Honey Adulteration Research Articles

Sugar detection in adulterated honey using hyper-spectral imaging with stacking generalization method

This paper develops a new hybrid, automated, and non-invasive approach by combining hyper-spectral imaging, Savitzky–Golay (SG) Filter, Principal Components Analysis (PCA), Machine Learning (ML) classifiers/regressors, and stacking generalization methods to detect sugar in honey. First, the 32 different sugar concentration levels in honey were predicted using various ML regressors. Second, the six ranges of sugar were classified using various classifiers. Third, the 11 types of honey and 100% sugar were classified using classifiers. The stacking model (STM) obtained R2: 0.999, RMSE: 0.493 ml (v/v), RPD: 40.2, a 10-fold average R2: 0.996 and RMSE: 1.27 ml (v/v) for predicting 32 sugar concentrations. The STM achieved a Matthews Correlation Coefficient (MCC) of 99.7% and a Kappa score of 99.7%, a 10-fold average MCC of 98.9% and a Kappa score of 98.9% for classifying the six sugar ranges and 12 categories of honey types and a sugar.

Development of a zebrafish model for toxicity evaluation of adulterated Apis mellifera honey

Since ancient times, honey has been used for medical purposes and the treatment of various disorders. As a high-quality food product, the honey industry is prone to fraud and adulteration. Moreover, limited experimental studies have investigated the impact of adulterated honey consumption using zebrafish as the animal model. The aims of this study were: (1) to calculate the lethal concentration (LC50) of acid-adulterated Apis mellifera honey on embryos, (2) to investigate the effect of pure and acid-adulterated A. mellifera honey on hatching rate (%) and heart rate of zebrafish (embryos and larvae), (3) to elucidate toxicology of selected adulterated honey based on lethal dose (LD50) using adult zebrafish and (4) to screen the metabolites profile of adulterated honey from blood serum of adult zebrafish. The result indicated the LC50 of 31.10 ± 1.63 (mg/ml) for pure A. mellifera honey, while acetic acid demonstrates the lowest LC50 (4.98 ± 0.06 mg/ml) among acid adulterants with the highest mortality rate at 96 hpf. The treatment of zebrafish embryos with adulterated A. mellifera honey significantly (p ≤ 0.05) increased the hatching rate (%) and decreased the heartbeat rate. Acute, prolong-acute, and sub-acute toxicology tests on adult zebrafish were conducted at a concentration of 7% w/w of acid adulterants. Furthermore, the blood serum metabolite profile of adulterated-honey-treated zebrafish was screened by LC-MS/MS analysis and three endogenous metabolites have been revealed: (1) Xanthotoxol or 8-Hydroxypsoralen, (2) 16-Oxoandrostenediol, and (3) 3,5-Dicaffeoyl-4-succinoylquinic acid. These results prove that employed honey adulterants cause mortality that contributes to higher toxicity. Moreover, this study introduces the zebrafish toxicity test as a new promising standard technique for the potential toxicity assessment of acid-adulterated honey in this study and hazardous food adulterants for future studies.

A Comprehensive Narrative Review on the Hazards of Bee Honey Adulteration and Contamination

Honey bees are renowned for producing a remarkable substance known as bee honey, which stands as a functional food celebrated for its numerous health benefits. This natural wonder possesses a spectrum of advantageous properties, including anti-inflammatory, antioxidant, analgesic, antibacterial, and wound-healing qualities. However, in our modern era of heightened utilization of bee products, a new and pressing global health concern has emerged—the contamination of honey with pesticides, antibiotics, microorganisms, and heavy metals. The consumption of beekeeping products containing pesticide residues has been linked to a range of health issues, including genetic malformations, cellular degradation, allergic reactions, and even potential carcinogenic effects. Troublingly, documented cases exist of botulism in newborns resulting from the ingestion of contaminated honey. Additionally, the use of antibiotics in beekeeping practices has been associated with the concerning emergence of antibiotic resistance. This comprehensive review sheds light on the substantial consequences of honey contamination for human health. It underscores the urgent need for the establishment of a rigorous monitoring system, the validation of minimum acceptable pollutant levels, and, at the very least, the regulation of maximum residue limits for bee products, with a particular emphasis on bee honey.

Can a Local Food Label Nudge Consumer Behavior? Implications of an Eye-tracking Study of Honey Products

AbstractThis study presents an eye-tracking experiment to investigate consumer responses toward local Texas honey. Honey adulteration news was used as a treatment along with product attributes, such as a certified Texas honey seal, price, organic, and product reviews. The eye-tracking technology was applied to examine the effect of attribute-non-attendance to measure the treatment effects more robustly. The results show that honey adulteration information increases consumers’ willingness to pay (WTP) for some quality-related attributes. The results also show that negative product reviews have a much larger reduction in the magnitude of WTP than the increase produced by positive product reviews.

Characterization of Turkish Pine honey and differentiation from floral honeys by NMR spectroscopy and chemometric analysis

Honey is a viscous, supersaturated sugar solution produced by bees through the enzymatic transformation of nectar from flowers, containing a complex mixture of carbohydrates, organic acids, enzymes, and other minor constituents. Although honey has been used for thousands of years for its nutritional and medicinal properties, it has been the subject of increasing attention in recent years due to increasing adulterated honey production. Consequently, assessment of honey quality and authenticity has become essential to ensure consumer confidence of regional honey and to perverse the practice of authentic honey production. In this study, we employed nuclear magnetic resonance (NMR) spectroscopy and chemometric analysis to characterize Turkish Pine honey and compare it to flower honey originating from the Oceania, Aegean, and West Coast of North America regions. Utilizing 1H NMR spectroscopy, the chemical profile of Turkish Pine honey was characterized, and unique peaks were found. Additionally, PLS-DA statistical analysis was employed to further investigate the distinction of Turkish Pine honey among other floral and regional honeys. Upon completion of our statistical analysis, we were able to effectively distinguish Turkish Pine honey from other regional honey types, allowing us to formulate a universal test for authenticity of Turkish Pine Honey.

Flexible Electrochemical Sensing Label for the Detection of Glucose Adulteration in Honey

Flexible Electrochemical Sensing Label for the Detection of Glucose Adulteration in Honey

O papel dos testes qualitativos na detecção de adulterantes em mel de abelha sem ferrão: Uma promissora abordagem para produtores e consumidores de mel

Abstract Among the hive products of stingless bees (SB), honey is distinguished because it has different physicochemical properties than the honey produced by Apis mellifera. Its taste is more acidic and less sweet, and it naturally contains a higher percentage of water. Honey is one of the most frequently adulterated products marketed. Therefore, this work aimed to verify if the qualitative tests performed for A. mellifera honey are also valid for SB honey from Tetragonisca angustula, Melipona quadrifasciata, and Tetragona elongata and if they can detect the most common adulterations. Adulterations of SB honey with corn syrup, inverted sugar, and A. mellifera honey were simulated and tested with Lugol, Fiehe, and Lund reactions. For these three analyses, sample volume reduction was also tested. The Lund test did not work well with honey samples from SB because they have a higher water content, and reliable results could not be obtained. For the other two tests, the sample volume reduction used was efficient. The Fiehe test detected adulteration with corn syrup only. The Lugol test detected corn syrup and inverted sugar adulterations in all dilutions for all three SB species. No adulteration by added water or honey from A. mellifera was detected in any test. Therefore, using the qualitative Lugol’s reaction test to evaluate SB honey quality is reasonably affordable. Since it is a rapid and inexpensive test, it allows the development of production chains for SB honey. Thus, detecting inauthentic honey can be done by combining qualitative tests as the first screening, followed by quantitative tests if necessary.

Otkrivanje prevare u bagremovom medu sa područja Tuzle primenom Pivot profile tehnike

This research aimed to examine the applicability of the Pivot Profile (PP) technique in detecting adulteration in acacia honey from the Tuzla region, Bosnia and Herzegovina (B&H). The PP technique captured the relative meaning of descriptors and gathered free descriptions of differences between a target product and a pivot product (PVT), which served as a standard. Four pairs of samples were evaluated: original acacia honey (PVT) versus honey samples adulterated with 20%, 40%, 60%, and 80% fructose-glucose syrup. The sensory assessment involved 72 participants (25 women and 47 men), all acacia honey producers aged from 20 to 55 years of age. The chi-square test (ch² = 3032.37, p < 0.001) revealed significant statistical differences among values, indicating that the consumer panel effectively distinguished the samples. The chi-square test per cell was used to explore variation within the data matrix, identifying descriptors significantly differing from PVT in citation frequency. A total of 48 sensory attributes were generated (5 for appearance, 14 for odours, 4 for basic tastes, 3 for aftertastes, 16 for flavours, 2 for trigeminal effects, and 4 for texture). Correspondence Analysis (CA) was employed to visually represent sensory changes in honey samples based on adulteration levels, illustrating consumer perception of samples and attributes. CA effectively explained nearly 60% of the variability observed across the initial two dimensions, thus emphasizing the connection between sensory alterations and consumer perception. The results revealed a reduction in aroma and appearance attributes, along with occurrences of sensory defects such as off-flavours, unpleasant trigeminal effects, and altered viscosity properties. PP technique provided detailed information about each sample, assessing similarities and differences compared to PVT in a single session using multivariate techniques, contrasting with traditional trained or expert assessments. The PP technique appears promising for further exploration in vocabulary use and data analysis, not only for other honey types but also for various food products susceptible to adulteration.

Short-Wave Near-Infrared Spectroscopy and Chemometrics to Detect Adulteration of Honey with Sucrose Syrup

Near-infrared spectroscopy (NIRS) coupled with multivariate statistical analysis was assessed as a rapid method of detecting honey adulteration in the Philippines. The sample set contained 288 spectra of authentic and adulterated honey samples obtained from six farms in the provinces of Benguet and La Union. Spectral data were pre-processed using ParLeS software in which partial least squares regression (PLSR) analysis was employed. Multivariate analyses like PLSR, principal component analysis (PCA) and linear discriminant analysis (LDA) were performed to predict the level of adulteration, reducing sugar content, and apparent sucrose content. Calibration models for predicting adulteration level (from none to highly adulterated) gave the best results using PLSR on spectral data without pretreatment (calibration R2 > 0.93, validation R2 > 0.94). Principal components (PCs) of the spectral data were extracted using PCA wherein the NIR absorbance bands for sugar (836-840 nm and 978-980 nm) and water (938-940 nm, 978-980 nm, 984-986 nm and 992-994 nm) in honey were identified. Using LDA, calibration models were able to classify honey based on level of adulteration and apparent sucrose; overall accuracies of 99.5% and 100% were observed, respectively. When validated, however, the LDA models could not detect pure honey (out of 6 and 11 samples, respectively), while 86.7% and 100% of adulterated honey could be detected, respectively. Further sampling is recommended to strengthen LDA models.

Kastamonu Bölgesinden Toplanan Kestane Balının Mineral Madde ve Ağır Metal İçerikleri

Chestnut honey, which is known for its apitherapic properties besides its nutritional attributes, is one of the main groups of monofloral honey types. Kastamonu is the most important province because where constitutes two-thirds of the chestnut forest flora of the Black Sea region. Kastamonu Chestnut Honey, produced in apiaries within the chestnut forests, has been registered as a geographical indication and designation of origin. The nutritional value of honey is related to its nutritional and chemical content. Kastamonu chestnut forests have a different distribution with their scattered structure from the coastline to 1000-1200 meters altitude. Therefore, this study was planned with the prediction that chestnut honey produced in different districts has a different composition. The aim of the study is to contribute to official regulations regarding the product, product standardization, and national branding studies by determining mineral and heavy metal contents based on the region where the chestnut honey is produced. As a result of the study, the main concentrations of the elements in the chestnut honey samples were affected by the geographical location, because the apiaries where honey samples were collected in chestnut forests in Kastamonu districts had different altitudes, climates and soil properties, and different secondary flora. The most abundant elements in the samples were potassium (1410.0-6581.5 ppm) sodium (0-204.4 ppm), calcium (125.3-287.5 ppm), and magnesium (24.73-61.88 ppm). Iron (1.32-9.54 ppm), zinc (1.34-20.84 ppm), and manganese (1.39-18.69 ppm) were also found in moderate and others in trace levels. Because manganese is found at moderate levels in all chestnut honey samples and it is found at higher levels than other honey types, it can be recommended that Mn, as fingerprints to detect imitation and adulteration of chestnut honey. While Cd, a heavy metal, was found in only one sample, Ni was not detected in any sample. Whereas Pb concentration varied between 1.84 ppm and 3.38 ppm for the samples, the contents of Al concentrations were quite high (2.94-13.94 ppm). Because there wasn't a maximum limit for heavy metal contents of honey types in the Turkish Food Codex Contaminants Regulation, no evaluation could have been made regarding the suitability of these heavy metal contents. It is thought that heavy metal contamination limits in honey types should be included in the regulations and especially secondary sources such as metallic containers used for storage during handling processes and harvesting of honey for heavy metal contamination should be reviewed.

Application of UV–vis spectrophotometry and chemometrics to investigate adulteration by glucose syrup in Brazilian polyfloral honey

The quality control of food in an easy, fast, and low-cost way has been increasingly sought by industry, and methods based on spectroscopy have stood out in recent years. Honey is among the most adulterated foods worldwide, and fraud detection is difficult because it is a chemically complex matrix. In this sense, this study aimed to develop a simple, fast, and cheap method based on UV–vis spectrophotometry coupled to chemometrics for discriminating pure Brazilian polyfloral honey from adulterated ones. For that, 139 real samples of polyfloral honey produced in southern Brazil (Santa Catarina state) were analyzed by UV–vis scanning spectrophotometry (λ 200–800 nm), and a set of 42 samples (i.e., 30%) were intentionally adulterated with glucose syrup (10–60%, w/w). Three wavelength windows were shown to be relevant in the UV–vis spectra (e.g., 260–500 nm, 260–360 nm, and 280–300 nm), and these data sets were further analyzed by principal component analysis (PCA). Pure and adulterated honey samples were better discriminated by computing the 280–300 nm spectral window data (PC1 and PC2 = 98% total variance of the data set). To validate the method, 59 samples produced in southeastern Brazil (São Paulo state) were included in the descriptive model, which allowed identifying pure and adulterated honey again (PC1 + PC2 = 97% of the data set’s total variance). Thus, these findings support that UV–vis coupled with PCA proved to be a simple and efficient method to discriminate pure honey from adulterated ones, providing a fast and inexpensive protocol to monitor honey quality.

Detection of barley malt syrup as an adulterant in honey by 1H NMR profile.

Currently, Barley Malt Syrup (BMS) is one of the forms of growing adulteration in honey. However, there have been no reports regarding its identification by NMR. In this aspect, we proposed a 1H NMR profiling method to discriminate between authentic and honey adulterated with BMS. The authenticated honey samples were artificially adulterated with varying percentages of BMS. It was found that a marker peak primarily falling around the 5.40ppm region exhibited discrimination between pure and adulterated samples. Furthermore, NMR data of the samples were analyzed using statistical models. The findings demonstrate that NMR sugar profiles region, when combined with PCA analysis, can effectively detect varying degrees of adulteration. Despite qualitative nature of the outcomes, spiking studies have revealed that approach can reliably identify sugar addition at levels as low as 5-10%. Overall, NMR-based approach proves to be effective in detecting BMS as an adulterant in honey.

Detection of sugar syrup adulteration in unifloral honey using deep learning framework: An effective quality analysis technique

The adulteration of honey is a common practice in the production and processing, industries. Various analytical methods such as chromatography, DNA-based, and NMR technology have been used to detect honey adulteration. However, these methods still face challenges in addressing honey authentication issues due to their sophistication, cost, and feasibility. For instance, these methods are expensive, time-consuming, require trained professionals for their operation, and are inaccessible to most of the population. This paper proposes a deep learning framework based on a two-dimensional convolutional neural network to overcome these challenges. The framework uses high-resolution video sequences (one minute) of each honey sample with varying levels of sugar syrup adulteration. Before using the videos in the model, they undergo pre-processing. The performance of the proposed method is validated using several performance indices, including accuracy (0.94), precision, sensitivity (0.99), specificity (1.00), F1-score (0.98), ROC-AUC (0.98), etc. The experimental results demonstrate the potential application of the proposed model in honey quality evaluation. However, further research is required to improve and expand the application of the model in this field, which could positively impact the global honey market.

Weak-value amplified surface plasmon resonance sensor based on joint detection of optical activity and refractive index

A versatile system combining surface plasmon resonance (SPR) and weak value amplification (WVA) is presented, which can measure the optical activity and refractive index of chiral/achiral molecules, ionic compounds, and their mixture in solution individually or simultaneously. The variations in output light intensity directly exhibit high sensitivity to changes in optical activity and refractive index of the aforementioned substances. Furthermore, by examining the correlation between the intensity variation trend and the optical activity of the chiral molecule, the molecule's absolute configuration can be ascertained. Utilizing this instrument, optical rotation with a resolution of 3.04 × 10−6 rad and refractive index with a resolution of 5.57 × 10−9 RIU were obtained. As an attempt at practical application, this sensor was used to detect the adulteration of glucose and fructose in pure honey. Not only can such compromised honey be distinguished from pure honey using the refractive index or optical rotation, but the difference in optical activity can also be employed to effectively differentiate between adulterated honey samples containing glucose and fructose separately.

Investigation of Foreign Amylase Adulteration in Honey Distributed in Japan by Rapid and Improved Native PAGE Activity Staining Method.

Foreign amylase addition to honey in an effort to disguise diastase activity has become a widespread form of food fraud. However, since there is no report on the investigation in Japan, we investigated foreign amylases in 67 commercial honeys in Japan. First, the α-glucosidase and diastase activities of honeys were measured, which revealed that only α-glucosidase activity was significantly low in several samples. As both enzymes are secreted from honeybee glands, it is unlikely that only one enzyme was inactivated during processing. Therefore, we suspected the presence of foreign amylase. α-Amylase in honey were assigned using protein analysis software based on LC-QTOF-MS. As a result, α-amylases from Aspergillus and Geobacillus were detected in 13 and 6 out of 67 honeys, respectively. To detect foreign amylases easily, we developed a cost-effective method using native PAGE. Conventional native PAGE failed to separate the α-amylase derived from honeybee and Geobacillus. However, when native PAGE was performed using a gel containing 1 % maltodextrin, the α-amylase from honeybee did not migrated in the gel and the α-amylase could be separated from the other two α-amylases. The results from this method were consistent with those of LC-QTOF-MS method, suggesting that the novel native PAGE method can be used to detect foreign amylases.

Quality, composition and health effects of natural honey: a review

One of the most important foods produced and consumed worldwide is natural honey. This substance features nice sensory qualities such as a light hue as well as a familiar scent and flavor. It also contains organic acids, sugars, minerals, enzymes, phenolic and volatile chemicals, methylglyoxal, amino acids, vitamins etcetera which have been linked to potential biological activities. All of these features make this viscous substance extremely desirable by consumers thus raising its market value. Natural honey is however prone to contamination upon improper storage so that its natural quality and authenticity can be jeopardized. In this regard, the purpose of this study is to provide updates to the literature available on the physicochemical, sensory features, content, economic value, medicinal benefits, contamination, originality, and adulteration of natural honey. With this context, we hope to provide data that can help guide future honey study.

Traditional knowledge and actions of the Pisel Nek-mej (Scaptotrigona mexicana) stingless bee honey production in Cuetzálan, Puebla

Objective: During the last few years, the production of honey from stingless bees has become significant, as a result of its therapeutic properties. However, its production and commercialization are limited by the low yield per colony and its high sale price. This study seeks to recover the lore and actions that a group of producers from Cuetzálan, Puebla, Mexico has about the production of honey from the Scaptotrigona mexicana species of stingless bees. The objective was to collect information about the handling, production, and commercialization of tis bee species, as well as the challenges that producers face in the Cuetzálan region. Design/Methodology/Approach: This research was carried out using a qualitative approach. Semi-structured interviews were conducted to gather the information. The participants were chosen using the snowball sampling technique, contacting stingless bee honey producers in Cuetzálan, Puebla, Mexico. Results: The lore about the handling of the stingless bees is passed on from generation to generation. This traditional handling is understood as a cultural symbol. This type of honey is renowned for its medicinal properties; however, its production is scarce, and the resulting product is very expensive. Consequently, the theft and adulteration of honey has become a major problem, creating mistrust among consumers. Study Limitations/Implications: More producers should be interviewed, and additional proof of the handling processes used to identify adulteration should be gathered. This information would be used to develop recommendations that could be applied in other producing regions of the country. Findings/Conclusions: The social and scientific recognition of the properties of stingless bee honey shows the importance of adopting innovations; however, including organizational processes to improve the commercialization channels and to minimize unfair honey production practices is also very important.

Detecting adulteration of honey with sugar syrup using EPR spectroscopy: A feasibility study

The food adulteration is a common practice nowadays. Honey is an important food product that is getting adulterated. The substances most often incorporated into honey are sugar syrups as they are readily available. The added syrups lower the quality of the honey. Since the sugars have the same chemical composition, as the sugars in honey, there may not be many changes in the chemical parameters of pure honey and honey adulterated with sugar syrup. In this work, we are analyzing the feasibility of using Electron Paramagnetic Resonance (EPR) spectra of the samples for detection of honey adulteration with sugar syrup. The EPR spectrums of the samples are obtained by incorporating a paramagnetic nitroxide radical.

Biogenic amines and stable isotopes in the quality and authenticity of honeys from Brazil.

The identification of biogenic amines and some precursor amino acids and the adulteration through stable isotopes was carried out in 114 honey from different geographic regions in Brazil (states of São Paulo (SP) and Santa Catarina (SC)) as support for evaluating quality control and food safety. Serotonin was detected in all samples, while melatonin was quantified in 92.2% of honey from SP and in 94% of SC. l-Dopa, dopamine and histamine appeared at higher levels in honey from SP. Cadaverine, putrescine, spermidine and spermine, varied little according to botanical source. Three honey from the metropolitan region of SP were considered adulterated (C4SUGARS>7%), 92 were authentic samples (C4SUGARS-7 to 7%) and 19 unadulterated (C4SUGARS less than-7%), with isotopic values of δ13CH and δ13CP>7%. The data were important for differentiating quality as a function of biogenic amines and stable isotope technique was important in detecting honey adulteration.

Honey fraud detection based on sugar syrup adulterations by HPLC-UV fingerprinting and chemometrics

In recent years, honey-producing sector has faced the increasing presence of adulterated honeys, implying great economic losses and questioning the quality of this highly appreciated product by the society. Due to the high sugar content of honey, sugar syrups are among its most common adulterants, being also the most difficult to detect even with isotope ratio techniques depending on the origin of the sugar syrup plant source. In this work, a honey authentication method based on HPLC-UV fingerprinting was developed, exhibiting a 100% classification rate of honey samples against a great variety of sugar syrups (agave, corn, fiber, maple, rice, sugar cane and glucose) by partial least squares-discriminant analysis (PLS-DA). In addition, the detection and level quantitation of adulteration using syrups as adulterants (down to 15%) was accomplished by partial least squares (PLS) regression with low prediction errors by both internal and external validation (values below 12.8% and 19.7%, respectively).