, Na, and K had significant differences among different geographical origins. The clusters of honey from different geographical origins were visualized with principal component analysis. In addition, support vector machine (SVM) and linear discrimination analysis (LDA) were used to quantitively classify the origins. The results indicated that SVM performed better than LDA, and the discriminant results of multi-floral honey were better than acacia honey. The accuracy and mean average precision for multi-floral honey were 99.7% and 99.7%, respectively. This study provided a fast approach for geographical origin classification, and might be helpful for food traceability.

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

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

Use of energy-dispersive X-ray fluorescence combined with chemometric modelling to classify honey according to botanical variety and geographical origin.

Honey is one of the food commodities most frequently affected by fraud. Although addition of extraneous sugars is the most common type of fraud, analytical methods are also needed to detect origin masking and misdescription of botanical variety. In this work, multivariate analysis of the content of certain macro- and trace elements, determined by energy-dispersive X-ray fluorescence (ED-XRF) without any type of sample treatment, were used to classify honeys according to botanical variety and geographical origin. Principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) were used to create classification models for nine different botanical varieties-orange, robinia, lavender, rosemary, thyme, lime, chestnut, eucalyptus and manuka-and seven different geographical origins-Italy, Romania, Spain, Portugal, France, Hungary and New Zealand. Although characterised by 100% sensitivity, PCA models lacked specificity. The PLS-DA models constructed for specific combinations of botanical variety-country (BV-C) allowed the successful classification of honey samples, which was verified by external validation samples. Graphical abstract.

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

BACKGROUND: Antibacterial activity of honey is not only crucial characteristic in selection of honey for medical usage but also an important honey quality marker. The aim of the study was to characterise the antibacterial potential of 29 honey samples representing the main types of multi-floral blossom and honeydew honeys produced in Switzerland. Antibacterial activity against Staphylococcus aureus and Pseudomonas aeruginosa was expressed as a minimum inhibitory and bactericidal concentrations (MIC and MBC). Furthermore, the content of bee-derived glucose oxidase (GOX) and its enzymatic product, H2 O2 , were also evaluated. RESULTS: All honey samples successfully met basic defined criteria (moisture and hydroxymethylfurfural (HMF)) tested in this study. Honeydew honeys were the most effective honey samples and generated the highest levels of H2 O2 . A strong significant correlation was found between the overall antibacterial activity and the level of H2 O2 among all honey samples. Interestingly, the content of GOX in honey samples did not correlate with their antibacterial activity as well as H2 O2 production capacity. A weak antibacterial activity was determined in five floral honeys, most likely due to increased enzymatic activity of pollen-derived catalase. CONCLUSION: This study showed that antibacterial effect of Swiss honey samples is associated mainly with H2 O2 . © 2019 Society of Chemical Industry.

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

BACKGROUND: The growing need to classify the origin of honey in a simple way is leading to the development of affordable analytical equipment that is in-line and manageable, enabling rapid on-site screening. The aim of this work was therefore to evaluate whether an electronic tongue (made of four metallic electrodes: Ir, Rh, Pt, Au), based on potential multistep pulse voltammetry with electrochemical polishing, is able to differentiate between honey samples from Spain, Honduras, and Mozambique. RESULTS: It was demonstrated, for the first time, that automatic pulse voltammetry, in combination with principal component analysis (PCA) statistical analysis, was able to differentiate honey samples from these three countries. A partial least squares (PLS) analysis predicted the level of certain physicochemical parameters, the best results being for conductivity and moisture with correlation coefficients of 0.948 and 0.879, whereas the weakest correlation was for the sugars. CONCLUSION: The tool proposed in this study could be applied to identify the country origin of the three types of multifloral honey considered here. It also offers promising perspectives for expanding knowledge of the provenance of honey. All of this could be achieved when a comprehensive database with the information generated by this electronic tongue has been created. © 2019 Society of Chemical Industry.

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

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

Differentiation of oak honeydew and chestnut honeys from the same geographical origin using chemometric methods.

Oak honeydew and chestnut honeys often share the same production area in Atlantic landscapes. Consequently these honeys have common physicochemical properties and pollen composition, making their differentiation by routine methods, a difficult task. The increase in the demands of consumers for clear honey labelling, identifying floral make-ups and the substantial health properties of both honey types, make it necessary to improve methods to differentiate the honeys. Statistical multivariate techniques were used to study the differences in the physicochemical composition and pollen spectra between chestnut honey and oak honeydew honey. Palynological analysis, moisture, pH, electrical conductivity, hydroxymethylfurfural, diastase number, colour, phenolic content, minerals and sugars were used for this purpose. The variables that had more weight in the differentiation by principal component analysis were Castanea, Cytisus type, CIELab coordinates (a* and L), RSA, Mg and trehalose; 97.6% of the honey samples were correctly classified by linear discriminant analysis.

An overview of physicochemical characteristics and health-promoting properties of honeydew honey.

Honeydew honey has differentiated chemical and physicochemical characteristics besides potential functional properties such as antimicrobial, anti-inflammatory and antioxidant. In this sense, the interest and consumption of this honey as a functional product by the food industry and consumers have increased. Honeydew honeys usually present dark color, a lower content of monosaccharides and higher values of pH, acidity, electric conductivity, proteins, minerals, phenolic compounds, and oligosaccharides compared to blossom honeys, which contribute to its outstanding biological activities. Consequently, contaminations and adulterations of this honey can occur and compromise the quality, safety and authenticity of honeydew honey. Thus, detailed knowledge of the composition and properties of honeydew honeys is of great importance, especially considering that honeydew honeys are still few studied and therefore underestimated. Therefore, in this review, the physicochemical characteristics, chemical and bioactive composition, functional and health-promoting properties of honeydew honey as well as contamination, adulteration and authenticity of this honey are summarized.

PAHs in different honeys from Serbia.

Maximum limits for PAHs content in honey and bee products are not set. The objective of this study was to conduct a market survey of honey for the presence of PAH16 with the aim of detecting potential contamination and health risks for consumers. A total number of 61 honey samples produced in the territory of Serbia were examined. The content of PAH16 was measured using a gas chromatography-mass spectrometric method. Large values were found in some samples: 140.6 µg/kg for chrysene, 136.3 µg/kg for benzo[ghi]perylene, 120.1 µg/kg for benzo[a]pyrene, 87.2 µg/kg for benz[a]anthracene and 79.6 µg/kg for benzo[k]fluoranthene. It was established that 6.6% honey samples were not safe for human consumption because of high benzo[a]pyrene and PAH4 content, which greatly exceeded the maximum limits for all food categories. Considering that screening of honey obtained from the market does not allow accurate detection of the contamination origin requires further investigations to identify potential contamination sources.