Monofloral Honey Samples Research Articles

Rapid Convolutional Algorithm for the Discovery of Blueberry Honey Authenticity Markers via Nontargeted LC-MS Analysis.

Bees produce honey through the collection and transformation of nectar, whose botanical origin impacts the taste, nutritional value, and, therefore, the market price of the resulting honey. This phenomenon has led some to mislabel their honey so that it can be sold at a higher price. Metabolomics has been gaining popularity in food authentication, but rapid data mining algorithms are needed to facilitate the discovery of new authenticity markers. A nontargeted high-resolution liquid chromatography-mass spectrometry (HR/LC-MS) analysis of 262 monofloral honey samples, of which 50 were blueberry honey, was performed. Data mining methods were demonstrated for the discovery of binary single-markers (compound was only detected in blueberry honey), threshold single-markers (compound had the highest concentration in blueberry honey), and interval ratio-markers (the ratio of two compounds was within a unique interval in blueberry honey). A novel convolutional algorithm was developed for the discovery of interval ratio-markers, which trained 14× faster and achieved a 0.2 Matthews correlation coefficient (MCC) units higher classification score than existing open-source implementations. The convolutional algorithm also had classification performance similar to that of a brute-force search but trained 1521× faster. A pipeline for shortlisting candidate authenticity markers from the LC-MS spectra that may be suitable for chemical structure identification was also demonstrated and led to the identification of niacin as a blueberry honey threshold single-marker. This work demonstrates an end-to-end approach to mine the honey metabolome for novel authenticity markers and can readily be applied to other types of food and analytical chemistry instruments.

Identifying Key Markers for Monofloral (Eucalyptus, Rosemary, and Orange Blossom) and Multifloral Honey Differentiation in the Spanish Market by UHPLC-Q-Orbitrap-High-Resolution Mass Spectrometry Fingerprinting and Chemometrics.

Honey differentiation based on the botanical origin is crucial to guarantee product authenticity, especially considering the increasing number of fraud cases. This study assessed the metabolomic differences arising from various botanical origins in honey products sold in Spanish markets, focusing on two goals: (1) discrimination within monofloral samples (eucalyptus, rosemary, and orange blossom honey) and (2) differentiation between multifloral vs. monofloral honey samples. An omics strategy based on ultra-high-performance liquid chromatography coupled with quadrupole-Orbitrap-high-resolution mass spectrometry (UHPLC-Q-Orbitrap-HRMS) was applied for the reliable identification of specific honey markers selected by orthogonal partial least squares discriminant analysis (OPLS-DA) (R2Y = 0.929-0.981 and Q2 = 0.868-0.952), followed by the variable importance in projection (VIP) approach. Key amino acid, alkaloid, and trisaccharide markers were identified to distinguish between honey samples. Some Amadori compounds were highlighted as eucalyptus honey markers, suggesting their potential use for honey aging and botanical origin differentiation. L-phenylalanine and raffinose were markers of rosemary honey. Four markers (e.g., trigonelline, L-isoleucine, and N-(1-deoxy-1-fructosyl)isoleucine) were found in higher levels in multifloral samples, indicating a greater availability of amino acids, potentially increasing the Maillard reaction. This research is the first to address the botanical origin's impact on honey by identifying novel markers not previously described.

Evaluation of the Antioxidant Activity and Phenolic Composition of Different Monofloral and Polyfloral Brazilian Honey Extracts.

This study aimed to evaluate the chemical composition and antioxidant activity of phenolic extracts from monofloral and polyfloral honey samples obtained from different Brazilian regions. The chemical composition (total content of phenolic compounds and flavonoids) of extracts were measured by using colorimetric assays and analyzed by high performance liquid chromatographic (HPLC-DAD). The antioxidant activity was evaluated by chemical and biochemical assays (reducing power assay, 1,1-diphenyl-2-picrylhydrazyl (DPPH⋅) and 2,2-azino-bis(3-ethylbenzothiazoline-6-sulphonic) acid (ABTS⋅+) scavenger assays. It was also investigated the ability of extracts in attenuate lipid peroxidation induced by Fe2+ in phospholipids. The obtained results clearly demonstrated that the botanical origin and geographical region of honey collection influenced the chemical composition and antioxidant activity of extracts. Furthermore, the samples were constituted by phenolic acids and flavonoids, which p-coumaric acid was predominant among the compounds identified. All samples were able to scavenge free radicals and inhibit lipid peroxidation, and good correlations were obtained between the flavonoid content and honey color. In conclusion, the obtained extracts were constituted by antioxidant compounds, which reinforce the usage of honey in human diets, and demonstrated that the region of honey collection strong influenced in the chemical composition and, consequently, its biological effect.

The Total Phenolic Content and Antioxidant Activity of Nine Monofloral Honey Types

Honey is well known for its antioxidant and antimicrobial properties, which significantly contribute to its high demand among consumers. While there is plenty of information available about the antioxidant potential of honey, there is still a lack of research specifically focused on monofloral honeys, as most studies have been based on market samples. To address this issue, in the present study we analyzed the total phenolic content and antioxidant activity of nine monofloral honey types produced in Greece: fir, chestnut, citrus, erica, cotton, Jerusalem thorn, pine, oak and thyme, in comparison with manuka honey. The samples were collected from beekeepers applying the appropriate beekeeping practices. In total, ninety-six representative monofloral honey samples meeting the microscopic, physicochemical, and sensory characteristics were analyzed. Oak honey stood out as the darkest type (L* = 33.67) with the highest total phenolic content (203.75 mg GAE/100 g) and antioxidant activity (106.2 mg AAE/100 g). Chestnut honey closely followed, having also the highest electrical conductivity (1.679 mS/cm). Although manuka honey had a high total phenolic content, its total antioxidant activity was found to be medium-low compared to fir, pine, and erica honeys. Citrus honey, being the lightest in color (L* = 37.2), exhibited the lowest total antioxidant activity (6.36 mg AAE/100 g). Statistical analysis revealed significant positive correlation between total antioxidant activity and electrical conductivity (ra-e = 0.587, pa-e = 0.000), and negative correlation between total antioxidant activity and L* parameter (ra-L = −0.424, pa-L = 0.000). Similar correlations were also observed regarding total phenolic content (rp-e = 0.457, pp-e = 0.000, rp-L = −0.455, pp-L = 0.000). In conclusion, oak and chestnut honeys seem to have a high antioxidant potential, that should be further explored, to highlight their value and help promote them worldwide.

Biomarker Aroma Compounds of Monofloral Honey From Kazakhstan by Gas Chromatography–Mass Spectrometry (GC–MS) and Chemometric Analysis*

The aroma compounds of honey provide useful information to determine the geographical origin. This work focuses on the study of aroma compounds of 16 honey samples using headspace (HS)-solid-phase microextraction (SPME) gas chromatography–mass spectrometry (GC-MS) to reaffirm the geographical features of 4 monofloral honey. 7 sunflower, 3 buckwheat, 2 agrimonia, and 4 tamarix monofloral honey samples were obtained from four regions of Kazakhstan. Moreover, the GC-MS data were applied to chemometric analysis for the common aroma compounds to discriminate the monofloral honeys. In total, 76 aroma compounds were detected and 72 were identified. α-Pinene, benzaldehyde, octanal, hotrienol, limonene, cosmene, nonanol, linalool oxide, dehydro-p-cymene, β-linalool, 2-nonen-1-ol, carvacrol, lilac aldehyde A, β-citral, 2-decen-1-al, and β-damascenone were identified as common aroma compounds for all honey types. According to principal component analysis (PCA), the aroma compounds of sunflower, buckwheat, agrimonia, and tamarix honey were distinguished. Dehydro-p-cymene, β-linalool, 2-nonen-1-ol, and linalool oxide were determined as dominant compounds for agrimonia honey, while nonanol, benzaldehyde, octanol, dehydro-p-cymene and β-linalool for buckwheat, β-citral, lilac aldehyde A, 2-decen-1-al, D-limonene, β-damascenone, linalool oxide for tamarix honey, and hotrienol, cosmene, α-pinene, and carvacrol for the sunflower product. PCA revealed that the dominant compounds for each honey could be used as biomarker compounds to detect the origin of the honey and possible adulteration, such as blending and inverted sugar addition.

Assessment of the botanical origin of Saudi Arabian honey samples to identify pollen with chromatographic tools and packing and storage.

The increasing demand for honey purification and authentication necessitates the global utilization of advanced processing tools. Common honey processing techniques, such as chromatography, are commonly used to assess the quality and quantity of valuable honey. In this study, 15 honey samples were authenticated using HPLC and GC-MS chromatographic methods to analyze their pollen spectrum. Various monofloral honey samples were collected, including Acacia, Hypoestes, Lavandula, Tamarix, Trifolium, and Ziziphus species, based on accurate identification by apiarists in 2023 from the Kingdom of Saudi Arabia. Honey analysis revealed the extraction of pollen from 20 different honeybee floral species. Pollen identified from honey samples using advanced chromatographic tools revealed dominant vegetation resources: Ziziphus species (23%), Acacia species (25%), Tamarix species (34%), Lavandula species (26%), Hypoestes species (34%), and Trifolium species (31%). This study uses HPLC to extract phenolic compounds, revealing dominant protocatechuic acid (4.71 mg g-1), and GC-MS to analyze organic compounds in honey pollen. Specifically, 2-dodecanone was detected with a retention time of 7.34 min. The utilization of chromatographic tools in assessing honey samples for pollen identification provides a reliable and efficient method for determining their botanical origins, thereby contributing to the quality control and authentication of honey products.

Physico-chemical properties of multifloral honey Apis dorsata and monofloral honey of bees Apis mellifera

Physicochemical properties of honey as one of the information about the quality of honey. The type of bee, geographic location, and type of vegetation the source of the honey bee feed influence the physico-chemical properties of honey. This study aims to determine the physico-chemical properties of multifloral honey of Apis dorsata bees and monofloral honey of Apis mellifera bees. The honey samples for this study consisted of 4 multifloral honey samples and 4 monofloral honey samples. Physicochemical parameters of honey include water content, color, pH, acidity, reducing sugars, and hydroxymethylfurfural (HMF). Data were analyzed descriptively and quantitatively. The results of the analysis showed that most of the research honey had a water content above the SNI 8664-2018 standard. Honey that has high levels is easy to ferment and to overcome this by lowering the water content of honey through a dehumidifier. Monofloral honey has an intensity value of 47 to 143 mm Pfund, while multifloral honey has 74 to 100 mm Pfund. The pH value of honey ranges from 3.5 to 4.5. The level of acidity, reducing sugar content, and HMF content of all honey samples in the study complied with SNI-8664. There are differences in the physical and chemical characteristics of multifloral honey and monofloral honey.

Improving honey identification: Stable isotope ratios variability of mono and polyfloral honeys from the citrus growing area of Salto/Concordia and from Uruguayan coastal areas

Concordia in Argentina and Salto in Uruguay are two neighbouring regions famous for the production of a precious citrus honey, whose valorisation passes through the ability to guarantee its geographical origin. In this study the influence of the different botanical origins (monofloral and polyfloral) within the same region of origin on the different stable isotope ratios was evaluated. Moreover, the effectiveness of the stable isotope ratio parameters δ13Choney, δ13Cprotein, δ15Nprotein, δ34Sprotein, δ2Hprotein and δ18Oprotein to discriminate between honeys produced in the internal border regions between Argentina and Uruguay (namely, Concordia and Salto) and honeys sampled in the two different Uruguayan coastal regions (Canelones and Maldonado) was tested on 82 monofloral and polyfloral honey samples. The results show that the different stable isotope ratios, except that of nitrogen, are not significantly influenced by the botanical origin of the samples. The sulphur isotopic ratio of proteins and carbon of honey are the most significant parameters for discriminating the geographical origin of the honeys considered. Applied a Principal Component Analysis, the first two factors overall explain 63.5% of the total variance, while the Discriminant Analysis provided optimal discrimination between the three origins, reaching a minimum of 96.7% correct reclassification.

Antioxidant and anti-glycation activity of eight Moroccan honeys from different botanical origins

Eight monofloral honey samples from different botanical and geographical origins in the central and eastern parts of Morocco were examined for their phenolic composition, capacity to scavenge free radicals, and ability to inhibit advanced glycation end–products. According to the melissopalynological analysis, the examined honey samples were considered to be natural honeys, and were classified as monofloral with very frequent pollen grains characteristic of each types of the selected Moroccan honey samples: Zantaz (Bupleurum sp.), fennel, thistle, eucalyptus, spurge, thyme, jujube, and carob. Our results showed that the average moisture content varied from 16.3 ± 0.1% to 19.9 ± 0.1%, and the mean color intensity ranged from 30.94 ± 7.42 to 166.9 ± 6.43 mm Pfund. The highest total phenolic content recorded was 163.83 ± 1.84 mg of gallic acid equivalent per kg, while the highest flavonoid content was 84.44 ± 1.20 mg of catechin equivalent per kg. Zantaz honey exhibited potent antioxidant capacity, as demonstrated by ABTS, DPPH, β-carotene bleaching, FRAP, and ORAC assays. The most significant results were obtained for the ORAC test, with the highest ORAC value of 4.65 mM Trolox equivalent per gram was recorded for Zantaz honey extract. HPLC–DAD analysis revealed different polyphenolic profiles, which can be attributed to differences in floral origin. Furthermore, our study revealed that the extracts of thistle honey, fennel honey, and Zantaz honey were the most effective glycation inhibitors, with the highest inhibition percentage of 96% obtained for the thistle honey extract.

Efficiency of Microwave and Ultrasound-Assisted Extraction as a Green Tool for Polyphenolic Isolation from Monofloral Honeys

Monofloral honey is obtained from the nectar of single-source plants and has a higher market value due to its polyphenol content associated with its biological properties, especially its antioxidant capacity. In this work, advanced extraction techniques using microwave- (MAE) and ultrasound-assisted (UAE) extraction of phenolic compounds in monofloral honey were optimized and compared. Optimal parameters for MAE were an irradiation time of 15 min, a temperature of 60 °C, and a microwave power of 300 W, and for UAE, a sonication time of 10 min, a temperature of 35 °C, and an ultrasound amplitude of 60%. The extraction solvent used was 70% ethanol. In the extracts of different monofloral honey samples (mint, fennel, raspberry, lavender, sage, buckwheat, maroon, heaven) obtained at optimal MAE and UAE conditions, polyphenolic compounds were determined using UPLC-ESI/MS2 analysis and antioxidant capacity using ORAC, ABTS, and DPPH assays. The results showed that UAE was the more efficient technique for the extraction of total flavanones, flavones, hydroxycinnamic acids, and total phenols, and MAE for total flavonols and hydroxybenzoic acids. The antioxidant ORAC and DPPH capacity was higher for the extracts obtained with MAE, while the ABTS capacity was higher for those obtained with UAE.

Antimicrobial and Antibiofilm Properties of Latvian Honey against Causative Agents of Wound Infections.

Honey is widely used in traditional medicine and modern wound healing biomaterial research as a broad-spectrum antimicrobial, anti-inflammatory and antioxidant agent. The study's objectives were to evaluate the antibacterial activity and polyphenolic profiles of 40 monofloral honey samples collected from beekeepers in the territory of Latvia. The antimicrobial and antifungal activity of Latvian honey samples were compared with commercial Manuka honey and the honey analogue sugar solutions-carbohydrate mixture and tested against Escherichia coli, Pseudomonas aeruginosa, Staphylococcus aureus, clinical isolates Extended-Spectrum Beta-Lactamases produced Escherichia coli, Methicillin-resistant Staphylococcus aureus and Candida albicans. Antimicrobial activity was evaluated with the well-diffusion method (80% honey solution w/v) and microdilution method. The honey samples with the highest antimicrobial potential were tested to prevent biofilm development and activity against a preformed biofilm. The principal component analysis of the antimicrobial properties of honey samples vs. polyphenolic profile was performed. Eleven honey samples exhibited antibacterial activity to all investigated bacteria. The antibacterial effect of the samples was most significant on the Gram-positive bacteria compared to the studied Gram-negative bacteria. Latvian honey presents promising potential for use in wound healing biomaterials, opening the possibility of achieving long-term antibacterial effects.

Utilization of Response Surface Methodology in Optimization of Proline Extraction from Castanea sativa Honey.

Proline constitutes approximately 85 % of the amino acid composition of honey. Therefore, the quantitative determination of this amino acid in honey samples is used by many national/international authorities to evaluate the quality of honey types. In this study, it was aimed to achieve maximum proline amino acid extraction from honey samples whose botanical origins were confirmed by melissopalynological analysis. For this reason, based on three different spectrophotometric methods used in the literature for proline analysis, proline extraction was optimized with the Response Surface Method (RSM) and Box-Behnken experimental design. Three independent variables were determined as treatment time (2, 6, and 10 min), treatment temperature (22, 46, and 70 °C), and cooling time (5, 25, and 45 min). As a result of the optimization, it was seen that only significantly effective independent variable on the proline content of honey was the processing temperature. The optimum conditions obtained as a result of the RSM were found to be 2 min for the treatment time, 70 °C for the treatment temperature and 45 min for the cooling time. The composite desirability of the optimum conditions (R2 ) was found to be 1.00. It was determined that the method proposed by International Honey Commission (IHC) is efficient for proline analysis, but it provides more proline extraction by reducing of time from 10 min to 2 min in hold time in boiling water bath only during the extraction step. As a result, the conditions to be used in order to achieve maximum proline extraction with different spectrophotometric methods were determined and optimum values were determined. In addition, since the botanical origin of honey samples significantly affects the proline content of honey, it can be suggested that this study be optimized for different monofloral honey samples as well.

Physicochemical Properties, Antioxidative and Antibacterial Activities of the Persian Medicine-Based Maolasal Honey: An Experimental Study

Background: Maolasal is a honey-induced product which may lead to several beneficial effects from the Persian Medicine (PM) point of view. Heating process as a major step of Maolasal preparation may decrease the honey quality and deteriorate thermal treatment indicators of honey. Methods: This study was conducted on four honey samples (from different floral sources). Maolasal preparation process was done according to one of the most important PM references “Gharabadin Kabir”. Thermal treatment indices, antibacterial and antioxidative activities of products were measured. Results: The 5-Hydroxymethylfurfural (HMF) concentrations of PM-based Maolasal samples of polyfloral, monofloral, and sugar honey were higher than 40 mg/kg; while PM-based Maolasal sample of monofloral honey had acceptable HMF concentration (38.9 mg/kg). Proline content of all samples decreased thorough Maolasal preparation and simple heating processes in all samples and these reductions were greater in monofloral honey and sugar honey Maolasal samples. Maolasal preparation processes decreased diastase activity of all samples. Although Maolasal preparation process led to sucrose content reduction in the three Maolasal samples, sucrose content of Maolasal sample of monofloral honey was higher than its raw sample. Maolasal preparation process increased total phenolic content of all samples. Finally, Maolasal preparation process led to an increase in antibacterial and antioxidant activities of all the samples. Conclusion: Maolasal samples reduced diastasis activity and proline content and increased HMF concentration. Maolasal preparation process may lead to an increase in antibacterial and antioxidative activities of honey which may be helpful for special preventive/therapeutic medicinal objectives.

Metabarcoding of eDNA for tracking the floral and geographical origins of bee honey

Authentic honey products have a high commercial value and are often falsified via adulteration. Metabarcoding of environmental DNA (eDNA) from bacterial, floral, and entomological sources has recently been proposed as a useful tool for identifying and authenticating floral and geographical origins of bee honey. In this study, eDNA metabarcoding was applied to reveal the bacterial, plant, and honey bee DNA signatures of 48 commercial honey products from six different geographical origins. Bacterial DNA composition in commercial honey showed different relative abundance of Paenibacillus and Bacillus in geographically different samples, and high abundance of Methylobacterium in chestnut honey implying potential use of bacterial DNA composition for honey authentication. Using the chloroplast trnL (UAA) as a DNA marker, floral origins of commercial honey were investigated. Based on floral DNA signatures, 12 monofloral honey samples were identified among the 45 samples tested. Targeted amplicon sequencing of cytochrome oxidase I (COI) gene from entomological DNA identified three different Apis mellifera sequence variants, specific to geographic origin of honey, suggesting that COI can be implemented as a DNA marker to trace the origin of honey. Therefore, the current study demonstrated the potential of eDNA based metabarcoding as a robust tool for evaluating commercial bee honey by exploring their floral and geographical origins.

Physicochemical Properties and Antioxidant Activity of Three Types of Monofloral Honey from Indonesia

Background: In addition to minerals, honey contains carbohydrates (glucose and fructose), protein, amino acids, water, enzymes, ash, vitamins, and other substances. Compounds of honey can affect the chemical properties of honey. Knowing the physicochemical properties of honey is very important because physicochemical properties affect the quality of honey. One of the biological activities of honey is an antioxidant. Antioxidants can interfere with oxidative processes, prevent disease, and play an important role in the body's defence system. Objective: to determine and compare physicochemical properties (color, viscosity, ash content, water content, reducing sugar (glucose), total phenolic compound, HMF) and antioxidant activities of monofloral honey samples from Indonesia. Methods: The color of honey are categorized using the Pfund scale. Viscosity measurement is carried out using a Brookfield viscometer. The water content is carried out using a refractometer. Phenolic content and antioxidant activities analysis were carried out by UV-VIS spectrophotometer. Results: The results show that rambutan honey from Malang has the highest physicochemical properties and antioxidant activity, which had an amber color, water content of 21.7% b/b, acidity 20.7 mL NaOH/Kg, viscosity of 33.08 poise, ash content of 0.17% b/b, reducing sugar 69.38%b/b, total phenolics content 533.7 mg GAE/Kg sample and IC50 0.111 µg/mL. Conclusion: The quality of honey varies from region to region. The best honey (according to SNI) is rambutan honey from Malang.

Classification of Monofloral Honeys by Measuring Electrical Impedance Based on Neural Networks

The study of electrical impedance applied to food has become a method with great potential for use in the food industry, which allows the monitoring and control of quality processes in a safe and non-invasive way. Recent research has shown that this technique can be an alternative method to determine the floral origin of the honey bee (Apis mellifera L.) and acquire information on chemical and physical properties such as conductivity, ash content and acidity. In this work, the electrical impedance of six monofloral honey samples from diverse origins and one commercial multi-floral honey were measured using a low-cost impedance meter, obtaining 101 samples (reactance (X) versus resistance (R)), with a frequency sweep between 1 Hz and 25 MHz in all the honeys analyzed. This shows that it is possible, by using a multilayer neural network trained from these data, to classify with 100% accuracy between these honeys and, thereby, quickly and easily determine the floral origin of the honey. This is without the need to use the chemical data or equivalent electrical models.

Physicochemical and antioxidant properties of Coffea arabica honey from Western Oromia, Ethiopia

Coffea arabica is one of the most widely consumed and marketed commodities in the world. The study was designed to characterize C.arabica honey for botanical composition, physicochemical parameters, and antioxidant properties of honey. Twelve honey samples of C. arabica honey were collected during the flowering period of coffee flowers from the Zander hive. The physicochemical properties of honey and the Botanical origin of honey were determined based on Harmonized methods of the International Honey Commission. The antioxidant power of the coffee monofloral honey samples was determined by dissolving 1.5 gm of honey with 25 ml distilled water and mixing it with 25ml methanol and placed at 25◦C for sixty minutes of maceration using a temperature shaker. The pollen count percentage from honey indicated that all honey samples collected from Gera, Gomma, Yayu, and Manna districts were identified as coffee monofloral honey representing 84%, 93%, 75%, and 73 % of pollen count respectively. The mean moisture, ash, HMF, EC, FA, pH, fructose, glucose and sucrose content of Coffea arabica honey were 22.48%, 0.21%, 11.88, 0.49 mS/cm, 13.44 meq/Kg, 3.32, 32.77%, 32.9%, and 3.57% respectively. The total phenol and flavonoid content range from 42.1-82.1 and 21.7-59.7 mg/100 g of GAE/g respectively while the radical scavenging activity ranges from 60.2- 66.3%. The pollen analysis of honey from the area is coffee monofloral honey since its pollen count exceeds more than 45% and the honey quality also meets the Ethiopian and International standards. The antioxidant power of Coffee honey has a considerable amount of polyphenolics which have relevant antiradical activity.

Identification of Seasonal Honey Based on Quantitative Detection of Typical Pollen DNA

Monofloral honey is produced from the nectar of a single predominant botanical species in a particular season and has certain unique properties. Valuable monofloral honey produced in a particular season with unique properties is often targeted for adulteration. Herein, a method for the identification of monofloral honey and determination of its production season was developed. Major nectar plants, including Prunus sp., Robinia pseudoacacia, Castanea sp., and Kalopanax sp., were selected to evaluate the honey produced between April and July in South Korea. Results showed that the highest amount of DNA from each plant was detected in the corresponding flowering season. The pollens tended to accumulate in the honeycomb after the flowering season. The accumulations result in an increase in the diversity of pollen detected in honey. Additionally, DNA quantity of each plant decreased in the samples as the number of plant DNA types increased from May to July. Moreover, the authenticity of the commercial monofloral honey samples showed only cherry blossom honey was found authentic, which exhibited the expected high amount of Prunus sp. DNA. This molecular tool is expected to be useful in verifying the origin of monofloral honey and its production season.

Chemical Composition Analysis and Antioxidant Activity of Coffea robusta Monofloral Honeys from Vietnam.

Monofloral honey samples (Coffea robusta) from Vietnam were determined for their chemical compositions. This is the first report on the chemical composition and antioxidant activity of coffee honey from Vietnam. These samples were characterized by their high contents of total and reducing sugars, total phenolic contents, and total flavonoid contents. The contents of seven phenolic acids (PAs) were quantified by high performance liquid chromatography (HPLC) and analyzed with the assistance of principle component analysis (PCA) to differentiate the honey samples into groups. The hydroxymethylfurfural (HMF) (0.048–2.933 mg/kg) and free acid contents (20.326–31.163 meq/kg) of coffee honey were lower in Nepal, which reflected the freshness of the honey when conducting this survey. The coffee honey had total sugar and reducing sugar contents 831.711 g/kg and 697.903 g/kg, respectively. The high level of total phenolic (0.642 mg GAE/g) and flavonoid (0.0341 mg GE/g) contents of coffee honey contributed to their antioxidant activity of this honey sample. Among the coffee honey tested, the IC50 of DPPH radical-scavenging activities value was 1.134–17.031 mg/mL, while the IC50 of ABTS radical-scavenging activities value was 115.381–213.769 mg/mL. The phenolic acids composition analysis displayed that gallic acid appeared in high concentrations in all studied honey samples, ranging from 0.037–1.015 mg/kg, and ferulic acid content ranged from 0.193 to 0.276 mg/kg. The content of trigonelline and caffeine in coffee honey samples ranged from 0.314–2.399 mg/kg and 8.946–37.977 mg/kg. The data in this article highlight the relevance of coffee honey as a healthy substance.

Antioxidant activities of some monofloral honey types produced across Minas Gerais (Brazil).

This study was carried out with the objective of determining the antioxidant properties and quantification of total phenolics and flavonoids in relation to quercetin and rutin in some of the monofloral honeys produced in Minas Gerais (Brazil). In this study, 15 monofloral honey samples were obtained from different geographic regions of Minas Gerias, Brazil. The honeys were obtained from Cooperative of Beekeepers and Family Farmers of Northern Minas. To determine the antioxidant properties of honey samples, the test methods of total phenolic content, flavonoids (rutin and quercetin) and DPPH were used. As a result of the analysis of phenolic and flavonoid contents, the samples with the best results were A1-Aroeira and A4-Assa peixe. In antioxidant activity, the honey with the best EC50 results was A6-Aroeira. Differences between the antioxidant activities of the honey samples were found significantly (p< 0.01).