Authenticity and geographic origin of global honeys determined using carbon isotope ratios and trace elements

Research of saccharides and related biocomplexes: A review with recent techniques and applications

Saccharides and biocompounds as saccharide (sugar) complexes have various roles and biological functions in living organisms due to modifications via nucleophilic substitution, polymerization, and complex formation reactions. Mostly, mono-, di-, oligo-, and polysaccharides are stabilized to inactive glycosides, which are formed in metabolic pathways. Natural saccharides are important in food and environmental monitoring. Glycosides with various functionalities are significant in clinical and medical research. Saccharides are often studied with the chromatographic methods of hydrophilic interaction liquid chromatography and anion exchange chromatograpy, but also with capillary electrophoresis and mass spectrometry with their on-line coupling systems. Sample preparation is important in the identification of saccharide compounds. The cases discussed here focus on bioscience, clinical, and food applications.

Analysis of δ13C and δ15N values in Croatian honey by EA-IRMS and possibility of their application in botanical origin verification

The aim of this work was to give characteristic stable carbon and nitrogen isotope ratio (δ13Choney, δ13Cprotein and δ15N) ranges and examine their relation with botanical origin of honey. Despite that δ13C parameter has primary purpose to detect honey adulteration, stable isotopes generally have become important parameter for detection its botanical and geographical origin. The data about stable isotopes are scarce in comparison to other well-known parameters in honey, and in Croatia there is no data about stable isotopes in unifloral honey. This research includes six characteristic honey types (black locust, chestnut, lime, rape, winter savory, and sage honey) from Croatia. Large number of differences between honey types were found in the analyzed IRMS parameters. PCA analysis has successfully separated winter savory from all other honey types, except sage honey, whose samples differed from black locust samples.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13197-023-05888-9.

The buzz about honey-based biosurveys

Approximately 1.8 million metric tonnes of honey are produced globally every year. The key source behind this output, the honey bee (Apis mellifera), works tirelessly to create the delicious condiment that is consumed worldwide. The honey that finds its way into jars on store shelves contains a myriad of information about its biogeographical origins, such as the bees that produced it, the botanical constituents, and traces of other organisms or pathogens that have come in contact with the product or its producer. With the ongoing threat of honey bee decline and overall global biodiversity loss, access to ecological information has become an key factor in preventing the loss of species. This review delves into the various molecular techniques developed to characterize the collective DNA harnessed within honey samples, and how it can be used to elucidate the ecological interactions between honey bees and the environment. We also explore how these DNA-based methods can be used for large-scale biogeographical studies through the environmental DNA collected by foraging honey bees. Further development of these techniques can assist in the conservation of biodiversity by detecting ecosystem perturbations, with the potential to be expanded towards other critical flying pollinators.

Isotopic characteristics (δ13C, δ15N, and δ18O) of honey from Bangladesh retail markets: Investigating sugar manipulation, botanical and geographical authentication

The study analyzed stable isotope composition (carbon, nitrogen, oxygen) of Bangladesh origin monofloral and multifloral honey for the first time to identify the C-4plant sugar adulteration, botanical and geographical differentiation. The C-4 sugar content (11.90 to 86.61%) using carbon isotope values of whole honey and protein extractidentified18% adulterated honeys.Whereas 82% honey have been detected as authentic with the δ13C ranges from -24.86 to -29.26‰ and the C-4 sugar values ranges from -6.75 to 5.67%. The chemometric approach using carbon and nitrogen isotopesvalues revealed discrimination among floral types of Bangladeshi authentic honeys indicating the influence of botanical source on isotopic composition. Canonical discriminant analysis (CDA) of C and N isotopes showed geographic distinction among Bangladeshi and overseas origin honeys. It is notable that the black seed honeys were correctly classified with the CDA analysis representing this type as unique Bangladesh brand as New Zealand manuka honey.

Graphical Discrimination of New Zealand Honey from International Honey Using Elemental Analysis

This study investigated the potential of utilising the elemental fingerprinting of honey to differentiate New Zealand (NZ) honey from that of international origin. Twenty elements were analysed by ICP-MS in 352 honeys from 34 various countries. Of these, 323 honeys (245 New Zealand honeys, 78 international) and two subsets of data (NZ and European origin, n = 306, and, NZ and Denmark/Germany, n = 280) were visualised using principal component analysis (PCA). For the NZ/Europe subset, 42.2% of data was explained in the first two principal components. Statistical classification rules were also derived using linear discriminant analysis (LDA) and decision tree analysis. Various combinations of elements were explored for classification, considering the effect of soil-derived elements and those from anthropogenic sources. A high degree of accuracy (at least 90%) for the characterisation of New Zealand honey was observed for all statistical models, showing the robustness of these analyses. When using decision tree analysis to distinguish New Zealand samples from international samples, a tree with five terminal nodes (using Cs, Ba and Rb) was created with 92.4% accuracy. This work has demonstrated that elemental fingerprints of honey are a promising tool for categorising New Zealand honey from other geographical locations.

Quality control of Ganoderma lucidum by using C, H, O, and N stable isotopes and C and N contents for geographical traceability

Rationale

Ganoderma lucidum (G. lucidum) is a popular medicinal fungus that has been used in traditional medicine for decades, with its provenance influencing its medicinal and commercial worth. The amount of active ingredients and the price of G. lucidum from different origins vary significantly; hence, fraudulent labeling is common. Reliable techniques for G. lucidum geographic verification are urgently required to safeguard the interests of consumers, producers, and honest dealers. A stable isotope is widely acknowledged as a useful traceability technique and could be developed to confirm the geographical origin of G. lucidum.

Methods

G. lucidum samples from various sources and in varying stages were identified by using δ 13C, δD, δ 18O, δ 15N, C, and N contents combined with chemometric tools. Chemometric approaches, including PCA, OPLS-DA, PLS, and FLDA models, were applied to the obtained data. The established models were used to trace the origin of G. lucidum from various sources or track various stages of G. lucidum.

Results

In the stage model, the δ 13C, δD, δ 18O, δ 15N, C, and N contents were considered meaningful variables to identify various stages of G. lucidum (bud development, growth, and maturing) using PCA and OPLS-DA and the findings were validated by the PLS model rather than by only four variables (δ 13C, δD, δ 18O, and δ 15N). In the origin model, only four variables, namely δ 13C, δD, δ 18O, and δ 15N, were used. PCA divided G. lucidum samples into four clusters: A (Zhejiang), B (Anhui), C (Jilin), and D (Fujian). The OPLS-DA model could be used to classify the origin of G. lucidum. The model was validated by other test samples (Pseudostellaria heterophylla), and the external test (G. lucidum) by PLS and FLDA models demonstrated external verification accuracy of up to 100%.

Conclusion

C, H, O, and N stable isotopes and C and N contents combined with chemometric techniques demonstrated considerable potential in the geographic authentication of G. lucidum, providing a promising method to identify stages of G. lucidum.

Detection of honey adulteration using benchtop 1H NMR spectroscopy

High magnetic field NMR spectroscopy featuring the use of superconducting magnets is a powerful analytical technique for the detection of honey adulteration. Such high field NMR systems are, however, typically housed in specialised laboratories, require cryogenic coolants, and necessitate specialist training to operate. Benchtop NMR spectrometers featuring permanent magnets are, by comparison, significantly cheaper, more mobile and can be operated with minimal expertise. The lower magnetic fields used in such systems, however, result in limited spectral resolution, which diminishes their ability to perform quantitative composition analysis. These limitations may be overcome by implementing a recently developed field-invariant model-based fitting method which is defined by the underlying quantum mechanical properties of the nuclear spin system; this method is applied here to quantify the sugar composition of honey using benchtop ¹H NMR (43 MHz) spectroscopy. The detection of adulteration of 26 honey samples with brown rice syrup is quantitatively demonstrated to a minimum adulterant concentration of 5 wt%. Honey adulteration with corn syrup, glucose syrup and wheat syrup was also quantitatively detected using this approach. Our NMR detection of adulteration was shown to be invariant with time over 60 days of storage.

Analysis and Discrimination of Canadian Honey Using Quantitative NMR and Multivariate Statistical Methods

To address the growing concern of honey adulteration in Canada and globally, a quantitative NMR method was developed to analyze 424 honey samples collected across Canada as part of two surveys in 2018 and 2019 led by the Canadian Food Inspection Agency. Based on a robust and reproducible methodology, NMR data were recorded in triplicate on a 700 MHz NMR spectrometer equipped with a cryoprobe, and the data analysis led to the identification and quantification of 33 compounds characteristic of the chemical composition of honey. The high proportion of Canadian honey in the library provided a unique opportunity to apply multivariate statistical methods including PCA, PLS-DA, and SIMCA in order to differentiate Canadian samples from the rest of the world. Through satisfactory model validation, both PLS-DA as a discriminant modeling technique and SIMCA as a class modeling method proved to be reliable at differentiating Canadian honey from a diverse set of honeys with various countries of origins and floral types. The replacement method of optimization was successfully applied for variable selection, and trigonelline, proline, and ethanol at a lower extent were identified as potential chemical markers for the discrimination of Canadian and non-Canadian honeys.

Quality of Honey Imported into the United Arab Emirates

This study was performed to assess the physicochemical quality characteristics of honey imported by the United Arab Emirates (UAE) via Dubai ports between 2017 and 2021. There were 1330 samples analyzed for sugar components, moisture, hydroxymethylfurfural (HMF) content, free acidity, and diastase number. Of the honey tested, 1054 samples complied with the Emirates honey standard, but 276 (20.8%) did not; this was due to non-compliance with one or more quality parameters, thus suggesting some level of adulteration, improper storage or inappropriate heat treatment. For the non-compliant samples, the average values of sucrose content ranged from 5.1 to 33.4%; the sum of glucose and fructose ranged from 19.6 to 88.1%; the moisture content varied from 17.2 to 24.6%; the HMF occurred in a range from 83.2 to 663.0 mg/kg, and the acidity varied from 52 to 85 meq/kg. The non-compliant honey samples were grouped according to their country of origin. India was shown to be the country having the highest percentage of non-compliant samples at 32.5% and Germany had the lowest at 4.5%. This study emphasized that the inspection of honey samples traded internationally should involve physicochemical analysis. A comprehensive inspection of honey at the Dubai ports should reduce incidents of adulterated products being imported.

A review of conventional and rapid analytical techniques coupled with multivariate analysis for origin traceability of soybean

Soybean has developed a reputation as a superfood due to its nutrient profile, health benefits, and versatility. Since 1960, its demand has increased dramatically, going from a mere 17 MMT to almost 358 MMT in the production year 2021/22. These extremely high production rates have led to lower-than-expected product quality, adulteration, illegal trade, deforestation, and other concerns. This necessitates the development of an effective technology to confirm soybean's provenance. This is the first review that investigates current analytical techniques coupled with multivariate analysis for origin traceability of soybeans. The fundamentals of several analytical techniques are presented, assessed, compared, and discussed in terms of their operating specifics, advantages, and shortcomings. Additionally, significance of multivariate analysis in analyzing complex data has also been discussed.

Microbial Community Structure among Honey Samples of Different Pollen Origin

Honey's antibacterial activity has been recently linked to the inhibitory effects of honey microbiota against a range of foodborne and human pathogens. In the current study, the microbial community structure of honey samples exerting pronounced antimicrobial activity was examined. The honey samples were obtained from different geographical locations in Greece and had diverse pollen origin (fir, cotton, fir-oak, and Arbutus unedo honeys). Identification of honey microbiota was performed by high-throughput amplicon sequencing analysis, detecting 335 distinct taxa in the analyzed samples. Regarding ecological indices, the fir and cotton honeys possessed greater diversity than the fir-oak and Arbutus unedo ones. Lactobacillus kunkeei (basionym of Apilactobacillus kun-keei) was the predominant taxon in the fir honey examined. Lactobacillus spp. appeared to be favored in honey from fir-originated pollen and nectar since lactobacilli were more pronounced in fir compared to fir-oak honey. Pseudomonas, Streptococcus, Lysobacter and Meiothermus were the predominant taxa in cotton honey, whereas Lonsdalea, the causing agent of acute oak decline, and Zymobacter, an osmotolerant facultative anaerobic fermenter, were the dominant taxa in fir-oak honey. Moreover, methylotrophic bacteria represented 1.3-3% of the total relative abundance, independently of the geographical and pollen origin, indicating that methylotrophy plays an important role in honeybee ecology and functionality. A total of 14 taxa were identified in all examined honey samples, including bacilli/anoxybacilli, paracocci, lysobacters, pseudomonads, and sphingomonads. It is concluded that microbial constituents of the honey samples examined were native gut microbiota of melliferous bees and microbiota of their flowering plants, including both beneficial bacteria, such as potential probiotic strains, and animal and plant pathogens, e.g., Staphylococcus spp. and Lonsdalea spp. Further experimentation will elucidate aspects of potential application of microbial bioindicators in identifying the authenticity of honey and honeybee-derived products.

Hyperspectral Microscopy Technology to Detect Syrups Adulteration of Endemic Guindo Santo and Quillay Honey Using Machine-Learning Tools

Honey adulteration is a common practice that affects food quality and sale prices, and certifying the origin of the honey using non-destructive methods is critical. Guindo Santo and Quillay are fundamental for the honey production of Biobío and the Ñuble region in Chile. Furthermore, Guindo Santo only exists in this area of the world. Therefore, certifying honey of this species is crucial for beekeeper communities-mostly natives-to give them advantages and competitiveness in the global market. To solve this necessity, we present a system for detecting adulterated endemic honey that combines different artificial intelligence networks with a confocal optical microscope and a tunable optical filter for hyperspectral data acquisition. Honey samples artificially adulterated with syrups at concentrations undetectable to the naked eye were used for validating different artificial intelligence models. Comparing Linear discriminant analysis (LDA), Support vector machine (SVM), and Neural Network (NN), we reach the best average accuracy value with SVM of 93% for all classes in both kinds of honey. We hope these results will be the starting point of a method for honey certification in Chile in an automated way and with high precision.

Inductively Coupled Plasma-Mass Spectrometry (ICP-MS), a Useful Tool in Authenticity of Agricultural Products' and Foods' Origin

Fraudulent practices are the first and foremost concern of food industry, with significant consequences in economy and human's health. The increasing demand for food has led to food fraud by replacing, mixing, blending, and mislabeling products attempting to increase the profits of producers and companies. Consequently, there was the rise of a multidisciplinary field which encompasses a large number of analytical techniques aiming to trace and authenticate the origins of agricultural products, food and beverages. Among the analytical strategies have been developed for the authentication of geographical origin of foodstuff, Inductively Coupled Plasma Mass Spectrometry (ICP-MS) increasingly dominates the field as a robust, accurate, and highly sensitive technique for determining the inorganic elements in food substances. Inorganic elements are well known for evaluating the nutritional composition of food products while it has been shown that they are considered as possible tracers for authenticating the geographical origin. This is based on the fact that the inorganic component of identical food type originating from different territories varies due to the diversity of matrix composition. The present systematic literature review focusing on gathering the research has been done up-to-date on authenticating the geographical origin of agricultural products and foods by utilizing the ICP-MS technique. The first part of the article is a tutorial about food safety/control and the fundaments of ICP-MS technique, while in the second part the total research review is discussed.

Isolation and Barcoding of Trace Pollen-free DNA for Authentication of Honey

Adulteration and mislabeling of honey to mask its true origin have become a global concern. Pollen microscopy, the current gold standard for identifying honey's geographical and plant origins, is laborious, requires extensive training, and fails to identify filtered honey and honey spiked with pollen from a more favorable plant to disguise its origins. We successfully isolated pollen-free DNA from filtered honey using three types of adsorbents: (i) anti-dsDNA antibodies coupled to magnetic microspheres; (ii) anion-exchange adsorbent; and (iii) ceramic hydroxyapatite. The internal transcribed spacer 2 region of the captured pollen-free DNA was polymerase chain reaction-amplified and subjected to next-generation sequencing. Using an in-house bioinformatics pipeline, initial experiments showed that anion exchange had the greatest capacity to capture trace pollen-free DNA, and it was successfully applied to isolate DNA from five honey samples. Enrichment of trace pollen-free DNA from filtered honey samples opens a new approach for identifying the true origins of honey.

Using Compound-Specific Carbon Stable Isotope Analysis of Squalene to Establish Provenance and Ensure Sustainability for the Deep-Water Shark Liver Oil Industry

Deep-water dogfish (sharks) are caught on Australia’s continental shelf as by-products to other deep-water species with revenue derived from fillets for human consumption and from the livers which are sold for their oil content. Deep-water dogfish utilise a large oil-rich liver for buoyancy, which may account for 20–25% of their body weight. An important constituent of certain dogfish liver oil is squalene, a highly unsaturated triterpenoid (C30H50) hydrocarbon which in some species can be up to 90% of the oil, though in the Australian commercial species it is typically around 50%. Squalene (and deep-water dogfish liver oil in general) has a long-standing high value in products, such as cosmetics and nutraceuticals. Manufacturers are increasingly required to demonstrate the sustainability of products, and this is integral to the importance of demonstrating product provenance. Australia’s mid-slope deep-water dogfish fishery is recognised globally as well managed and sustainable; therefore, it is important to be able to distinguish products derived from these regions from other unregulated, unsustainable and cheaper sources in order to protect Australia’s competitive advantages and ensure sustainability. In this study, we have sourced deep-water dogfish liver oil samples originating from Southeast Australia, New Zealand, India, Northeast Africa and the Arabian Sea. The squalene was isolated by commercial or laboratory processing. A compound-specific carbon stable isotope analysis of the derived squalene was then used to determine isotopic resolution and assign the likely origins of a variety of commonly available off-the-shelf nutraceuticals in Australian outlets. Squalene sourced and produced from Southeast Australian and New Zealand dogfish liver oils showed δ13C values in the range of −22.1 to −24.2‰, with all other squalene samples distinguishable at −19.9 to −20.7‰. Many of the off-the-shelf squalene products claiming to be of Australian origin showed δ13C values very distinct from the range of the genuine Southeast Australian- and New Zealand-produced squalene.

The proper choice of proxies for relevant strontium isotope baselines used for provenance and mobility studies in glaciated terranes - Important messages from Denmark

Strontium (Sr) isotope based provenance and mobility studies of ancient humans and animals necessitate representative isoscapes/baselines. However, regions/terranes that were shaped and affected by glaciers during the last Ice Ages and are covered by glaciogenic sediments present a challenge with regards to the choice of suitable surface proxy archives. Recent studies proposed that only ⁸⁷Sr/⁸⁶Sr signatures from pristine areas are relevant for this purpose. To test this theory, 160 new Sr concentrations [Sr] and ⁸⁷Sr/⁸⁶Sr signatures composed from ~960 subsamples of soil leachates and plants, complemented with 55 surface waters from agriculturally unaffected pristine forest sites from all over Denmark (island of Bornholm excluded) were analyzed. The results reveal that average ⁸⁷Sr/⁸⁶Sr signatures of all three proxies (plants: 0.7115 ± 0.0025; 2σ, n = 162; soil leachates: 0.7118 ± 0.0037; 2σ; n = 161, surface waters: 0.7104 ± 0.0030; 2σ, n = 55) are elevated compared to larger water bodies (creeks, rivers, lakes). In mixing diagrams, the data converge in a shared high [Sr] low ⁸⁷Sr/⁸⁶Sr endmember, which points to either remnant natural carbonates and/or organic components retaining carbonate Sr in the studied Podzols/Luvisols. The indications for more abundant carbonates in the past, compared to today's acid leached soils, implies that ⁸⁷Sr/⁸⁶Sr values measured from pristine forest locations and heathlands do not adequately reflect the biosphere compositions that prevailed ~12,000-2000 thousand years ago. Consequently, pristine forests in Denmark seem to be unsuitable proxy archive environments for constructing Sr isotope baselines for determining the provenance and mobility of ancient humans and animals. Hence, ⁸⁷Sr/⁸⁶Sr values measured in these pristine areas are non-representative and inadequate, and their use will lead to wrong interpretations. Finally, our study sheds light on the complexity of defining relevant and representative isoscapes/baselines in significantly changing environments and areas where the surface biosphere conditions do not necessary reflect the underlying geology.

Helium-flushed sheathed nickel tube reactor for continuous flow oxygen stable isotope compound-specific analysis

RATIONALE

Compound-specific oxygen stable isotope analysis has been commercially available for about 20 years but the technique has been infrequently applied and practical operating knowledge is limited. Existing reactor designs and chemistry fail to fully exclude contaminating oxygen, are chromatographically flawed, and are generally fabricated from expensive platinum tubing.

METHODS

As a new interface between the gas chromatograph and isotope ratio mass spectrometer, we used a nickel tube reactor (containing no platinum wires) in a ceramic sheath with countercurrent helium flushing, operated at 1250°C. We analyzed suites of four long-chain alcohols (LCAs), defining the least and most ¹⁸ O-enriched LCAs as internal standards. The other two LCAs, co-injected in varying amounts, were treated as unknowns and amplitude-corrected during data reduction.

RESULTS

With this design, signals from non-oxygenated compounds are minimized with a hydrogen trickle, while excessive graphitization is counterproductive. A balance of hydrogen and graphite is required to maintain a proper, stable redox state in the reactor. With low extraneous oxygen, the exact hydrogen flow has little effect on final δ¹⁸ O data quality. Overall average δ¹⁸ O values precisions and errors for the unknowns were better than 0.4 ‰ for injections between 2 and 7 nmol per component.

CONCLUSIONS

Our actively flushed sheath reduces oxygen infiltration to negligible levels and results in a chromatographic flow devoid of dead or poorly swept volumes. The improved design allows measurement of LCAs with accuracy and precision sufficient to enable investigating real processes, and may also have wider applications to other isotopes.

Study on stable carbon isotope fractionation of rape honey from rape flowers (Brassica napus L.) to its unifloral ripe honey

A new idea and strategy for honey traceability and identification was provided by studying the carbon isotope fractionation of rape honey and its components in the different ripening process, as well as the fractionation from rape flowers, stamens, nectar to rape honey. The results showed the moisture content of rape honey continued to decrease, and the glucose and fructose content continued to increase during the ripening process. The δ¹³C of rape honey and its protein were less affected by honey ripeness, while the δ¹³C of sugars in rape honey were greatly affected by this. At the same time, the fractionation of carbon isotope from rape flowers to honey was significant. The δ¹³C of rape honey and its protein, disaccharide, fructose, and glucose had a strong correlation, and the δ¹³C of rape honey and its components were mainly related to rape flowers and its stamens.

Food regulation and policing: innovative technology to close the regulatory gap in Australia

Internationally, food regulations are centred on human health and safety to prevent health crises. In Australia, regulatory control over the health and safety of humans is sound, however from a criminological perspective, control over fraudulent activities within food supply chains lack. Food fraud knows no geographical boundaries and has endless reach, therefore should be prioritised by policymakers, regulators and law enforcement. Australia’s reputation for high-quality food is important domestically, but also for establishing and maintaining trust in international food trade relationships, therefore lack of enforcement over food could damage ‘Brand Australia’. Given the food industry’s vested interest in maintaining this reputation, it must also play a role to protect it. This research reviews regulatory landscape against food fraud in Australia and then, questions whether coupling informal controls to support existing formal regulatory controls may be the most appropriate and holistic way forward to protect the industry and consumers. It tests a regulatory pluralism framework to determine whether it can logically organize informal, innovative responses to contribute cohesively alongside formal controls at various points along the supply chain to prevent food fraud. Finally, it considers available informal, innovative technologies to: enhance testing regimes; prevent product and label tampering; and trace food supply chains adopted internationally show positive progress in responding to increasingly sophisticated and organized global food fraud. The research concludes adopting a regulatory pluralism framework, coupling existing regulatory controls and innovative technology could enhance and strengthen Australia’s regulatory response to fraud within its food industry.

Levels of trace elements and rare earth elements in honey from Jordan

Honey is a common sweetener in the Jordanian diet with an annual consumption of approximately one thousand tons, two-thirds of which are imported. It is believed that the elemental profile of honey is an indicator of safety and botanical and geographic origin. In the literature, there are a lack of studies concerning the levels of major and trace elements in honey in Jordan. A total of 46 elements, including 15 rare earth elements (REEs), were analyzed by inductively coupled plasma-mass spectrometry (ICP-MS) in 18 monofloral and multifloral imported honey samples and 12 multifloral local samples. Regarding monofloral samples, Black Forest samples had the highest total metal content, while acacia samples had the lowest total metal content. Local multifloral honey had the largest Sr and total REE levels, while it had the lowest Mn levels. Very low levels of toxic elements were found in all samples, indicating the safety of honey in Jordan for human consumption. The results of this study showed that a large number of samples (> 100) and the application of advanced statistical models are required to discriminate between multifloral imported and local honey.

Cataloguing the small RNA content of honey using next generation sequencing

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Plant miRNAs are present in Australian polyfloral and Leptospermum scoparium honey.

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Sequencing shows that honey contains a diverse range of small, non-coding RNAs.

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Honey RNA comes from different phylogenies including invertebrates and prokaryotes.

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Unique small RNA profiles can provide insight into honey production conditions.

Honey adulteration is a problem that effects the global honey industry and specifically, has been discovered in the Australian market. Common methods of adulteration include dilution with sugar syrup substitutes and the mislabelling of the floral and geographic origin(s) of honey. Current authentication tools rely on the molecular variability between different honeys, identifying unique chemical profiles and/or DNA signatures characteristic of a particular honey.

Honey is known to contain plant miRNAs derived from its floral source. To explore the composition and variability of honey RNA molecules, this is the first study to catalogue the small RNA content of Australian polyfloral table honey and New Zealand Leptospermum scoparium honey using next generation sequencing. The data shows that in addition to miRNAs, honey contains a variety of small non-coding RNAs including tRNA-derived fragments. Moreover, the honey small RNAs are derived from a range of phylogenetic sources, including from plant, invertebrate, and prokaryotic species. The data indicates that different honeys contain unique small RNA profiles, which suggests a novel avenue in developing molecular-based honey authentication tools.

Opportunities and Constraints in Applying Artificial Neural Networks (ANNs) in Food Authentication. Honey—A Case Study

The present work aims to test the potential of the application of Artificial Neural Networks (ANNs) for food authentication. For this purpose, honey was chosen as the working matrix. The samples were originated from two countries: Romania (50) and France (53), having as floral origins: acacia, linden, honeydew, colza, galium verum, coriander, sunflower, thyme, raspberry, lavender and chestnut. The ANNs were built on the isotope and elemental content of the investigated honey samples. This approach conducted to the development of a prediction model for geographical recognition with an accuracy of 96%. Alongside this work, distinct models were developed and tested, with the aim of identifying the most suitable configurations for this application. In this regard, improvements have been continuously performed; the most important of them consisted in overcoming the unwanted phenomenon of over-fitting, observed for the training data set. This was achieved by identifying appropriate values for the number of iterations over the training data and for the size and number of the hidden layers and by introducing of a dropout layer in the configuration of the neural structure. As a conclusion, ANNs can be successfully applied in food authenticity control, but with a degree of caution with respect to the “over optimization” of the correct classification percentage for the training sample set, which can lead to an over-fitted model.

Application of Compound-Specific Isotope Analysis in Environmental Forensic and Strategic Management Avenue for Pesticide Residues

Unintended pesticide pollution in soil, crops, and adjacent environments has caused several issues for both pesticide users and consumers. For users, pesticides utilized should provide higher yield and lower persistence while considering both the environment and agricultural products. Most people are concerned that agricultural products expose humans to pesticides accumulating in vegetation. Thus, many countries have guidelines for assessing and managing pesticide pollution, for farming in diverse environments, as all life forms in soil are untargeted to these pesticides. The stable isotope approach has been a useful technique to find the source of organic matter in studies relating to aquatic ecology and environmental sciences since the 1980s. In this study, we discuss commonly used analytical methods using liquid and gas chromatography coupled with isotopic ratio mass spectrometry, as well as the advanced compound-specific isotope analysis (CSIA). CSIA applications are discussed for tracing organic pollutants and understanding chemical reactions (mechanisms) in natural environments. It shows great applicability for the issues on unintended pesticide pollution in several environments with the progress history of isotope application in agricultural and environmental studies. We also suggest future study directions based on the forensic applications of stable isotope analysis to trace pesticides in the environment and crops.

Occurrence of environmental contaminants (pesticides, herbicides, PAHs) in Australian/Queensland Apis mellifera honey

Honey is a popular agricultural product containing mostly sugars and water, but due to its nutritious components and natural production by honeybees (Apis mellifera) from floral nectar, it is marketed as a premium health food item. As environmental monitors, honeybees can potentially transfer environmental contaminants to honey. Whilst pesticides can have ubiquitous presence in agricultural and urban areas, polycyclic aromatic hydrocarbons (PAHs) can be more prevalent in higher density urban/industrial environments. Australian beehives are customarily located in rural areas/forests, but it is increasingly popular to keep hives in urban areas. This study assessed the levels of environmental contaminants in honeys (n = 212) from Queensland/Australian sources including rural, peri-urban and urban areas. Honey samples were analysed by LC-MS/MS and GC-MS/MS for 53 herbicides, 83 pesticides, 18 breakdown products (for certain pesticides/herbicides) and 33 PAHs and showed low/negligible pesticide, herbicide and PAHs contamination, consistent regardless of honey origins.

Selected Instrumental Techniques Applied in Food and Feed: Quality, Safety and Adulteration Analysis

This review presents an overall glance at selected instrumental analytical techniques and methods used in food analysis, focusing on their primary food science research applications. The methods described represent approaches that have already been developed or are currently being implemented in our laboratories. Some techniques are widespread and well known and hence we will focus only in very specific examples, whilst the relatively less common techniques applied in food science are covered in a wider fashion. We made a particular emphasis on the works published on this topic in the last five years. When appropriate, we referred the reader to specialized reports highlighting each technique's principle and focused on said technologies' applications in the food analysis field. Each example forwarded will consider the advantages and limitations of the application. Certain study cases will typify that several of the techniques mentioned are used simultaneously to resolve an issue, support novel data, or gather further information from the food sample.

Advances in Troubleshooting Fish and Seafood Authentication by Inorganic Elemental Composition

The demand for fish and seafood is growing worldwide. Meanwhile, problems related to the integrity and safety of the fishery sector are increasing, leading legislators, producers, and consumers to search for ways to effectively protect themselves from fraud and health hazards related to fish consumption. What is urgently required now is the availability of reliable, truthful, and reproducible methods assuring the correspondence between the real nature of the product and label declarations accompanying the same product during its market life. The evaluation of the inorganic composition of fish and seafood appears to be one of the most promising strategies to be exploited in the near future to assist routine and official monitoring operations along the supply chain. The present review article focuses on exploring the latest scientific achievements of using the multi-elemental composition of fish and seafood as an imprint of their authenticity and traceability, especially with regards to the geographical origin. The scientific literature of the last 10 years focusing on the analytical determination and statistical elaboration of elemental data (alone or in combination with methodologies targeting other compounds) to verify the identity of fishery products is summarized and discussed.

High-Performance Anion Exchange Chromatography with Pulsed Amperometric Detection (HPAEC-PAD) and Chemometrics for Geographical and Floral Authentication of Honeys from Southern Italy (Calabria region)

High-performance anion exchange chromatography with pulsed amperometric detection (HPAEC–PAD) combined with chemometric analysis was developed to describe, for the first time, the sugar profile of sixty-one honeys of different botanical origin produced in southern Italy (Calabria Region). The principal component and linear discriminant analysis used to describe the variability of sugar data were able to discriminate the honeys according to their botanical origin with a correlation index higher than 90%. For the purpose of the robustness of the conclusions of this study, the analytical advantages of the HPAEC–PAD method have been statistically demonstrated compared to the official Italian HPLC–RI method (Refractive Index detection). Finally, as the characterization of the floral and geographical origin of honey became an important issue due to high consumer demand, 13 acacia honeys originating from Europe and China were studied by using the same method. By chemometric method it was possible to discriminate the different geographical origin with an index of 100%. All results proved the possibility to identify the sugar profile obtained by HPAEC–PAD combined with a robust statistical analysis, as a tool of authentication.

Employing DNA metabarcoding to determine the geographical origin of honey

Unfavourable climatic conditions force Iranian beekeepers to translocate over large distances in the course of the year. However, irrespective of the main place of production, the honey is always labeled with the name of the beekeepers' hometown, which leads consequently to mislabeled products. The present study investigates the capability of DNA metabarcoding to locate the geographical origin of honey. The molecular markers (ITS2 and rbcL) allowed identification of 926 plant species in studied samples. A comprehensive review of floristic reference books specified 34 key species that could be used to successfully determine the geographical origin in 91.4% of samples. These key species were usually present in honey with tiny amounts and thus, conventional palynology might not be able to detect them. The present investigation indicates that although ITS2 is able to detect more species than rbcL, utilizing a combination of both markers provides more robust evidence of geographical origin.

Use of elemental profiles to verify geographical origin and botanical variety of Spanish honeys with a protected denomination of origin

Honey with Protected Denomination of Origin (PDO) could be an attractive target for fraudsters. Elemental profiles by Energy Dispersive-X Ray Fluorescence were processed by multivariate methods to classify 183 PDO honeys produced in three regions of Spain (Liébana, Granada, Tenerife). Additional honey samples (18) produced in a fourth region without PDO (El Bierzo) separated well from the PDO clusters. The manganese content was a discriminant marker of Liébana PDO and El Bierzo, that could also be differentiated from each other. Within each region, distinct clusters revealed differences between dark vs light varieties, multi- vs uni-floral honey and producers of the same PDO. The developed models were validated with 131 samples produced outside the PDO regions and El Bierzo. The proposed classification approach could be implemented as a fast screening tool to support pollen analysis in honey authentication. The reduced number of observations in some light honey models affected their performance.

Determination of the Geographical Origin of Maltese Honey Using 1H NMR Fingerprinting

The price of honey, as a highly consumed natural product, depends on its botanical source and its production environment, causing honey to be vulnerable to adulteration through mislabeling and inappropriate, fraudulent production. In this study, a fast and simple approach is proposed to tackle this issue through non-target one dimensional zg30 and noesypr1d 1H NMR fingerprint analysis, in combination with multivariate data analysis. Results suggest that composition differences in sugars, amino acids, and carboxylic acid were sufficient to discriminate between the tested honey of Maltese origin and that of non-local origin. Indeed, all chemometric models based on noesypr1d analysis of the whole fraction honey showed better prediction in geographical discrimination. The possibility of discrimination was further investigated through analysis of the honey's phenolic extract composition. The partial least squares models were deemed unsuccessful to discriminate, however, some of the linear discriminant analysis models achieved a prediction accuracy of 100%. Lastly, the best performing models of both the whole fraction and the phenolic extracts were tested on five samples of unknown geographic for market surveillance, which attained a high agreement within the models. Thus, suggesting the use of non-target 1H NMR coupled with the multivariate-data analysis and machine learning as a potential alternative to the current time-consuming analytical methods.

Mineral and Trace Element Analysis of Australian/Queensland Apis mellifera Honey

Honey is an extensively utilized sweetener containing sugars and water, together with small quantities of vitamins, minerals, fatty acids, amino acids and proteins. Naturally produced by honeybees (Apis mellifera) from floral nectar, honey is increasingly sold as a health food product due to its nutritious features. Certain honeys are retailed as premium, trendy products. Honeybees are regarded as environmental monitors, but few reports examine the impact of environment on Australian honey trace elements and minerals. In higher density urban and industrial environments, heavy metals can be common, while minerals and trace elements can have ubiquitous presence in both agricultural and urban areas. Honey hives are traditionally placed in rural and forested areas, but increasingly the trend is to keep hives in more urban areas. This study aimed to determine the levels of 26 minerals and trace elements and assess elemental differences between honeys from various regional Queensland and Australian sources. Honey samples (n = 212) were acquired from markets, shops and supermarkets in Queensland while urban honeys were purchased online. The honey samples were classified into four groups according to their regional sources: urban, rural, peri-urban and blend honey. Elemental analyses of honey were performed using ICP-MS and ICP-OES after microwave and hot block digestion. Considerable variations of essential trace elements (Co, Cu, Cr, Fe, Mn, Mo and Zn) and mineral levels (Ca, K, Mg, Na and P) were found in honeys surveyed. There were significant differences (p < 0.05) between urban and rural honey samples for B, Na, P, Mn, K, Ca and Cu. Significant differences (p < 0.05) were also found between blend and urban honey samples for K, Cu, P, Mn, Sr, Ni, B and Na. Peri-urban versus urban honeys showed significant differences in P, K and Mn. For rural and peri-urban honeys, the only significant difference (p < 0.05) was for Na. Toxic heavy metals were detected at relatively low levels in honey products. The study revealed that the Queensland/Australian honey studied is a good source of K and Zn and would constitute a good nutritional source of these elements.

Geographical origin and botanical type honey authentication through elemental metabolomics via chemometrics

The trace and rare earth elements content of 93 honeys of different botanical type and origin have been studied through ICP-MS. Discriminant Analysis (DA) was successful for botanical type and geographical origin classification while Cluster Analysis (CA) was successful only for botanical type. Through Probabilistic Neural Network (PNN) analysis, 85.3% were correctly classified by the network according to their geographical origin and 73.3% according to their organic characterization. A Partial Least Squares (PLS) model was constructed, giving a prediction accuracy of more than 95%. Information obtained using Rare Earths (Y, La, Ce, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb, Lu) and trace elements (Li, Mg, Mn, Ni, Co, Cu, Sr, Ba, Pb) via chemometric evaluation facilitated classification of honey samples.

Evaluation of physicochemical properties of Qinling Apis cerana honey and the antimicrobial activity of the extract against Salmonella Typhimurium LT2 in vitro and in vivo

Apis cerana honey collected from the Qinling Mountains in China has been widely used for its antimicrobial property in traditional Chinese medicine. However, its antibacterial mechanism against Salmonella Typhimurium LT₂ is still uncertain. A total of 52 volatile components were identified using headspace-gas-chromatography-ion-mobility, and Qinling A. cerana honey exhibited more abundant aromas than monofloral honeys. The phenolic extracts of honey sample F exhibited the lowest minimum inhibitory concentration (5 mg/mL), and chlorogenic acid exhibited the highest (155.91 ± 0.79 mg/kg), followed by caffeic acid, and rutin. After being treated with the extract, cell membranes of S. Typhimurium LT₂ significantly shrunk and further collapsed. The extract treatment on mice caused a significant decrease in S. Typhimurium LT₂, and a dramatic increase in the potential prebiotic Lactobacillus in both the caecum and colon. The results demonstrate that the Qinling A. cerana honey extract could effectively inhibit S. Typhimurium in vitro and in vivo.

Exploring the Potential of the Microbiome as a Marker of the Geographic Origin of Fresh Seafood

Geographic food fraud – misrepresenting the geographic origin of a food item, is very difficult to detect, and therefore this type of fraud tends to go undetected. This potentially negatively impacts the health of Canadians and economic success of our seafood industry. Surveillance studies have shown that up to a significant portion of commercially sold seafood items in Canada are mislabeled or otherwise misrepresented in some way. The current study aimed to determine if the microbiome of fresh shellfish could be used as an accurate marker of harvest location. Total DNA was extracted from the homogenate of 25 batches of fresh soft-shell clams (Mya arenaria) harvested in 2015 and 2018 from two locations on the East Coast of Canada and the microbiome of each homogenate was characterized using 16S rRNA targeted amplicon sequencing. Clams harvested from Nova Scotia in both years had a higher abundance of Proteobacteria and Acidobacteria (p < 0.05), but a lower abundance of Actinobacteria (p < 0.05) than those from Quebec. Alpha-diversity also differed significantly between sites. Samples harvested from Nova Scotia had greater diversity (p < 0.0001) than those from Quebec. Beta-diversity analysis showed that the microbial community composition was significantly different between the samples from Nova Scotia and Quebec and indicated that 16S rRNA targeted amplicon sequencing might be an effective tool for elucidating the geographic origin of unprocessed shellfish. To evaluate if the microbiome of shellfish experiences a loss of microbial diversity during processing and storage – which would limit the ability of this technique to link retail samples to geographic origin, 10 batches of retail clams purchased from grocery stores were also examined. Microbial diversity and species richness was significantly lower in retail clams, and heavily dominated by Proteobacteria, a typical spoilage organism for fresh seafood, this may make determining the geographic origin of seafood items more difficult in retail clams than in freshly harvested clams.

New Approaches to Identifying and Reducing the Global Burden of Disease From Pollution

Pollution from multiple sources causes significant disease and death worldwide. Some sources are legacy, such as heavy metals accumulated in soils, and some are current, such as particulate matter. Because the global burden of disease from pollution is so high, it is important to identify legacy and current sources and to develop and implement effective techniques to reduce human exposure. But many limitations exist in our understanding of the distribution and transport processes of pollutants themselves, as well as the complicated overprint of human behavior and susceptibility. New approaches are being developed to identify and eliminate pollution in multiple environments. Community-scale detection of geogenic arsenic and fluoride in Bangladesh is helping to map the distribution of these harmful elements in drinking water. Biosensors such as bees and their honey are being used to measure heavy metal contamination in cities such as Vancouver and Sydney. Drone-based remote sensors are being used to map metal hot spots in soils from former mining regions in Zambia and Mozambique. The explosion of low-cost air monitors has allowed researchers to build dense air quality sensing networks to capture ephemeral and local releases of harmful materials, building on other developments in personal exposure sensing. And citizen science is helping communities without adequate resources measure their own environments and in this way gain agency in controlling local pollution exposure sources and/or alerting authorities to environmental hazards. The future of GeoHealth will depend on building on these developments and others to protect a growing population from multiple pollution exposure risks.

Optimised approach for small mass sample preparation and elemental analysis of bees and bee products by inductively coupled plasma mass spectrometry

The elemental fingerprint of honey, pollen and bees are useful biomonitors of anthropogenic activities across the world. Elements in honey and pollen may also be analysed for their nutritional value and potential toxicity. There are currently limited studies that address the use of small sample masses while retaining good reproducibility and detection limits during elemental analysis. The aim of this study was to develop a simple analytical method to quantify 39 major, minor, trace and rare earth elements in small mass samples of bees, honey and pollen by inductively coupled plasma mass spectrometry. The final method was validated for 20-200 mg bee, 20-100 mg pollen or 50-200 mg of honey with 0.2 mL nitric acid followed by 0.1 mL hydrogen peroxide in a digestion block (80 °C, 2 h total); samples were made up to a final volume of approximately 6 mL. The method reduces the volume of chemicals used, limits sample manipulation and improves detection limits over traditional digestion methods. The sample preparation and analysis method were deemed to be satisfactory for the three matrices examined, with spike recoveries ranging from 96 (B) to 129% (As) for trace elements and 91 (Pr) to 112% (La) for rare earth elements, and acceptable detection limits (down to 5.07 μg kg^-1 for Co using 30 mg sample mass, pollen). Precision was acceptable with the relative percent standard deviation of fully homogenised samples ranging from 0.53 (K, bee, 20 mg) to 24% (As, 30 mg, bee) across the three matrices and all masses analysed. This small mass digestion method enables the analysis of a single bee allowing a more distinctive elemental signature to be determined. Similarly, pollen from fewer flowers of the same species can be pooled together which is advantageous for analysis of flowers that produce little pollen.

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

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