Detection techniques for adulterants in honey: Challenges and recent trends

Discrimination of honey and syrup-based adulteration by mineral element chemometrics profiling

Mineral elements are important constituents in honey, which play vital roles in determining the quality and authenticity. The present work aims to systematically estimate the mineral profile of honeys, syrups, and adulterated honeys by syrup directly with chemometrics. Twelve mineral elements with higher contents were determined by ICP-OES in 67 honeys from 6 botanical origins, 17 syrups from 3 types, and 61 adulterations. Statistical analysis revealed honey was significantly different and higher than pale syrup in mineral profile except for barium. Five mono-floral models were established based on chemometrics analysis using the sPLS-DA method, and their discrimination accuracy were over 93% Although mineral contents in honeys from different botanical and geographical origins were quite different, the multi-floral model's classify accuracy was 87.7% as well as in blind test. The results revealed that mineral element chemometrics profiling can be a stable and robust tool to differentiate adulterated honey from pure honey.

Fraud in Animal Origin Food Products: Advances in Emerging Spectroscopic Detection Methods over the Past Five Years

Animal origin food products, including fish and seafood, meat and poultry, milk and dairy foods, and other related products play significant roles in human nutrition. However, fraud in this food sector frequently occurs, leading to negative economic impacts on consumers and potential risks to public health and the environment. Therefore, the development of analytical techniques that can rapidly detect fraud and verify the authenticity of such products is of paramount importance. Traditionally, a wide variety of targeted approaches, such as chemical, chromatographic, molecular, and protein-based techniques, among others, have been frequently used to identify animal species, production methods, provenance, and processing of food products. Although these conventional methods are accurate and reliable, they are destructive, time-consuming, and can only be employed at the laboratory scale. On the contrary, alternative methods based mainly on spectroscopy have emerged in recent years as invaluable tools to overcome most of the limitations associated with traditional measurements. The number of scientific studies reporting on various authenticity issues investigated by vibrational spectroscopy, nuclear magnetic resonance, and fluorescence spectroscopy has increased substantially over the past few years, indicating the tremendous potential of these techniques in the fight against food fraud. It is the aim of the present manuscript to review the state-of-the-art research advances since 2015 regarding the use of analytical methods applied to detect fraud in food products of animal origin, with particular attention paid to spectroscopic measurements coupled with chemometric analysis. The opportunities and challenges surrounding the use of spectroscopic techniques and possible future directions will also be discussed.

A sensitive and visual molecularly imprinted fluorescent sensor incorporating CaF2 quantum dots and β-cyclodextrins for 5-hydroxymethylfurfural detection

Calcium fluoride (CaF₂) quantum dots have many applications in various fields. But there is no report on fluorescent characteristics of CaF₂ quantum dots (CaF₂ QDs). Here, a synthesis of multiple-color emission CaF₂ QDs by changing the temperature, time and raw ratio is reported, by which the CaF₂ QDs with purple, blue, green, and yellow emission can be obtained, respectively. They were characterized by X-ray diffraction (XRD) and transmission electron microscope (TEM). On this basis, a novel molecular imprinting ratiometric fluorescence sensor (MIR sensor) had been constructed based on the prepared CaF₂ QDs and CdTe QDs, in which the yellow emission CaF₂ QDs was used as a responsive signal material and the red emission CdTe QDs was served as a reference signal material. And the β-CD and methylacrylic acid (MAA) as bifunctional monomers were used for constructing the specific molecularly imprinted polymers (MIPs) in MIR sensor. This MIR sensor was applied for highly selective and excellent sensitive detection of 5-hydroxymethylfurfural (HMF). Under optimum conditions, it exhibited an excellent linear relationship between the fluorescence intensity ratio (I₅₉₉/I₆₂₅) and the concentration of HMF in the range of 0.1-6.0 μg/mL with a detection limit of 0.043 μg/mL. Finally, the established HMF-MIR sensor was successfully utilized to detect HMF in honey with satisfactory results. This work provided a reference for the application of the CaF₂ QDs and the detection of the furfural substances.

Synthesis and characterization of phosphocholine chloride-based three-component deep eutectic solvent: application in dispersive liquid-liquid microextraction for determination of organothiophosphate pesticides

BACKGROUND

A new type of deep eutectic solvent based on three components using phosphate salts has been synthesized, characterized, and applied in the extraction of eight organothiophosphate pesticides from honey samples. In this study, the deep eutectic solvent was prepared from phosphocholine choline chloride as a hydrogen bond acceptor and dichloroacetic acid and decanoic acid as hydrogen bond donors. The method consisted of two steps in which initially the analytes were extracted from the samples into a water-miscible organic solvent. In the second step, the extracted phase was mixed with the prepared deep eutectic solvent and the mixture was used in the following dispersive liquid-liquid microextraction method.

RESULTS

The method was validated under optimal conditions, and it was found that it has low limits of detection (0.05-0.10 ng g^-1 ) and quantification (0.19-0.36 ng g^-1 ), good linearity (r²  ≥ 0.994), broad linearity (0.36-1000 ng g^-1 ), and satisfactory repeatability (relative standard deviation ≤10% for intra- (n = 6) and inter-day (n = 4) precisions at a concentration of 2 ng g^-1 of each analyte).

CONCLUSION

The proposed method was applied in different honey samples, and malathion was found at a concentration of 29 ng g^-1 in one sample. © 2019 Society of Chemical Industry.

Raman Spectroscopy and Chemometric Modeling to Predict Physical-Chemical Honey Properties from Campeche, Mexico

In this work, 10 chemometric models based on Raman spectroscopy were constructed to predict the physicochemical properties of honey produced in the state of Campeche, Mexico. The properties of honey studied were pH, moisture, total soluble solids (TSS), free acidity, lactonic acidity, total acidity, electrical conductivity, Redox potential, hydroxymethylfurfural (HMF), and ash content. These proprieties were obtained according to the methods described by the Association of Official Analytical Chemists, Codex Alimentarius, and the International Honey Commission. For the construction of the chemometric models, 189 honey samples were collected and analyzed in triplicate using Raman spectroscopy to generate the matrix data [X], which were correlated with each of the physicochemical properties [Y]. The predictive capacity of each model was determined by cross validation and external validation, using the statistical parameters: standard error of calibration (SEC), standard error of prediction (SEP), coefficient of determination of cross-validation (R2cal), coefficient of determination for external validation (R2val), and Student's t-test. The statistical results indicated that the chemometric models satisfactorily predict the humidity, TSS, free acidity, lactonic acidity, total acidity, and Redox potential. However, the models for electric conductivity and pH presented an acceptable prediction capacity but not adequate to supply the conventional processes, while the models for predicting ash content and HMF were not satisfactory. The developed models represent a low-cost tool to analyze the quality of honey, and contribute significantly to increasing the honey distribution and subsequently the economy of the region.

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.

NMR carbohydrate profile in tracing acacia honey authenticity

The sugar profile in honey can be used as a fingerprint to confirm the authenticity or reveal the adulteration of the product by sweetener addition. In this work, we have accurately determined the profile of 20 minor saccharides in a set of 46 European acacia honeys using a recently proposed NMR approach based on the CSSF-TOCSY experiment. Comparison of this reference profile with the sugar composition of several Chinese honey samples of the same declared botanical origin has revealed important differences. A detailed analysis of the saccharide profile of these Chinese honeys suggests product adulteration by overfeeding bee colonies with industrial sugars syrups during the main nectar flow period.

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.