Geographical and Botanical Origin Discrimination of Romanian Honey Using Complex Stable Isotope Data and Chemometrics

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.

A review of recent compound-specific isotope analysis studies applied to food authentication

Compound-specific stable isotope analysis (CSIA) of food products is a relatively new and novel technique used to authenticate food and detect adulteration. This paper provides a review of recent on-line and off-line CSIA applications of plant and animal origin foods, essential oils and plant extracts. Different food discrimination techniques, applications, scope, and recent studies are discussed. CSIA δ13C values are widely used to verify geographical origin, organic production, and adulteration. The δ15N values of individual amino acids and nitrate fertilizers have proven effective to authenticate organic foods, while δ2H and δ18O values are useful to link food products with local precipitation for geographical origin verification. Most CSIA techniques focus on fatty acids, amino acids, monosaccharides, disaccharides, organic acids, and volatile compounds enabling more selective and detailed origin and authentication information than bulk isotope analyses.. In conclusion, CSIA has a stronger analytical advantage for the authentication of food compared to bulk stable isotope analysis, especially for honey, beverages, essential oils, and processed foods.

A non-targeted metabolomic strategy for characterization of the botanical origin of honey samples using headspace gas chromatography-ion mobility spectrometry

In this work, characterization of the botanical origin of honey was carried out using headspace gas chromatography coupled to ion mobility spectrometry (HS-GC-IMS). The proposed methodology was applied for the analysis of 89 samples from ten different botanical origins. A total of 15 volatile compounds could be identified, namely, 3-methyl-1-butanol, heptanal, valeraldehyde, octanal, trans-2-hexenal, nonanal, hexanal, benzaldehyde, 2-heptanone, 2-butanone, 2-hexanone, 6-methyl-5-hepten-2-one, 2-pentanone, ethyl acetate and linalool. The analytical method was characterized in terms of limits of detection and quantification, and precision, in order to quantify the identified compounds. Compounds were quantified using the sum of the protonated monomer and proton-bound dimer and logarithmic regression (R² > 0.98), although the establishment of a concentration threshold that would allow creation of classification rules was not possible since there was variability within the group. Consequently, the establishment of chemometric models was necessary. A non-targeted strategy using 275 features is proposed. Orthogonal partial least squares-discriminant analysis (OPLS-DA) allowed the differentiation of five botanical origins: thousand flowers, rosemary, albaida, orange blossom, and "others" (rest of the investigated botanical origins, since a limited number of samples was available). A success validation rate of 100% allowed the classification of 14 honeys with unknown botanical origin.

Stable isotope ratio analysis of carbon to distinguish sialic acid from freshly stewed bird's nest products

Freshly stewed bird's nest products are easily adulterated with exogenous synthetic sialic acid to enhance the grade of the products and sell at high prices. This paper identifies the carbon stable isotope characteristics of sialic acid from natural and commercially synthetic sources using stable isotope ratio mass spectrometry (IRMS). Specifically, an off-line pretreatment technique combined with on-line LC-IRMS was developed to accurately determine δ¹³C values of sialic acid in a freshly stewed bird's nest. This method has no obvious isotope fractionation and good reproducibility. EA-IRMS was used to determine the δ¹³C values of commercial sialic acid. The results showed that the δ¹³C values of sialic acid from natural and synthetic sources were -29.90% ± 0.42% and -16.26% ± 3.91%, respectively, with distinct carbon stable isotope distribution characteristics. By defining a δ¹³C threshold value of -28.54% for natural SA, additional commercial SA from a minimum of 10% can be identified. Therefore, δ¹³C was proposed as a suitable tool for verifying the authenticity of fresh stewed bird's nests on the market.

Probabilistic Machine Learning for the Authentication of the Protected Designation of Origin of Greek Bottarga from Messolongi: A Generic Methodology to Cope with Very Small Number of Samples

Consumers are increasingly interested in the geographical origin of foodstuff, as an important characteristic of food authenticity and quality. To assure the authenticity of the geographical origin, various methods have been proposed. Stable isotope analysis is a method that has been extensively used for products like wine, oil, and meat by using large datasets and analysis. On the other hand, only few studies have been conducted for the discrimination of seafood origin and especially for mullet roes or bottarga products, and even fewer investigate a small number of samples and datasets. Stable isotopes of Carbon (C), Nitrogen (N), and Sulfur (S) analysis of bottarga samples from four different origins were carried out. The first results show that the stable isotopes ratios of C, N, and S could be used to discriminate the Greek PDO Bottarga (Messolongi) from other similar products by using a probabilistic machine learning methodology. That could use limited sample data to fit/estimate their parameters, while, at the same time, being capable of describing accurately the population and discriminate individual samples regarding their origin.

Activity concentrations of 238U, 232Th, 226Ra 137Cs and 40K radionuclides in honey samples from Romania. Lifetime cancer risk estimated

Romania is on the first place in Europe with an annual production of honey of 30.9 thousand tons in 2018, while the European Union is on the second place in the world with a total of 283 thousand tons. The most part of the honey production from Romania is exported. The aim of this study was to estimate internal radiation doses and lifetime cancer risk from honey ingestion sampled from several locations on the Romanian territory. The activity concentration of ¹³⁷Cs and ²³⁸U is found to be below the detection limit of the method. The activity of ²²⁶Ra ranged from lower than the minimum detectable value (<1.08 Bq·kg^-1) to 7.35 ± 1.73 Bq·kg^-1. For ²³²Th and ⁴⁰K the average recorded values were 1.51 ± 0.74 and 24.08 ± 4.37 Bq·kg^-1, respectively. The annual effective dose due to the intake of ²³²Th, ²²⁶Ra, ⁴⁰K has been assessed ranging from 0.08 to 0.47 (μSv·y^-1), 0.35 to 1.65 (μSv·y^-1) and 0.04 to 0.33 (μSv·y^-1), respectively. ²⁶Ra gives the largest contribution (56-82%) to the total annual effective dose due to ingestion received by consumption of honey, in the samples where it was identified. In the other samples (where ²²⁶Ra was below the detection limit), the largest contribution to annual effective dose is due to ²³²Th (45-85%). The values obtained from the lifetime cancer risk calculation range in the domain from 2.85·10^-7 to 1.78·10^-6 for ²³²Th, 1.33·10^-6 to 6.22·10^-6 for ²²⁶Ra and 1.38·10^-7 to 1.25·10^-6 for ⁴⁰K. For ¹³⁷Cs, only one value was recorded 2.20·10^-8. The ²³²Th, ²²⁶Ra, ⁴⁰K and ¹³⁷Cs activities measured in the present work were comparable with completion of others activated values of honey samples around Europe.

Application of Visible/Infrared Spectroscopy and Hyperspectral Imaging With Machine Learning Techniques for Identifying Food Varieties and Geographical Origins

Food quality and safety are strongly related to human health. Food quality varies with variety and geographical origin, and food fraud is becoming a threat to domestic and global markets. Visible/infrared spectroscopy and hyperspectral imaging techniques, as rapid and non-destructive analytical methods, have been widely utilized to trace food varieties and geographical origins. In this review, we outline recent research progress on identifying food varieties and geographical origins using visible/infrared spectroscopy and hyperspectral imaging with the help of machine learning techniques. The applications of visible, near-infrared, and mid-infrared spectroscopy as well as hyperspectral imaging techniques on crop food, beverage, fruits, nuts, meat, oil, and some other kinds of food are reviewed. Furthermore, existing challenges and prospects are discussed. In general, the existing machine learning techniques contribute to satisfactory classification results. Follow-up researches of food varieties and geographical origins traceability and development of real-time detection equipment are still in demand.

Honey Phenolic Compound Profiling and Authenticity Assessment Using HRMS Targeted and Untargeted Metabolomics

Honey consumption is attributed to potentially advantageous effects on human health due to its antioxidant capacity as well as anti-inflammatory and antimicrobial activity, which are mainly related to phenolic compound content. Phenolic compounds are secondary metabolites of plants, and their content in honey is primarily affected by the botanical and geographical origin. In this study, a high-resolution mass spectrometry (HRMS) method was applied to determine the phenolic profile of various honey matrices and investigate authenticity markers. A fruitful sample set was collected, including honey from 10 different botanical sources (n = 51) originating from Greece and Poland. Generic liquid-liquid extraction using ethyl acetate as the extractant was used to apply targeted and non-targeted workflows simultaneously. The method was fully validated according to the Eurachem guidelines, and it demonstrated high accuracy, precision, and sensitivity resulting in the detection of 11 target analytes in the samples. Suspect screening identified 16 bioactive compounds in at least one sample, with abscisic acid isomers being the most abundant in arbutus honey. Importantly, 10 markers related to honey geographical origin were revealed through non-targeted screening and the application of advanced chemometric tools. In conclusion, authenticity markers and discrimination patterns were emerged using targeted and non-targeted workflows, indicating the impact of this study on food authenticity and metabolomic fields.

SPME-GC-MS and FTIR-ATR Spectroscopic Study as a Tool for Unifloral Common Greek Honeys’ Botanical Origin Identification

Among the variants of Greek honey, the most commonly available are pine, fir, thyme, and citrus honey. Samples of the above kinds of honey, identified according to European and Greek legislation, were studied using gas chromatography coupled with mass spectrometry (GC-MS) and the attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopic techniques. Two chemometric models were developed based on statistically significant volatile compounds (octane; 2-phenylacetaldehyde; 1-nonanol; methyl 2-hydroxybenzoate; 2-(4-methylcyclohex-3-en-1-yl); nonanoic acid) and the 1390–945 and 847–803 cm−1 spectral regions, mainly vibrations of fructose and glucose, combined with the stepwise linear discriminant analysis (stepwise LDA) statistical technique. In total, 85.5% of standard samples, and 82.3% through internal validation and 88.5% through external validation, were identified correctly using the GC-MS-stepwise-LDA chemometric model. The corresponding results for the ATR-FTIR-stepwise-LDA chemometric model were 93.5%, 82.5%, and 84.6%. The double validation (internal, external) enhances the robustness of the proposed chemometric models. The developed models are considered statistically equivalent, but FTIR spectroscopy is simple, rapid, and more economical.

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.

Achieving Food Authenticity and Traceability Using an Analytical Method Focusing on Stable Isotope Analysis

High-value agricultural products are characterized by the geographical conditions of the production areas such as climatic and soil conditions. These products are protected by the geographical indication (GI) protection system, which has been introduced in more than 100 countries. Because GI products are expensive in the market, products are often mislabeled as GI. Thus, there is an urgent need for the development of analytical methods that enable the tracing of geographical origins of food materials. Stable isotope analysis is used to trace the geographical origin of food materials. In this study, we review the applications for tracing the geographical origin of agricultural products (especially rice, beef, and honey) focusing on an analytical method for analyzing stable isotopes (δD, δ13C, δ15N, δ18O, and δ34S).

Classification of Unifloral Honeys from SARDINIA (Italy) by ATR-FTIR Spectroscopy and Random Forest

Nowadays, the mislabeling of honey floral origin is a very common fraudulent practice. The scientific community is intensifying its efforts to provide the bodies responsible for controlling the authenticity of honey with fast and reliable analytical protocols. In this study, the classification of various monofloral honeys from Sardinia, Italy, was attempted by means of ATR-FTIR spectroscopy and random forest. Four different floral origins were considered: strawberry-tree (Arbutus Unedo L.), asphodel (Asphodelus microcarpus), thistle (Galactites tormentosa), and eucalyptus (Eucalyptus calmadulensis). Training a random forest on the infrared spectra allowed achieving an average accuracy of 87% in a cross-validation setting. The identification of the significant wavenumbers revealed the important role played by the region 1540-1175 cm-1 and, to a lesser extent, the region 1700-1600 cm-1. The contribution of the phenolic fraction was identified as the main responsible for this observation.

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.

Applications of emerging stable isotopes and elemental markers for geographical and varietal recognition of Romanian and French honeys

The research towards the identification of new authenticity markers is crucial to fight against fraudulent activities on honey, one of the top ten most falsified food commodities. This work proposes an association of stable isotopes and elemental content as markers for honey authentication, with respect to its floral and geographical origin. Emerging markers like isotopic signature of honey water alongside with carbon and hydrogen isotopic ratios of ethanol obtained from honey fermentation and Rare Earth Elements, were used to develop new recognition models. Thus, the efficiency of the discrimination potential of these emerging markers was discussed individually and in association. This approach proved its effectiveness for geographical differentiation (>98%) and the role of the emerging markers in these classifications was an essential one, especially of: (D/H)_I, δ²H, δ¹⁸O, La, Ce and Pr. Floral recognition was realized in a lower percentage revealing the suitability of these markers mainly for geographical classification.

Multielemental characterization of honey using inductively coupled plasma mass spectrometry fused with chemometrics

Honey is considered a desirable ingredient in a range of different foodstuffs because of its nutrient and therapeutic effect. The honey characteristics mainly depend on the type of vegetation visited by the bees and the climatic conditions in which the plants are growing. Therefore, the purity, floral and geographical origin and authenticity are important factors influencing the overall perception of honey and honey-based products in terms of quality and price. An important parameter in this picture is the elemental composition of honey because it can be linked with the floral type of honey, floral plant density and the botanical origin of nectar and pollens. In this work, the concentration range variation of 18 elements (Al, As, Ba, Ca, Cd, Co, Cr, Cu, Mg, Mn, Na, Ni, K, Pb, Sr, Ti, V and Zn) was investigated in four varieties of honey (linden, acacia, rape, and sunflower) originating from Romania, because the elemental profile of honey may give important information to differentiate its geographical and varietal origin for authenticity purpose. All the determinations were carried out by inductively coupled plasma quadrupole mass spectrometry (ICP-Q-MS). The most abundant minerals decreased in the following order: K > Ca > Mg > Na, having the mean values of 248.70, 59.97, 20.54 and 11.92 mg kg^-1 , respectively. The mineral content marks the differences in honey samples from different botanical origin and can be used as a tool for authentication purposes and also extends its applicability to assess the traceability of honey. Analysis of variance showed the preliminary relationships between the elements and samples. Further, the discrimination between different studied honey samples was achieved by principal component analysis (PCA). The multivariate analysis of the data allowed us to separate the honey samples into distinct groups according to their macroelement and microelement composition, emphasizing the origin of variation of element concentrations by honey type. Therefore, this approach might be potentially useful for the control of honey quality, origin or authenticity, and even to use the honey as environmental tracer.

Raspberry, Rape, Thyme, Sunflower and Mint Honeys Authentication Using Voltammetric Tongue

The aim of this study was to authenticate five types of Romanian honey (raspberry, rape, thyme, sunflower and mint) using a voltammetric tongue (VE tongue) technique. For the electronic tongue system, six electrodes (silver, gold, platinum, glass, zinc oxide and titanium dioxide) were used. The results of the melissopalynological analysis were supplemented by the data obtained with the electronic voltammetric tongue system. The results were interpreted by means of principal component analysis (PCA) and linear discriminant analysis (LDA). In this way, the usefulness of the working electrodes was compared for determining the botanical origin of the honey samples. The electrodes of titanium dioxide, zinc oxide, and silver were more useful, as the results obtained with these electrodes showed that it was achieved a better classification of honey according to its botanical origin. The comparison of the results of the electronic voltammetric tongue technique with those obtained by melissopalynological analysis showed that the technique was able to accurately classify 92.7% of the original grouped cases. The similarity of results confirmed the ability of the electronic voltammetric tongue technique to perform a rapid characterization of honey samples, which complements its advantages of being an easy-to-use and cheap method of analysis.

Fast Classification of Geographical Origins of Honey Based on Laser-Induced Breakdown Spectroscopy and Multivariate Analysis

Traceability of honey is highly required by consumers and food administration with the consideration of food safety and quality. In this study, a technique named laser-induced breakdown spectroscopy (LIBS) was used to fast trace geographical origins of acacia honey and multi-floral honey. LIBS emissions from elements of Mg, Ca, Na, and K had significant differences among different geographical origins. The clusters of honey from different geographical origins were visualized with principal component analysis. In addition, support vector machine (SVM) and linear discrimination analysis (LDA) were used to quantitively classify the origins. The results indicated that SVM performed better than LDA, and the discriminant results of multi-floral honey were better than acacia honey. The accuracy and mean average precision for multi-floral honey were 99.7% and 99.7%, respectively. This study provided a fast approach for geographical origin classification, and might be helpful for food traceability.

Linking growing conditions to stable isotope ratios and elemental compositions of Costa Rican bananas (Musa spp.)

Traceability of agricultural produce is getting increasingly important for numerous reasons including marketing, certification, and food safety. Globally, banana (Musa spp.) with its high nutritional value and easy accessibility, is a popular fruit among consumers. Bananas are produced throughout the (sub-)tropics under a wide range of environmental conditions. Environmental conditions could influence the composition of bananas. Understanding the effect of these conditions on fruit composition provides a way of increasing the fruit's traceability and linking it to its origin - a crucial aspect for the increasing global supply chain. In this study, we examined the influence of growing conditions on the isotopic and elemental composition of bananas produced in 15 Costa Rican farms. A total of 88 bananas (peel and pulp) were collected from the farms and analysed for isotopic signatures (δ¹³C, δ¹⁵N, and δ¹⁸O) and elemental compositions. The growing conditions were characterized in terms of climate, topography and soil conditions. The isotopic ratios differed significantly between groups of farms. The δ¹³C and δ¹⁵N values were mainly influenced by soil types, while rainfall and temperatures related more to the δ¹⁸O values. The elemental compositions of the bananas were primarily influenced by the local rainfall and soil types, while the geographical origin could be distinguished using principal component analysis. The overall results link the growing conditions to the isotopic and elemental compositions of bananas, thereby also providing a way to trace its origin.

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.

Volatile Profile and Physico-Chemical Analysis of Acacia Honey for Geographical Origin and Nutritional Value Determination

Honey composition and color depend greatly on the botanical and geographical origin. Water content, water activity and color of 50 declared acacia samples, collected from three different geographical zones of Romania, together with chromatographic determination of sugar spectrum were analyzed. A number of 79 volatile compounds from the classes of: Alcohols, aldehydes, esters, ketones, sulphur compounds, aliphatic hydrocarbons, nitrogen compounds, carboxylic acids, aromatic acids and ethers were identified by solid-phase micro-extraction and gas-chromatography mass spectrometry. The overall volatile profile and sugar spectrum of the investigated honey samples allow the differentiation of geographical origin for the acacia honey samples subjected to analysis. The statistical models of the chromatic determination, physicochemical parameters and volatile profile was optimal to characterize the honey samples and group them into three geographical origins, even they belong to the same botanical origin.

Stable carbon isotope ratios for organic acids in commercial honey samples

Stable carbon isotope ratios (δ¹³C) for glucose, fructose, disaccharides, trisaccharides, and organic acids in 116 commercial honey samples were measured by LC/IRMS. On the basis of EA/IRMS and LC/IRMS authenticity criteria, 39 of the samples were judged to have been adulterated. The δ¹³C values for organic acids from pure honey, reported here for the first time, ranged from -33.6 to -26.5‰. The mean Δδ¹³C (glucose-organic acids) value was +3.7 ± 0.9‰. Glucose and organic acid δ¹³C values were strongly correlated (R = 0.71, P < 0.001). Gluconic acid, the predominant organic acid in honey, has been reported to be produced via decomposition of glucose by bee glucose-oxidase and certain Gluconobacter spp. This fact was confirmed by isotope analysis.

Emerging approach for analytical characterization and geographical classification of Moroccan and French honeys by means of a voltammetric electronic tongue

Moroccan and French honeys from different geographical areas were classified and characterized by applying a voltammetric electronic tongue (VE-tongue) coupled to analytical methods. The studied parameters include color intensity, free lactonic and total acidity, proteins, phenols, hydroxymethylfurfural content (HMF), sucrose, reducing and total sugars. The geographical classification of different honeys was developed through three-pattern recognition techniques: principal component analysis (PCA), support vector machines (SVMs) and hierarchical cluster analysis (HCA). Honey characterization was achieved by partial least squares modeling (PLS). All the PLS models developed were able to accurately estimate the correct values of the parameters analyzed using as input the voltammetric experimental data (i.e. r>0.9). This confirms the potential ability of the VE-tongue for performing a rapid characterization of honeys via PLS in which an uncomplicated, cost-effective sample preparation process that does not require the use of additional chemicals is implemented.

Classification of red wines using suitable markers coupled with multivariate statistic analysis

Methodologies for chemometric classification of five authentic red wine varieties from Murfatlar wine center, Romania, young and aged are reported. The discriminant analysis based on several anthocyanins, organic acids, (13)C/(12)C, (18)O/(16)O and D/H isotopic ratios, (1)H and (13)C NMR fingerprints revealed a very satisfactory categorization of the wines, both in terms of variety and vintage, thus illustrating the validity of selected variables for wine authentication purposes. LDA applied to the combined data shows 85.7% classification of wines according to grape variety and 71.1% classification of wines according to vintage year, including a control wine set for each categorization, thus allowing an accurate interpretation of the data. Thereby, anthocyanins, certain anthocyanin ratios, oxalic, shikimic, lactic, citric and succinic acids, sugars like glucose, amino acids like histidine, leucine, isoleucine and alanine, and also 2,3-butanediol, methanol, glycerol and isotopic variables were significant for classification of wines.

Recent developments in honey characterization

Advanced analytical techniques in honey characterization.