2-acetylfuran-3-glucopyranoside as a novel marker for the detection of honey adulterated with rice syrup

Exploring the role of NIR spectroscopy in quantifying and verifying honey authenticity: A review

Honey, recognized for its diverse flavors and nutritional benefits, confronts challenges in maintaining authenticity and quality due to factors like adulteration and mislabelling. This review undertakes a comprehensive exploration of the utility of Near-Infrared (NIR) spectroscopy as a non-destructive analytical method for concurrently evaluating both honey quantity and authenticity. The primary purpose of this investigation is to delve into the various applications of NIR spectroscopy in honey analysis, with a specific focus on its capability to identify and quantify significant quality parameters such as sugar content, moisture levels, 5-HMF, and proline content. Results from the study underscore the effectiveness of NIR spectroscopy, especially when integrated with advanced chemometrics models. This combination not only facilitates quantification of diverse quality parameters but also enhances the classification of honey based on geographical and botanical origin. The technology emerges as a potent tool for detecting adulteration, addressing critical challenges in preserving the authenticity and quality of honey products. The impact of this critical analysis extends to shedding light on the current state, challenges, and future prospects of applying NIR spectroscopy in the honey industry. This analysis outlines the current challenges and future prospects of NIR spectroscopy in the honey industry. Emphasizing its potential to improve consumer confidence and food safety, the research has broader implications for authenticity and quality assurance in honey. Integrating NIR spectroscopy into industry practices could establish stronger quality control measures, benefiting both producers and consumers globally.

Review of scientific instruments: Evaluation of adulteration in honey using a microwave planar resonator sensor

A microwave microstrip line resonator sensor is developed as an alternative tool for detecting adulteration in honey. A honey-filled tube is placed at the position with the maximum electric field intensity. When the honey is adulterated, its permittivity is changed, leading to a distinct resonance frequency shift and enabling detection. Compared with the existing microwave sensors, this sensor offers the advantages of low cost, compact size, and easy fabrication. Moreover, quantitative analysis of the adulteration could be achieved. Electromagnetic simulation is performed using a co-simulation with CST and MATLAB. The simulation results reveal that the resonance frequency of the resonator decreases as the added water content increases, following a quadratic polynomial relationship. In the experiments, the results demonstrate a successive decrease in the resonance frequency from the empty tube, honey-filled tube to water-filled tube cases. Furthermore, honey samples with varying water contents (up to 70%) are tested, and the resonance frequency decreases with increasing added water content, which agrees well with the simulation results. In addition, there is a quadratic relationship between the two parameters. Principal component analysis is conducted on the transmission coefficients, and the first principal component decreases with increasing water content. With the addition of the second principal component, the cases of different water contents in honey can be well classified.

Rapid and Automated Method for Detecting and Quantifying Adulterations in High-Quality Honey Using Vis-NIRs in Combination with Machine Learning

Honey is one of the most adulterated foods, usually through the addition of sweeteners or low-cost honeys. This study presents a method based on visible near infrared spectroscopy (Vis-NIRs), in combination with machine learning (ML) algorithms, for the correct identification and quantification of adulterants in honey. Honey samples from two botanical origins (orange blossom and sunflower) were evaluated and adulterated with low-cost honey in different percentages (5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, and 50%). The results of the exploratory analysis showed a tendency to group the samples according to botanical origin, as well as the presence of adulteration. A supervised analysis was performed to detect the presence of adulterations. The best performance with 100% accuracy was achieved by support vector machines (SVM) and random forests (RF). A regression study was also carried out to quantify the percentage of adulteration. The best result was obtained by support vector regression (SVR) with a coefficient of determination (R²) of 0.991 and a root mean squared error (RMSE) of 1.894. These results demonstrate the potential of combining ML with spectroscopic data as a method for the automated quality control of honey.

FTIR-ATR detection method for emerging C3-plants-derivated adulterants in honey: Beet, dates, and carob syrups

The European Union Publications Office has recently presented a report on the European Union's coordinated action with the Joint Research Centre to determine certain fraudulent practices in the honey sector, in which it has been indicated that 74% of the samples analyzed, imported from China, and 93% of the samples analyzed, imported from Turkey, the two largest honey producers worldwide, presented at least one indicator of exogenous sugar or suspicion of being adulterated. This situation has revealed the critical state of the problem of honey adulteration worldwide and the need to develop analytical techniques for its detection. Even though the adulteration of honey is carried out in a general way with sweetened syrups derived from C4 plants, recent studies have indicated the emerging use of syrups derived from C3 plants for the adulteration of honey. This kind of adulteration makes it impossible to analyze its detection using official analysis techniques. In this work, we have developed a fast, simple, and economical method based on the Fourier transform infrared spectroscopy technique, with attenuated total reflectance, for the qualitative, quantitative, and simultaneous determination of beetroot, date, and carob syrups, derived from of C3 plants; whose available bibliography is very scarce and analytically not very conclusive for its use by the authorities. The proposed method has been based on the establishment of the spectral differences between honey and the mentioned syrups at eight different points in the spectral region between 1200 and 900 cm^-1 of the mid-infrared, characteristic of the vibrational modes of carbohydrates in honey, which allows the pre-discrimination of the presence or absence of the syrups studied, and their subsequent quantification, with precision levels lower than 2.0% of the relative standard deviation and relative errors lower than 2.0% (m/m).

Rapid, reliable and easy-to-perform chemometric-less method for rice syrup adulterated honey detection using FTIR-ATR

The adulteration of honey (Apis mellifera) is a global problem due to its economic, commercial and health implications. The world's leading beekeeping organisation, APIMONDIA, considers that the detection of adulteration in honey is a problem that has not yet been resolved. This evidence of the importance of the intensive development of analytical techniques that allow the unequivocal detection of adulterants in honey, especially those whose use as honey adulterants has recently emerged. This work aims to develop a fast, easy-to-perform, low-cost analytical method to qualitatively and quantitatively determine rice syrup using the Fourier transform infrared spectroscopy (FTIR) technique with attenuated total reflectance (ATR) mode without complex mathematical procedures and sophisticated sample preparation. This study involved the analysis of 256 intentionally rice-syrup-adulterated honey samples and 92 pure honey samples of bee multifloral honey from Spain. The method, based strictly on the determination of the absorbance directly from the samples, at 1013 cm^-1 The methodology used no need for previous treatments or preparations and demonstrated the scope for the unequivocal detection of rice syrup in adulterated honey containing equal to or higher than 3% (m/m) or more of this adulterant. Using the Exponential Plus Linear model (r = 0.998) shows high accuracy and precision, in terms of relative error (0.32%, m/m) and coefficient of variation (1.4%). The results of this study have led to the establishment of a maximum absorbance threshold of 0.670 for honey without rice syrup.

A Novel, Rapid Screening Technique for Sugar Syrup Adulteration in Honey Using Fluorescence Spectroscopy

The adulteration of honey with different sugar syrups is common and difficult to detect. To ensure fair trade and protect the interests of apiarists, a rapid, simple and cost-effective detection method for adulterants in honey is needed. In this work, fluorescence emission spectra were obtained for honey and sugar syrups between 385 and 800 nm with excitation at 370 nm. We found substantial differences in the emission spectra between five types of honey and five sugar syrups and also found differences in their frequency doubled peak (FDP) intensity at 740 nm. The intensity of the FDP significantly declined (p < 0.01) when spiking honey with ≥10% sugar syrup. To validate this method, we tested 20 adulterant-positive honey samples and successfully identified 15 that were above the limit of detection. We propose that fluorescence spectroscopy could be broadly adopted as a cost-effective, rapid screening tool for sugar syrup adulteration of honey through characterization of emission spectra and the intensity of the FDP.

Identification and quantification of adulterated honey by Raman spectroscopy combined with convolutional neural network and chemometrics

In this study, Raman spectroscopy combined with convolutional neural network (CNN) and chemometrics was used to achieve the identification and quantification of honey samples adulterated with high fructose corn syrup, rice syrup, maltose syrup and blended syrup, respectively. The shallow CNNs utilized to analyze honey mixed with single-variety syrup classified samples into four categories by the adulteration concentration with more than 97% accuracy, and the general CNN model for simultaneously detecting honey adulterated with any type of syrup obtained an accuracy of 94.79%. The established CNNs had the best performance compared with several chemometric classification algorithms. In addition, partial least square regression (PLS) successfully predicted the purity of honey mixed with single syrup, while coefficients of determination and root mean square errors of prediction were greater than 0.98 and less than 3.50, respectively. Therefore, the proposed methods based on Raman spectra have important practical significance for food safety and quality control of honey products.

Rapid and accurate discrimination between pure and adulterated commercial Indian Honey brands using FTIR spectroscopy and principal component analysis

Background:

Four leading commercial Indian honey brands were investigated using FTIR spectroscopy and principal component analysis for rapid and accurate differentiation of pure, mildly adulterated, and highly adulterated honey brand samples.

Methods:

This study is the first to investigate commercial Indian honey brands using FTIR and PCA.

Results:

Hence such methods can investigate adulterations in bulk commercial honey brand samples where sophisticated instrumentations and facilities are not available.

Conclusion:

Thus, the potential of FTIR and PCA can be further used for detecting the presence of adulterations in bulk honey samples without much cost and efforts.

Mass spectrometry in food authentication and origin traceability

Food authentication and origin traceability are popular research topics, especially as concerns about food quality continue to increase. Mass spectrometry (MS) plays an indispensable role in food authentication and origin traceability. In this review, the applications of MS in food authentication and origin traceability by analyzing the main components and chemical fingerprints or profiles are summarized. In addition, the characteristic markers for food authentication are also reviewed, and the advantages and disadvantages of MS-based techniques for food authentication, as well as the current trends and challenges, are discussed. The fingerprinting and profiling methods, in combination with multivariate statistical analysis, are more suitable for the authentication of high-value foods, while characteristic marker-based methods are more suitable for adulteration detection. Several new techniques have been introduced to the field, such as proton transfer reaction mass spectrometry, ambient ionization mass spectrometry (AIMS), and ion mobility mass spectrometry, for the determination of food adulteration due to their fast and convenient analysis. As an important trend, the miniaturization of MS offers advantages, such as small and portable instrumentation and fast and nondestructive analysis. Moreover, many applications in food authentication are using AIMS, which can help food authentication in food inspection/field analysis. This review provides a reference and guide for food authentication and traceability based on MS.

Identification of Pigmented Substances in Black Honey from Leucosceptrum canum: Novel Quinonoids Contribute to Honey Color

Leucosceptrum canum (Lamiaceae) honey (LCH) is a rare and high-value honey with an unusual dark brown color. Its pigments may be related to the purported health benefits of the honey and could serve as indicators of authentic LCH. Here, we purified the pigmented substances contributing to LCH's color and identified them using high-resolution mass spectrometry and nuclear magnetic resonance spectroscopy. The major pigmented substances were 1-[4-(3-carboxy-propylamino)-3,6-dioxo-cyclohexa-1,4-dienyl]-pyrrolidine-2-carboxylic acid (GPBQ), 1-[4-(3-carboxy-propylamino)-3,6-dioxo-cyclohexa-1,4-dienyl]-pyrrolidine-2-carboxylic acid. (GAPBQ), and 2,5-di-(N-prolyl)-para-benzoquinone (DPBQ). According to UHPLC-DAD data recorded at 370 nm, GPBQ, GAPBQ, and DPBQ contents ranged from 2.58 to 5.13, 2.93 to 4.96, and 4.26 to 9.22 mg/kg, respectively. These amino acid-quinone conjugates, found here for the first time, are pigments that can serve as markers to control the quality of LCH.

Comprehensive investigation and risk study on pyrrolizidine alkaloid contamination in Chinese retail honey

Pyrrolizidine alkaloids (PAs) are common phytotoxins. We performed the first comprehensive investigation on PA contamination in Chinese honeys. LC-MS analysis revealed that 58% of 255 honey samples purchased from 17 regions across Mainland China and Taiwan contained PAs with total content ranging over 0.2-281.1 μg/kg. Monocrotaline (from Crotalaria spp), a PA never found in honey in other regions, together with echimidine (Echium plantagineum) and lycopsamine (from Senecio spp.), were three predominant PAs in PA-contaminated Chinese honeys. Further, PAs present in honeys were found to have geographically distinct pattern, indicating possible control of such contamination in future honey production. Moreover, we proposed a new risk estimation approach, which considered both content and toxic potency of individual PAs in honeys, and found that 12% of the PA-contaminated Chinese honeys tested might pose potential health risk. This study revealed a high prevalence and potential health risk of PA contamination in Chinese honeys.

Characteristic Components and Authenticity Evaluation of Rape, Acacia, and Linden Honey

Honey fraud has an extensive global magnitude and impacts both honey price and beekeeper viability. This study aimed at investigating the characteristic phytochemicals of rape, acacia, and linden honey to verify honey authenticity. We discovered methyl syringate, phaseic acid, and lindenin (4-(2-hydroxypropan-2-yl) cyclohexa-1,3-diene-1-carboxylic acid) as particular or unique phytochemicals of rape, acacia, and linden honey. Methyl syringate and lindenin were the most abundant components in rape and linden honey; moreover, their average contents reached up to 10.44 and 21.25 mg/kg, respectively. The average content of phaseic acid was 0.63 mg/kg in acacia honey. To our knowledge, the presence of phaseic acid in honey is a novel finding. Furthermore, we established the HPLC fingerprints of three monofloral honeys. We offered assessment criteria and combined characteristic components with standard fingerprints to evaluate the authenticity of commercial rape, acacia, and linden honeys. For uncertain commercial honey samples, genuine pure honeys constituted nearly 70%. We differentiate the adulteration of acacia and linden honeys with low-price rape honey. Our results reveal that 10% of commercial honeys were pure syrups. Overall, we seem to propose a novel and reliable solution to assess the authenticity of monofloral honey.

A comprehensive analysis of 13C isotope ratios data of authentic honey types produced in China using the EA-IRMS and LC-IRMS

In the current study, we have comprehensively analyzed different kinds of pure honey which was produced in various areas in China according to δ13C-EA -IRMS (AOAC method 998.12) and δ13C-LC-IRMS (proposed by the Intertek laboratory in Europe) methods. As for the δ13C-EA -IRMS method, the study was confirmed that the C4 sugar of all authentic honey samples was qualified. Further inter-laboratory comparison experiments using the δ13C-LC-IRMS method found that all authentic honey samples had Δδ13C (‰) values within the naturally occurring range of ± 1‰ for Δδ13C (‰) fru-glu. However, about 70% samples had Δδ13C (‰) values outside the range of ± 2.1‰ for Δδ13C (‰) max., indicating that a large proportion of pure honey in China can't pass the δ13C-LC-IRMS test, although these honeys were extracted from unadulterated sources. Based on the present findings, we consider that the δ13C-LC-IRMS method is not appropriate to reliably detect adulterated honeys with C3 sugars in China.

High-Throughput Monitoring of Multiclass Syrup Adulterants in Honey Based on the Oligosaccharide and Polysaccharide Profiles by MALDI Mass Spectrometry

Honey is a natural product that could be easily adulterated with various cheaper sweeteners. In the present study, matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) was applied for the detection of honey adulteration based on oligosaccharide and polysaccharide profiles. MS-based strategy could reveal the presence of polysaccharides with higher degree of polymerization (DP ≥ 13) and abnormal trends of saccharides in adulterated honey samples, which could be used as indicators for the identification of honey adulteration with high-fructose corn syrup and corn syrup. MS/MS-based strategy was proposed to characterize the difference in the composition of oligosaccharide isomers between honey samples and adulterated ones with corn syrup or invert syrup, in which the [M+Cl]^- of disaccharides, trisaccharides, and tetrasaccharides were fragmented to give diagnostic product ion pairs. The method is effective and robust for the high-throughput monitoring of honey adulteration, and provides a new perspective for the identification of other high-carbohydrate foods.

Establishing authenticity of honey via comprehensive Romanian honey analysis

Assessing the authenticity of honey is a serious problem that has gained much interest internationally because honey has frequently been subject to various fraudulent practices, including mislabelling of botanical and geographical origin and mixing with sugar syrups or honey of lower quality. To protect the health of consumers and avoid competition, which could create an unstable market, consumers, beekeepers and regulatory bodies are interested in having reliable analytical methodologies to detect non-compliant honey. This paper gives an overview of the different approaches used to assess the authenticity of honey, specifically by the application of advanced instrumental techniques, including spectrometric, spectroscopic and chromatographic methods coupled with chemometric interpretation of the data. Recent development in honey analysis and application of the honey authentication process in the Romanian context are highlighted, and future trends in the process of detecting and eliminating fraudulent practices in honey production are discussed.

Determination of honey adulteration with beet sugar and corn syrup using infrared spectroscopy and genetic-algorithm-based multivariate calibration

BACKGROUND

Fourier transform infrared spectroscopy (FTIR) equipped with attenuated total reflectance accessory was used to determine honey adulteration. Adulterated honey samples were prepared by adding corn syrup, beet sugar and water as adulterants to the pure honey samples in various amounts. The spectra of adulterated and pure honey samples (n = 209) were recorded between 4000 and 600 cm^-1 wavenumber range.

RESULTS

Genetic-algorithm-based inverse least squares (GILS) and partial least squares (PLS) methods were used to determine honey content and amount of adulterants. Results indicated that the multivariate calibration generated with GILS could produce successful models with standard error of cross-validation in the range 0.97-2.52%, and standard error of prediction between 0.90 and 2.19% (% w/w) for all the components contained in the adulterated samples. Similar results were obtained with PLS, generating slightly larger standard error of cross-validation and standard error of prediction values.

CONCLUSION

The fact that the models were generated with several honey samples coming from various different botanical and geographical origins, quite successful results were obtained for the detection of adulterated honey samples with a simple Fourier transform infrared spectroscopy technique. Having a genetic algorithm for variable selection helped to build somewhat better models with GILS compared with PLS. © 2018 Society of Chemical Industry.

Food fingerprints - A valuable tool to monitor food authenticity and safety

In recent years, food frauds and adulterations have increased significantly. This practice is motivated by fast economical gains and has an enormous impact on public health, representing an important issue in food science. In this context, this review has been designed to be a useful guide of potential biomarkers of food authenticity and safety. In terms of food authenticity, we focused our attention on biomarkers reported to specify different botanical or geographical origins, genetic diversity or production systems, while at the food safety level, molecular evidences of food adulteration or spoilage will be highlighted. This report is the first to combine results from recent studies in a format that allows a ready overview of metabolites (<1200 Da) and potentially molecular routes to monitor food authentication and safety. This review has therefore the potential to unveil important aspects in food adulteration and safety, contributing to improve the current regulatory frameworks.

Rapid Screening of Multiclass Syrup Adulterants in Honey by Ultrahigh-Performance Liquid Chromatography/Quadrupole Time of Flight Mass Spectrometry

Honey adulteration with sugar syrups is a widespread problem. Several types of syrups have been used in honey adulteration, and there is no available method that can simultaneously detect all of these adulterants. In this study, we generated a small-scale database containing the specific chromatographic and mass spectrometry information on sugar syrup markers and developed a simple, rapid, and effective ultrahigh-performance liquid chromatography/quadrupole time-of-flight mass spectrometry (UHPLC/Q-TOF-MS) method for the detection of adulterated honey. Corn syrup, high-fructose corn syrup, inverted syrup, and rice syrup were used as honey adulterants; polysaccharides, difructose anhydrides, and 2-acetylfuran-3-glucopyranoside were used as detection markers. The presence of 10% sugar syrup in honey could be easily detected in <30 min using the developed method. The results revealed that UHPLC/Q-TOF-MS was simple and rapid.

Review of methods for the detection and quantification of adulteration of rice: Basmati as a case study

Rice is a staple and widely grown crop endowed with rich genetic diversity. As it is difficult to differentiate seeds of various rice varieties based on visual observation accurately, the harvested seeds and subsequent processed products are highly prone to adulteration with look-alike and low quality seeds by the dishonest traders. To protect the interests of importing countries and consumers, several methods have been employed over the last few decades for unambiguous discrimination of cultivars, accurate quantification of the adulterants, and for determination of cultivated geographical area. With recent advances in biotechnology, DNA based techniques evolved rapidly and proved successful over conventional non-DNA based methods to purge the problem of adulteration at commercial level. In the current review, we made an attempt to summarize the existing methods of adulteration detection and quantification in a comprehensive manner by providing Basmati as a case study to enable the traders to arrive at a quick resolution in choosing the apt method to eliminate the adulteration practice in the global rice industry.

Adulteration of honey and available methods for detection – a review

Honey adulteration is a topical issue because increasingly sophisticated adulteration methods are constantly being developed and the official (legislative) determination of the quality indicators of honey is unable to detect most methods of honey adulteration. In addition, while the popularity among consumers is constantly growing, the worldwide production of honey is unstable. The aim of this review was to provide a current overview of methods suitable for the detection of individual methods of adulteration.

Recent developments in honey characterization

Advanced analytical techniques in honey characterization.