NMR carbohydrate profile in tracing acacia honey authenticity

Trace phospholipid and fatty acid differences between dairy and plant-based milk products by 1H and 31P NMR spectroscopy combined with multivariate statistical analysis

With development of modern food industry, plant-based milk products are widely used to replace dairy products to cook different kinds of food. Due to different origins, it is necessary to assess the nutrition difference between dairy and plant-based milk products. Phospholipids and unsaturated fatty acids, as the important nutrients in cream and butter, were closely related to body development and health. This study developed a rapid determination of phospholipids and double bonds in creams and butters based on 31P NMR and 1H NMR for nutritional difference assessment. Unsupervised principal component analysis and supervised orthogonal least squares discriminant analysis showed marked differences between dairy and plant-based milk products. Eight compounds were screened by variable importance in projection, fold change and P-value. Furthermore, two biomarkers (phosphatidylserine and phosphatidylethanolamine) were identified to distinguish dairy and plant-based milk products. The study demonstrated that 31P NMR has great potential for rapidly distinguishing milk origins.

NMR sugar-profile in genuine grape must

The wine market has always faced the problem of fraud, including the addition of exogenous sugar solutions to grape musts to increase the final alcohol content. Since in some countries the practice of chaptalization is prohibited (except by adding concentrated must) it is necessary to broaden the analytical techniques that allow the identification of this type of fraud. The aim of this study was to define an NMR-based sugar profile of genuine grape must to set concentration limits for each sugar as parameters of authenticity. Glucose, fructose, together with eleven minor sugars were quantified in 82 genuine Italian grape musts, developing an analytical procedure based on highly selective chemical shift filters followed by TOCSY. Alongside the characteristic myo- and scyllo-inositol, significant contents of mannose, galactose, and trehalose were also found. Otherwise, maltose, rhamnose, arabinose, sucrose and lactose are present in lower concentrations and show great concentration variability.

Intelligent System/Equipment for Quality Deterioration Detection of Fresh Food: Recent Advances and Application

The quality of fresh foods tends to deteriorate rapidly during harvesting, storage, and transportation. Intelligent detection equipment is designed to monitor and ensure product quality in the supply chain, measure appropriate food quality parameters in real time, and thus minimize quality degradation and potential financial losses. Through various available tracking devices, consumers can obtain actionable information about fresh food products. This paper reviews the recent progress in intelligent detection equipment for sensing the quality deterioration of fresh foods, including computer vision equipment, electronic nose, smart colorimetric films, hyperspectral imaging (HSI), near-infrared spectroscopy (NIR), nuclear magnetic resonance (NMR), ultrasonic non-destructive testing, and intelligent tracing equipment. These devices offer the advantages of high speed, non-destructive operation, precision, and high sensitivity.

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

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

Automatic nmr-based protocol for assessment of honey authenticity

¹H NMR analysis of organic extracts of honey is a powerful technique to confirm its botanical origin, thanks to the presence of signals that are specific to each floral typology. Similarly, signals from bee metabolites provide an important tool to verify honey entomological origin. Here, we present a method for honey screening that does not require any detailed analysis of the NMR spectrum for the detection and quantification of such markers. Our approach is based on the measurement of two spectral parameters, named entomological factor (EF) and aromatic factor (AF), calculated by integration of well-defined regions of the NMR spectrum. The values of EF and AF can reveal direct or indirect dilution of honey with sugar syrups. This method was tested on honeys of different floral origins and could identify all adulterated samples previously recognized by official techniques. Notably, several samples found compliant by official methods were proven non-genuine by the proposed approach.

NMR-Based Approaches in the Study of Foods

In this review, the three different NMR-based approaches usually used to study foodstuffs are described, reporting specific examples. The first approach starts with the food of interest that can be investigated using different complementary NMR methodologies to obtain a comprehensive picture of food composition and structure; another approach starts with the specific problem related to a given food (frauds, safety, traceability, geographical and botanical origin, farming methods, food processing, maturation and ageing, etc.) that can be addressed by choosing the most suitable NMR methodology; finally, it is possible to start from a single NMR methodology, developing a broad range of applications to tackle common food-related challenges and different aspects related to foods.

Quality assessment and chemical diversity of Australian propolis from Apis mellifera bees

The propolis industry is well established in European, South American and East Asian countries. Within Australia, this industry is beginning to emerge with a few small-scale producers. To contribute to the development of the Australian propolis industry, the present study aimed to examine the quality and chemical diversity of propolis collected from various regions across Australia. The results of testing 158 samples indicated that Australian propolis had pure resin yielding from 2 to 81% by weight, total phenolic content and total flavonoid content in one gram of dry extract ranging from a few up to 181 mg of gallic acid equivalent and 145 mg of quercetin equivalent, respectively. Some Australian propolis showed more potent antioxidant activity than the well-known Brazilian green, Brazilian red, and Uruguayan and New Zealand poplar-type propolis in an in vitro DPPH assay. In addition, an HPLC–UV analysis resulted in the identification of 16 Australian propolis types which can be considered as high-grade propolis owing to their high total phenolic content. Chemometric analysis of their ¹H NMR spectra revealed that propolis originating from the eastern and western coasts of Australia could be significantly discriminated based on their chemical composition.

Determination of the Carbohydrate Profile and Invertase Activity of Adulterated Honeys after Bee Feeding

The higher demand for honey from consumers, combined with its limited availability, has led to different types of honey adulteration, causing substantial economic as well as negative impacts on consumers’ nutrition and health. Therefore, a need has emerged for reliable and cost-effective quality control methods to detect honey adulteration to ensure both the safety and quality of honey. To simulate the process with those applied by beekeepers in real-time, bee colonies were fed with different types of bee feeding (sugar syrup, candy paste and commercial syrup). The produced samples were analyzed for their carbohydrate profile and their invertase activity with the aim to find the effects of bee feeding on the quality of the final product. Honey samples produced after feeding with commercial syrup presented low fructose (22.9 %) and glucose (31.7 %) concentrations and high content of maltose (20.1%), while the samples that came from bee feeding with sugar syrup and candy paste had high concentrations of sucrose (6.2 % and 3.2 %, respectively), exceeding in some cases the legislative limits. Moreover, the samples coming from sugar feeding had lower values of invertase activity, while the group with inverted syrup was clearly discriminated through multi-discriminant analysis. The invertase activity of control samples was found at 153.7 U/kg, which was significantly higher compared to the other groups. The results showed that bee feeding during honey production might lead to adulteration, which can be detected through routine analyses, including the carbohydrate profile and the invertase activity.

Honey authenticity: the opacity of analytical reports - part 1 defining the problem

The composition of honey, a complex natural product, challenges analytical methods attempting to determine its authenticity particularly in the face of sophisticated adulteration. Of the advanced analytical techniques available, only isotope ratio mass spectrometry (IRMS) is generally accepted for its reproducibility and ability to detect certain added sugars, with nuclear magnetic resonance (NMR) and high-resolution mass spectrometry (HRMS) being subject to stakeholder differences of opinion. Herein, recent reviews of honey adulteration and the techniques to detect it are summarised in the light of which analytical reports are examined that underpinned a media article in late 2020 alleging foreign sugars in UK retailers' own brand honeys. The requirement for multiple analytical techniques leads to complex reports from which it is difficult to draw an overarching and unequivocal authenticity opinion. Thus arose two questions. (1) Is it acceptable to report an adverse interpretation without exhibiting all the supporting data? (2) How may a valid overarching authenticity opinion be derived from a large partially conflicting dataset?

Determination of Floral Origin Markers of Latvian Honey by Using IRMS, UHPLC-HRMS, and 1H-NMR

The economic significance of honey production is crucial; therefore, modern and efficient methods of authentication are needed. During the last decade, various data processing methods and a combination of several instrumental methods have been increasingly used in food analysis. In this study, the chemical composition of monofloral buckwheat (Fagopyrum esculentum), clover (Trifolium repens), heather (Calluna vulgaris), linden (Tilia cordata), rapeseed (Brassica napus), willow (Salix cinerea), and polyfloral honey samples of Latvian origin were investigated using several instrumental analysis methods. The data from light stable isotope ratio mass spectrometry (IRMS), ultra-high performance liquid chromatography coupled with high-resolution mass spectrometry (UHPLC-HRMS), and nuclear magnetic resonance (NMR) analysis methods were used in combination with multivariate analysis to characterize honey samples originating from Latvia. Results were processed using the principal component analysis (PCA) to study the potential possibilities of evaluating the differences between honey of different floral origins. The results indicate the possibility of strong differentiation of heather and buckwheat honeys, and minor differentiation of linden honey from polyfloral honey types. The main indicators include depleted δ¹⁵N values for heather honey protein, elevated concentration levels of rutin for buckwheat honey, and qualitative presence of specific biomarkers within NMR for linden honey.

Processing Technologies for Bee Products: An Overview of Recent Developments and Perspectives

Increased demand for a more balanced, healthy, and safe diet has accelerated studies on natural bee products (including honey, bee bread, bee collected pollen royal jelly, propolis, beeswax, and bee venom) over the past decade. Advanced food processing techniques, such as ultrasonication and microwave and infrared (IR) irradiation, either has gained popularity as alternatives or combined with conventional processing techniques for diverse applications in apiculture products at laboratory or industrial scale. The processing techniques used for each bee products have comprehensively summarized in this review, including drying (traditional drying, infrared drying, microwave-assisted traditional drying or vacuum drying, and low temperature high velocity-assisted fluidized bed drying), storage, extraction, isolation, and identification; the assessment methods related to the quality control of bee products are also fully mentioned. The different processing techniques applied in bee products aim to provide more healthy active ingredients largely and effectively. Furthermore, improved the product quality with a shorter processing time and reduced operational cost are achieved using conventional or emerging processing techniques. This review will increase the positive ratings of the combined new processing techniques according to the needs of the bee products. The importance of the models for process optimization on a large scale is also emphasized in the future.

Nuclear Magnetic Resonance Metabolomics with Double Pulsed-Field-Gradient Echo and Automatized Solvent Suppression Spectroscopy for Multivariate Data Matrix Applied in Novel Wine and Juice Discriminant Analysis

The quality of foods has led researchers to use various analytical methods to determine the amounts of principal food constituents; some of them are the NMR techniques with a multivariate statistical analysis (NMR-MSA). The present work introduces a set of NMR-MSA novelties. First, the use of a double pulsed-field-gradient echo (DPFGE) experiment with a refocusing band-selective uniform response pure-phase selective pulse for the selective excitation of a 5–10-ppm range of wine samples reveals novel broad ¹H resonances. Second, an NMR-MSA foodomics approach to discriminate between wine samples produced from the same Cabernet Sauvignon variety fermented with different yeast strains proposed for large-scale alcohol reductions. Third a comparative study between a nonsupervised Principal Component Analysis (PCA), supervised standard partial (PLS-DA), and sparse (sPLS-DA) least squares discriminant analysis, as well as orthogonal projections to a latent structures discriminant analysis (OPLS-DA), for obtaining holistic fingerprints. The MSA discriminated between different Cabernet Sauvignon fermentation schemes and juice varieties (apple, apricot, and orange) or juice authentications (puree, nectar, concentrated, and commercial juice fruit drinks). The new pulse sequence DPFGE demonstrated an enhanced sensitivity in the aromatic zone of wine samples, allowing a better application of different unsupervised and supervised multivariate statistical analysis approaches.

A review on the application of spectroscopy to the condiments detection: from safety to authenticity

Condiments are the magical ingredients that make the food present a richer taste. In recent years, due to the increasing consciousness of food safety and human health, much progress has been made in developing rapid and nondestructive techniques for the evaluation of food condiments safety, authentication, and traceability. The potential of spectroscopy techniques, such as near-infrared (NIR), mid-infrared (MIR), Raman, fluorescence, inductively coupled plasma (ICP), and hyperspectral imaging techniques, has been widely enhanced by numerous applications in this field because of their advantages over other analytical techniques. Following a brief introduction of condiment and safety basics, this review mainly focuses on recent vibrational and atomic spectral applications for condiment nondestructive analysis and evaluation, including (1) chemical hazards detection; (2) microbiological hazards detection; and (3) authenticity concerns. The review shows current spectroscopies to be effective tools that will play indispensable roles for food condiment evaluation. In addition, online/real-time applications of these techniques promise to be a huge growth field in the near future.

Honey authenticity: analytical techniques, state of the art and challenges

Honey is a high-value, globally consumed, food product featuring a high market price strictly related to its origin. Moreover, honey origin has to be clearly stated on the label, and quality schemes are prescribed based on its geographical and botanical origin. Therefore, to enhance food quality, it is of utmost importance to develop analytical methods able to accurately and precisely discriminate honey origin. In this study, an all-time scientometric evaluation of the field is provided for the first time using a structured keyword on the Scopus database. The bibliometric analysis pinpoints that the botanical origin discrimination was the most studied authenticity issue, and chromatographic methods were the most frequently used for its assessment. Based on these results, we comprehensively reviewed analytical techniques that have been used in honey authenticity studies. Analytical breakthroughs and bottlenecks on methodologies to assess honey quality parameters using separation, bioanalytical, spectroscopic, elemental and isotopic techniques are presented. Emphasis is given to authenticity markers, and the necessity to apply chemometric tools to reveal them. Altogether, honey authenticity is an ever-growing field, and more advances are expected that will further secure honey quality.

Comparative NMR Metabolomics Profiling between Mexican Ancestral & Artisanal Mezcals and Industrialized Wines to Discriminate Geographical Origins, Agave Species or Grape Varieties and Manufacturing Processes as a Function of Their Quality Attributes

The oenological industry has benefited from the use of Nuclear Magnetic Resonance (¹H-NMR) spectroscopy in combination with Multivariate Statistical Analysis (MSA) as a foodomics tool for retrieving discriminant features related to geographical origins, grape varieties, and further quality controls. Said omics methods have gained such attention that Intergovernmental Organizations and Control Agencies are currently recommending their massive use amongst countries as quality compliances for tracking standard and degradation parameters, fermentation products, polyphenols, amino acids, geographical origins, appellations d’origine contrôlée and type of monovarietal strains in wines. This study presents, for the first time, a ¹H-NMR/MSA profiling of industrial Mexican wines, finding excellent statistical features to discriminate between oenological regions and grape varieties with supervised Orthogonal Projections to Latent Structures Discriminant Analysis (OPLS-DA). In a comparative way, it is applied with the ¹H-NMR/OPLS-DA workflow for the first time in ancestral and artisanal Mexican mezcals with promising results to discriminate between regions, agave species and manufacturing processes. The central aim of this comparative study is to extrapolate the know-how of wine-omics into the non-professionalized mezcal industry for establishing the NMR acquisition, preprocessing and statistical analysis basis to implement novel, non-invasive and highly reproducible regional, agave species and manufacturing-quality controls.

Classification of the botanical and geographical origins of Chinese honey based on 1H NMR profile with chemometrics

In this paper, we report a newly developed non-target ¹H NMR detection associated with chemometrics method to classify the botanical and geographical origins of the monofloral Chinese honey. ¹H NMR tests of 218 monofloral honey samples of 8 classes (Acacia, Jujube, Linden, Longan, Orange, Rape, Sunflower, Vitex) collected in 2017-2019 across China were conducted under the optimal sample preparation conditions and NMR acquisition parameters. The whole profiles of NMR spectra instead of individual or partial signals from specific components were processed and extracted, then fed to SIMCA-P to classify the botanical and geographical origins through non-target statistical analysis. For the botanical origins, most of them could be classified clearly according to Principal Component Analysis (PCA) with both R² and Q² close to 1. Orthogonal Partial Least Squares Discrimination Analysis (OPLS-DA) model could classify the honey floral types successfully with R²Y and Q² greater than 0.85. It is found that the integral bin for data extraction has no obvious influence on the classification. For the geographical origins, the classification at different geographical levels (providence and town) could be successfully distinguished by OPLS-DA model. The promising preliminary results with the geographical classification at 40 km level unambiguously demonstrate the application of this NMR-based multi-species non-targeted method for the honey authenticity. Successful result is obtained on a pilot prediction of the geographical classification. Comparing with the methods based on other techniques, the advantages of this reported one are less sample amount needed, simple preparation, short test time, and non-targeted multi-species detection.

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.

The Changes of Flavonoids in Honey during Storage

The purpose of this study was to determine the changes in the contents of flavonoids that were the most prevalent in acacia and multifloral honey during one year of storage. Samples were stored in transparent glass containers, at room temperature, on open shelves exposed to light during daytime. Eight individual flavonoids identified and quantified using HPLC-Diode Array Detector (DAD) belongs to three subgroups: flavonols (quercetin, luteolin, kaempferol and galangin), total flavanons (hesperetin and pinocembrin) and total flavones (apigenin and chrysin). Obtained results revealed that multifloral honey had more total flavonoids than acacia samples did. On average from all of the samples, multifloral honey had more of quercetin, hesperetin, luteolin, kaempferol and apigenin than acacia honey did. Content of flavonoids increased in samples between the 1st and 6th month of storage and then started to decrease until the 9th month, when they remained relatively constant all the way until the 12th month of storage. In conclusion, acacia and multifloral honey after one-year of storage still can be a valuable source of flavonoids.

Methods for determining the botanical origin of honey

The demand for monofloral, original, and special (functional) kinds of honey, or those with geographical indication, is forecast. At the same time, there is a need to improve the methods for determining the botanical and geographical origin of honey. The purpose of the research was to select and apply a variety of techniques for identifying the botanical origin of honey for its correspondence to acacia species. Samples of honey from the Kyiv, Odesa, and Dnipro regions extracted in the spring and summer period were used in the research. Organoleptic, physicochemical, NMR spectrometry, and advanced melissopalynology methods were applied. The tests were carried out at the laboratories of the Department of Certification and Standardization of Agricultural Products, NULES, Ukraine; the Ukrainian Laboratory of Quality and Safety of Agricultural Products; and the Bruker BioSpin GmbH company (Germany). According to the research results, the requirements for acacia honey were met by the organoleptic method for samples B1 and B2; by the physicochemical method for A0 and A2; by NMR spectroscopy for not a single sample, all being assessed as polyfloral; and by pollen analysis for B1 and B2. The conducted studies confirm the need for a comprehensive approach to the identification of the botanical origin of honey for its conformity to acacia species. There is a need to review the physicochemical indicators for the compliance of honey with the acacia species obtained in Ukraine. After all, even the modern NMR spectrometry technique indicated that the specially fabricated sample that did not contain acacia pollen grains was acacia honey. Identification of the botanical origin of monofloral honey, in particular acacia, should be carried out in the following sequence: pollen analysis (by dominant pollen grains), safety (presence of antibiotics, pesticides), physicochemical parameters according to international requirements, organoleptic parameters.

Evaluation of Egyptian honeys and their floral origins: phenolic compounds, antioxidant activities, and antimicrobial characteristics

This study reports the physicochemical characterization of clover (Trifolium hybridum) and citrus (Citrus sinensis) honeys produced in Fayoum, Egypt, by evaluating the analysis of moisture content, pH, total soluble solids (TSS), electric conductivity (EC), total sugars, crude protein, ash content, total acidity, hydroxymethylfurfural (HMF), and total phenolic compounds (TPC). Antioxidant and antimicrobial activities of honey extracts and their flower extracts were determined. The results clearly indicated that ethanol gave the highest extraction yield of both clover and citrus flowers, while ethyl acetate showed the highest extraction recovery for the phenolic compounds, with TPC amounting to 338.5 and 536.4 mg gallic acid equivalent kg^-1 fresh weight in clover and citrus flower extracts, respectively. Honey samples have less TPC than their flowers. The results showed that the TPC of citrus honey and its flowers was higher than clover honey and its flowers, respectively. Antioxidant activity was higher in extracts obtained from citrus flower than extracts of clover flower. The same trend was noticed for honey samples. Both clover and citrus honeys showed antimicrobial effects against tested microorganisms. HPLC analysis showed that p-coumaric acid was the main phenolic component in ethanol extracts of clover and citrus honeys, contributing about 83.0% and 52.2%, respectively. In citrus and clover flower extracts, syringic acid and quercetin were the main phenolics, respectively. It would be expected that characteristics of honey samples are mainly depended on the floral origin of nectar foraged by bees.

Food authentication in real life: How to link nontargeted approaches with routine analytics?

In times of increasing globalization and the resulting complexity of trade flows, securing food quality is an increasing challenge. The development of analytical methods for checking the integrity and, thus, the safety of food is one of the central questions for actors from science, politics, and industry. Targeted methods, for the detection of a few selected analytes, still play the most important role in routine analysis. In the past 5 years, nontargeted methods that do not aim at individual analytes but on analyte profiles that are as comprehensive as possible have increasingly come into focus. Instead of investigating individual chemical structures, data patterns are collected, evaluated and, depending on the problem, fed into databases that can be used for further nontargeted approaches. Alternatively, individual markers can be extracted and transferred to targeted methods. Such an approach requires (i) the availability of authentic reference material, (ii) the corresponding high-resolution laboratory infrastructure, and (iii) extensive expertise in processing and storing very large amounts of data. Probably due to the requirements mentioned above, only a few methods have really established themselves in routine analysis. This review article focuses on the establishment of nontargeted methods in routine laboratories. Challenges are summarized and possible solutions are presented.