Wine varietal authentication based on phenolics, volatiles and DNA markers: State of the art, perspectives and drawbacks

Elemental profile of wheat in the las vegas market: Geographic origin discrimination and probabilistic health risk assessment

This study investigates concentrations of toxic and potentially toxic elements (PTEs) in organic and conventional wheat flour and grains marketed in Las Vegas. Geographic origins of the samples were evaluated using Linear Discriminant Analysis (LDA). Monte Carlo Simulation technique was also employed to evaluate non-carcinogenic risk in four life stages. Concentrations of Al, As, Cd, Co, Cr, Cu, Fe, Mn, Mo, Ni, Pb, Se, Sr, and Zn were determined using inductively coupled plasma mass spectrometry (ICP-MS) following hot block-assisted digestion. Obtained results showed non-significant differences in contents of toxic and PTEs between conventional and organic wheat grains/flour. Using LDA, metal (loid)s were found to be indicative of geographical origin. The LDA produced a total correct classification rate of 95.8% and 100% for US and West Pacific Region samples, respectively. The results of the present study indicate that the estimated non-carcinogenic risk associated with toxic element intakes across the four life stages were far lower than the threshold value (Target Hazard Quotient (THQ) > 1). However, the probability of exceeding the threshold value for Mn is approximately 32% in children aged between 5 and 8 years. The findings of this study can aid in understanding dietary Mn exposure in children in Las Vegas.

Convergent technologies to tackle challenges of modern food authentication

The authentication process involves all the supply chain stakeholders, and it is also adopted to verify food quality and safety. Food authentication tools are an essential part of traceability systems as they provide information on the credibility of origin, species/variety identity, geographical provenance, production entity. Moreover, these systems are useful to evaluate the effect of transformation processes, conservation strategies and the reliability of packaging and distribution flows on food quality and safety. In this manuscript, we identified the innovative characteristics of food authentication systems to respond to market challenges, such as the simplification, the high sensitivity, and the non-destructive ability during authentication procedures. We also discussed the potential of the current identification systems based on molecular markers (chemical, biochemical, genetic) and the effectiveness of new technologies with reference to the miniaturized systems offered by nanotechnologies, and computer vision systems linked to artificial intelligence processes. This overview emphasizes the importance of convergent technologies in food authentication, to support molecular markers with the technological innovation offered by emerging technologies derived from biotechnologies and informatics. The potential of these strategies was evaluated on real examples of high-value food products. Technological innovation can therefore strengthen the system of molecular markers to meet the current market needs; however, food production processes are in profound evolution. The food 3D-printing and the introduction of new raw materials open new challenges for food authentication and this will require both an update of the current regulatory framework, as well as the development and adoption of new analytical systems.

Authenticity Markers of Aged Red Wines from Aglianico, Uva di Troia, Negroamaro and Primitivo Grapes

The wide ampelographic treasure of Italian wine grape varieties is driving research towards suitable approaches for the varietal authenticity control of wine. In this paper, Aglianico, Negroamaro, Primitivo and Uva di Troia red wines, which were produced experimentally by single-grape winemaking from non-aromatic grapes native to southern Italy, were analyzed with respect to berry markers, namely anthocyanins, hydroxycinnamic acids (HPLC-DAD), shikimic acid (HPLC-UV) and glycosidic aroma precursors (GC-MS). The study confirms that, just as for the berries, useful varietal authenticity markers for red wine, even after aging, turn out to be hydroxycinnamic acids, relative amounts of acylated forms of anthocyanins, and shikimic acid, together with some grape glycosidic precursors from terpenes and C13- norisoprenoids. Principal Component Analysis was used as a valuable tool to highlight the results.

Metal(loid)s Profile of Four Traditional Ethiopian Teff Brands: Geographic Origin Discrimination

Among the most renowned Ethiopian food crops, teff (Eragrostis tef (Zucc.)Trotter) is the most nutritious and gluten-free cereal. Because of the increase in demand for teff, it is necessary to establish geographic origin authentication of traditional teff brands based on multi-element fingerprint. For this purpose, a total of 60 teff samples were analysed using Inductively Coupled Plasma Mass Spectrometry (ICP-MS). Accuracy of the laboratory procedure was verified by the analysis of rice flour standard reference material (NIST SRM 1568b). In this context, four traditional teff brands (Ada'a, Ginchi, Gojam and Tulu Bolo) were analytically characterized using multi-element fingerprint and further treated statistically using linear discriminant analysis (LDA). Due to obvious extrinsic Fe, Al and V contamination, these elements were excluded from the discriminant model. Five elements (Cu, Mo, Se, Sr, and Zn) significantly contributed to discriminate the geographical origin of white teff. On the other hand, Mn, Mo, Se and Sr were used as discriminant variables for brown teff. LDA revealed 90 and 100% correct classifications for white and brown teff, respectively. Overall, multi-element fingerprint coupled with LDA can be considered a suitable tool for geographic origin discrimination of traditional teff brands.

TaqMan® and HRM approaches for SNP genotyping in genetic traceability of musts and wines

The fight against fraud in the wine sector requires continuous improvements and validations of new technologies applicable to musts and wines. Starting from published data from the Vitis18kSNP array, a series of new specific single nucleotide polymorphism (SNP) markers have been identified for some important north-western Italian cultivars, such as Barbera, Dolcetto and Arneis (Vitis vinifera L.), used in the production of high-quality wines under Protected Denomination of Origin. A pair of new SNP markers for each grape variety were selected and validated using two real-time PCR techniques: TaqMan® genotyping assays and high-resolution melting analysis (HRM). The TaqMan® assay has proven to be more reliable and repeatable than HRM analysis because despite being an economical and versatile technique for the detection of different types of genomic mutations (SNPs, insertions or deletions), HRM has shown limitations in the presence of poor-quality DNA extracted from musts and wines. TaqMan® assays have successfully identified Barbera, Dolcetto and Arneis in their respective musts and experimental wines, and with good efficiency in commercial wines. Marked differences between genotypes were observed, varietal identification in Dolcetto-based musts/wines was more efficient than that in Arneis-based wines. Therefore, the TaqMan® assay has considerable potential for varietal identification in wines and the procedure described in the present work can be easily adapted to all wines with adequate setup of DNA extraction methods that should be adapted to different wines.

Contribution of Starmerella bacillaris and Oak Chips to Trebbiano d'Abruzzo Wine Volatile and Sensory Diversity

In this study, six fermentation trials were carried out: co-inoculation and sequential inoculation of Saccharomyces cerevisiae and Starmerella bacillaris in the presence and absence of oak chips. Moreover, Starm. bacillaris strain was attached to the oak chips and co-inoculated or sequentially inoculated with S. cerevisiae. Wines fermented with Starm. bacillaris adhered to oak chips showed a higher concentration of glycerol (more than 6 g/L) than the others (about 5 g/L). These wines also showed a higher content of polyphenols (more than 300 g/L) than the others (about 200 g/L). The addition of oak chips induced an increase of yellow color (b* value of about 3). Oak-treated wines were characterized by a higher concentration of higher alcohols, esters and terpenes. Aldehydes, phenols and lactones were detected only in these wines, independently from the inoculation strategy. Significant differences (p < 0.05) were also observed in the sensory profiles. The fruity, toasty, astringency, and vanilla sensations were perceived as more intense in wines treated with oak chips. The white flower descriptor showed a higher score in wines fermented without chips. Oak surface-adhered Starm. bacillaris cells could be a good strategy to improve the volatile and sensory profile of Trebbiano d'Abruzzo wines.

Integrated Approach from Sample-to-Answer for Grapevine Varietal Identification on a Portable Graphene Sensor Chip

Identifying grape varieties in wine, related products, and raw materials is of great interest for enology and to ensure its authenticity. However, these matrices' complexity and low DNA content make this analysis particularly challenging. Integrating DNA analysis with 2D materials, such as graphene, offers an advantageous pathway toward ultrasensitive DNA detection. Here, we show that monolayer graphene provides an optimal test bed for nucleic acid detection with single-base resolution. Graphene's ultrathinness creates a large surface area with quantum confinement in the perpendicular direction that, upon functionalization, provides multiple sites for DNA immobilization and efficient detection. Its highly conjugated electronic structure, high carrier mobility, zero-energy band gap with the associated gating effect, and chemical inertness explain graphene's superior performance. For the first time, we present a DNA-based analytic tool for grapevine varietal discrimination using an integrated portable biosensor based on a monolayer graphene field-effect transistor array. The system comprises a wafer-scale fabricated graphene chip operated under liquid gating and connected to a miniaturized electronic readout. The platform can distinguish closely related grapevine varieties, thanks to specific DNA probes immobilized on the sensor, demonstrating high specificity even for discriminating single-nucleotide polymorphisms, which is hard to achieve with a classical end-point polymerase chain reaction or quantitative polymerase chain reaction. The sensor was operated in ultralow DNA concentrations, with a dynamic range of 1 aM to 0.1 nM and an attomolar detection limit of ∼0.19 aM. The reported biosensor provides a promising way toward developing decentralized analytical tools for tracking wine authenticity at different points of the food value chain, enabling data transmission and contributing to the digitalization of the agro-food industry.

Authentication of Polish Red Wines Produced from Zweigelt and Rondo Grape Varieties Based on Volatile Compounds Analysis in Combination with Machine Learning Algorithms: Hotrienol as a Marker of the Zweigelt Variety

The aim of this study was to determine volatile compounds in red wines of Zweigelt and Rondo varieties using HS-SPME/GC-MS and to find a marker and/or a classification model for the assessment of varietal authenticity. The wines were produced by using five commercial yeast strains and two types of malolactic fermentation. Sixty-seven volatile compounds were tentatively identified in the test wines; they represented several classes: 9 acids, 24 alcohols, 2 aldehydes, 19 esters, 2 furan compounds, 2 ketones, 1 sulfur compound and 8 terpenes. 3,7-dimethyl-1,5,7-octatrien-3-ol (hotrienol) was found to be a variety marker for Zweigelt wines, since it was detected in all the Zweigelt wines, but was not present in the Rondo wines at all. The relative concentrations of volatiles were used as an input data set, divided into two subsets (training and testing), to the support vector machine (SVM) and k-nearest neighbor (kNN) algorithms. Both machine learning methods yielded models with the highest possible classification accuracy (100%) when the relative concentrations of all the test compounds or alcohols alone were used as input data. An evaluation of the importance value of subsets consisting of six volatile compounds with the highest potential to distinguish between the Zweigelt and Rondo varieties revealed that SVM and kNN yielded the best classification models (F-score of 1, accuracy of 100%) when 3-ethyl-4-methylpentan-1-ol or 3,7-dimethyl-1,5,7-octatrien-3-ol (hotrienol) or subsets containing one or both of them were used. Moreover, the best SVM model (F-score of 1) was built with a subset containing 2-phenylethyl acetate and 3-(methylsulfanyl)propan-1-ol.

Isomer composition of aroma compounds as a promising approach for wine characterization and differentiation: A review

The perceived aroma is the result of the presence of volatile organic compounds (VOCs) as well as the interaction among them and with the nonvolatile sample matrix. These compounds can derive from grape berries (varietal) and also be formed during winemaking and aging processes. Varietal VOCs are strongly influenced by the grape variety, ripening, and geographical origin. Therefore, they were proposed as markers for wine discrimination. Nevertheless, recent studies highlighted the higher discriminating ability of VOC isomer forms. In this review the potential and importance of VOC isomers for terpenes, C13-norisoprenoids, C6-alcohols, thiols, lactones, and fatty acid esters, as well as isomeric relationships for wine characterization and differentiation have been described to get a full view of possible applications for the wine industry, highlighting potentialities and limitations. VOC isomers can be of paramount relevance to find reliable markers for wine authenticity and fraud prevention, regarding variety and geographical origin. Each isomer form owns a different olfactory threshold, influencing strongly wine sensory characteristics. Certain oenological treatments during winemaking and aging were found to modify the isomeric profile, particularly yeasts, aging, and wood in contact with wine. Nevertheless, this research field has potential and new research advances are expected in this field.

Use of Multivariate Statistics in the Processing of Data on Wine Volatile Compounds Obtained by HS-SPME-GC-MS

This review takes a snapshot of the main multivariate statistical techniques and methods used to process data on the concentrations of wine volatile molecules extracted by means of solid phase micro-extraction and analyzed using GC-MS. Hypothesis test, exploratory analysis, regression models, and unsupervised and supervised pattern recognition methods are illustrated and discussed. Several applications in the wine volatolomic sector are described to highlight different interactions among the various matrix components and volatiles. In addition, the use of Artificial Intelligence-based methods is discussed as an innovative class of methods for validating wine varietal authenticity and geographical traceability.

Impact of oenological processing aids and additives on the genetic traceability of 'Nebbiolo' wine produced with withered grapes

'Nebbiolo' is a well-known grapevine variety used to produce prestigious monovarietal Italian red wines. Genetic traceability is an important tool used to protect the authenticity of high-quality wines. SNP-based assays are an effective method to reach this aim in wines, but several issues have been reported for the authentication of commercial wines. In this study, the impact of the most common commercial additives and processing aids used in winemaking was analysed in 'Nebbiolo' wine using SNP-based traceability. Gelatine and bentonite had the strongest impact on the turbidity, colour and phenolic composition of wines and on residual grapevine DNA. The DNA reduction associated with the use of bentonite and gelatine (>99% compared to the untreated control) caused issues in the SNP-based assay, especially when the DNA concentration was below 0.5 pg/mL of wine. This study contributed to explaining the causes of the reduced varietal identification efficiency in commercial wines.

Identification of Tentative Traceability Markers with Direct Implications in Polyphenol Fingerprinting of Red Wines: Application of LC-MS and Chemometrics Methods

This study investigated the potential of using the changes in polyphenol composition of red wine to enable a more comprehensive chemometric differentiation and suitable identification of authentication markers. Based on high performance liquid chromatography-mass spectrometry (HPLC-MS) data collected from Feteasca Neagra, Merlot, and Cabernet Sauvignon finished wines, phenolic profiles of relevant classes were investigated immediately after vinification (Stage 1), after three months (Stage 2) and six months (Stage 3) of storage, respectively. The data were subjected to multivariate analysis, and resulted in an initial vintage differentiation by principal component analysis (PCA), and variety grouping by canonical discriminant analysis (CDA). Based on polyphenol common biosynthesis route and on the PCA correlation matrix, additional descriptors were investigated. We observed that the inclusion of specific compositional ratios into the data matrix allowed for improved sample differentiation. We obtained simultaneous discrimination according to the considered oenological factors (variety, vintage, and geographical origin) as well as the respective clustering applied during the storage period. Subsequently, further discriminatory investigations to assign wine samples to their corresponding classes relied on partial least squares-discriminant analysis (PLS-DA); the classification models confirmed the clustering initially obtained by PCA. The benefits of the presented fingerprinting approach might justify its selection and warrant its potential as an applicable tool with improved authentication capabilities in red wines.

Liquid chromatographic methods coupled to chemometrics: a short review to present the key workflow for the investigation of wine phenolic composition as it is affected by environmental factors

The guarantee of wine authenticity arises great concern because of its nutritional and economic importance. Phenolic fingerprints have been used as a source of chemical information for various authentication issues, including botanical and geographical origin, as well as vintage age. The local environment affects wine production and especially its phenolic metabolites. Integrated analytical methodologies combined with chemometrics can be applied in wine fingerprinting studies for the determination and establishment of phenolic markers that contain comprehensive and standardized information about the wine profile and how it can be affected by various environmental factors. This review summarizes all the recent trends in the generation of chemometric models that have been developed for treating chromatographic data and have been used for the investigation of critical wine authenticity issues, revealing phenolic markers responsible for the botanical, geographical, and vintage age classification of wines. Overall, the current review suggests that chromatographic methodologies are promising and powerful techniques that can be used for the accurate determination of phenolic compounds in difficult matrices like wine, highlighting the advantages of the applications of supervised chemometric tools over unsupervised for the construction of prediction models that have been successfully used for the classification based on their territorial and botanical origin.

Multi-Sensor Characterization of Sparkling Wines Based on Data Fusion

This paper is focused on the assessment of a multi-sensor approach to improve the overall characterization of sparkling wines (cava wines). Multi-sensor, low-level data fusion can provide more comprehensive and more accurate vision of results compared with the study of simpler data sets from individual techniques. Data from different instrumental platforms were combined in an enriched matrix, integrating information from spectroscopic (UV/Vis and FTIR), chromatographic, and other techniques. Sparkling wines belonging to different classes, which differed in the grape varieties, coupages, and wine-making processes, were analyzed to determine organic acids (e.g., tartaric, lactic, malic, and acetic acids), pH, total acidity, polyphenols, total antioxidant capacity, ethanol, or reducing sugars. The resulting compositional values were treated chemometrically for a more efficient recovery of the underlaying information. In this regard, exploratory methods such as principal component analysis showed that phenolic compounds were dependent on varietal and blending issues while organic acids were more affected by fermentation features. The analysis of the multi-sensor data set provided a more comprehensive description of cavas according to grape classes, blends, and vinification processes. Hierarchical Cluster Analysis (HCA) allowed specific groups of samples to be distinguished, featuring malolactic fermentation and the chardonnay and red grape classes. Partial Least Squares-Discriminant Analysis (PLS-DA) also classified samples according to the type of grape varieties and fermentations. Bar charts and complementary statistic test were performed to better define the differences among the studied samples based on the most significant markers of each cava wine type. As a conclusion, catechin, gallic, gentisic, caftaric, caffeic, malic, and lactic acids were the most remarkable descriptors that contributed to their discrimination based on varietal, blending, and oenological factors.

Differentiation Between Argentine and Austrian Red and White Wines Based on Isotopic and Multi-Elemental Composition

In this work, the characterization of white and red wines from Austria and Argentina was carried out based on the isotopic and multi-elemental profile data. They were determined using vanguard techniques such as isotope ratio mass spectrometry and inductively coupled plasma mass spectrometry. In particular, Al, As, B, Ca, Co, Cu, Fe, K, Li, Mg, Mn, Na, Ni, Pb, Rb, Sr, V, Zn, δ18O, and δ13C were determined. The results show that the samples of wines from Argentina generally present higher concentrations of the elements analyzed compared to Austrian wines. δ18O values from wine water were characteristic of each country, while δ13C values from ethanol did not present any geographical distinction. Linear discriminant analysis using isotopes and elements allowed us to classify 100% of the wines according to the origin and additionally, 98.4% when separately investigating red and white wines. The elements Sr, Li, V, Pb, B, Mn, Co, Rb, As, Na, Mg, Zn, and δ18O were identified as sensitive indicators capable of differentiate wines according to their production origin. Furthermore, Sr, Li, Na, δ13C, δ18O, Ca, B, Fe, Mn, V, Mg, Co, and Zn contributed to the differentiation of wines according to origin and color. To our knowledge, it is the first work that involves the measurement of a wide range of elements and stable isotopes in white and red wines in Argentina, as well as in Austria. This research highlights the power of the application of stable isotopes and multi-element data in multivariate statistical analysis, in order to obtain an accurate differentiation of wines origin.

A Multidisciplinary Fingerprinting Approach for Authenticity and Geographical Traceability of Portuguese Wines

The interest in developing reliable wine authenticity schemes is a hot-topic, especially for wines with recognized added-value. In order to accomplish this goal, two dimensions need to be considered: the grapevine variety determination and the geographical provenance. The aim of this study was to develop a multidisciplinary approach applicable to wines from the sub region Melgaço and Monção of the demarcated Vinho Verde region and from the demarcated Douro region. The proposed scheme consists on the use of DNA-based assays to detect Single Nucleotide Polymorphisms (SNPs) on three genes of the anthocyanin pathway (UFGT, F3H and LDOX) coupled with High-resolution melting (HRM) analysis aiming the varietal identification. The Alvarinho wines revealed to have the same haplotype using this marker set, demonstrating its applicability for genetic identification. In addition, to assess their geographical provenance, a multi-elemental approach using Sr and Pb isotopic ratios of wine, soil and bedrock samples was used. The isotopic data suggest a relation between Sr and Pb uptake by vine roots and soil's texture and clay content, rather than with the whole rock's isotopic ratios, but also highlights the potential of a discriminating method based on the combination of selected isotopic signatures.

Relationship between anthocyanins, proanthocyanidins, and cell wall polysaccharides in grapes and red wines. A current state-of-art review

Numerous research studies have evaluated factors influencing the nature and levels of phenolics and polysaccharides in food matrices. However, in grape and wines most of these works have approach these classes of compounds individually. In recent years, the number of publications interconnecting classes have increased dramatically. The present review relates the last decade's findings on the relationship between phenolics and polysaccharides from grapes, throughout the entire winemaking process up to evaluating the impact of their relationship on the red wine sensory perception. The combination and interconnection of the most recent research studies, from single interactions in model wines to the investigation of the formation of complex macromolecules, brings the perfect story line to relate the relationship between phenolics and polysaccharides from the vineyard to the glass. Grape pectin is highly reactive toward grape and grape derived phenolics. Differences between grape cultivars or changes during grape ripeness will affect the extractability of these compounds into the wines. Therefore, the nature of the grape components will be crucial to understand the subsequent reactions occurring between phenolics and polysaccharide of the corresponding wines. It has been demonstrated that they can form very complex macromolecules which affect wine color, stability and sensory properties.

Diversity of Italian red wines: A study by enological parameters, color, and phenolic indices

An extensive survey was conducted on 110 Italian monovarietal red wines from a single vintage to determine their standard compositional, color, and phenolic characteristics, analysing more than 35 parameters evaluated through methods commonly used in the wine industry. 'Primitivo' achieved the highest average alcohol strength (15.4% v/v) and dry extract values, while 'Cannonau' showed the lowest total acidity. 'Corvina' had the lowest phenolic content (1065 mg/L by Folin-Ciocalteu assay), remarkably different from the highest found in 'Sagrantino' (3578 mg/L), the latter being also the richest variety in both proanthocyanidins and vanillin-reactive flavanols. 'Teroldego' wines were the richest in both total and monomeric anthocyanins (702 and 315 mg/L, respectively), followed by 'Aglianico' and 'Raboso Piave', while 'Corvina', 'Nebbiolo', and 'Nerello Mascalese' were the poorest. 'Montepulciano' and 'Sangiovese' showed intermediate values for the majority of the parameters analyzed. A multivariate PCA-DA approach allowed achieving both a classification of the different wines as well as the discrimination of 'Sangiovese' wines produced in two regions (Emilia Romagna and Toscana) that returned a 42-66% success rate depending on the zone considered. Taking into account the number and diversity of the wines analyzed, a correlation study helped in better understanding the underlying relations between the most common and widespread analytical techniques for phenolic and color determinations.

Mid-Infrared Spectroscopy as a Valuable Tool to Tackle Food Analysis: A Literature Review on Coffee, Dairies, Honey, Olive Oil and Wine

Nowadays, food adulteration and authentication are topics of utmost importance for consumers, food producers, business operators and regulatory agencies. Therefore, there is an increasing search for rapid, robust and accurate analytical techniques to determine the authenticity and to detect adulteration and misrepresentation. Mid-infrared spectroscopy (MIR), often associated with chemometric techniques, offers a fast and accurate method to detect and predict food adulteration based on the fingerprint characteristics of the food matrix. In the first part of this review the basic concepts of infrared spectroscopy, sampling techniques, as well as an overview of chemometric tools are summarized. In the second part, recent applications of MIR spectroscopy to the analysis of foods such as coffee, dairy products, honey, olive oil and wine are discussed, covering a timespan from 2010 to mid-2020. The literature gathered in this article clearly reveals that the MIR spectroscopy associated with attenuated total reflection acquisition mode and different chemometric tools have been broadly applied to address quality, authenticity and adulteration issues. This technique has the advantages of being simple, fast and easy to use, non-destructive, environmentally friendly and, in the future, it can be applied in routine analyses and official food control.

Designing blockchain systems to prevent counterfeiting in wine supply chains: a multiple-case study

Purpose

The purpose of this paper is to contribute to the debate on blockchain (BC) adoption for preventing counterfeiting by investigating BC systems where different options for BC feeding and reading complement the use of BC technology. By grounding on the situational crime prevention, this study analyses how BC systems can be designed to effectively prevent counterfeiting.

Design/methodology/approach

This is a multiple-case study of five Italian wine companies using BC to prevent counterfeiting.

Findings

This study finds that the desired level of upstream/downstream counterfeiting protection that a brand owner intends to guarantee to customers through BC is the key driver to consider in the design of BC systems. The study identifies which variables are relevant to the design of feeding and reading processes and explains how such variables can be modulated in accordance with the desired level of counterfeiting protection.

Research limitations/implications

The cases investigated are Italian companies within the wine sector, and the BC projects analysed are in the pilot phase.

Practical implications

The study provides practical suggestions to address the design of BC systems by identifying a set of key variables and explaining how to properly modulate them to face upstream/downstream counterfeiting.

Originality/value

This research applies a new perspective based on the situational crime prevention approach in studying how companies can design BC systems to effectively prevent counterfeiting. It explains how feeding and reading process options can be configured in BC systems to assure different degrees of counterfeiting protection.

Comprehensive 2D Gas Chromatography with TOF-MS Detection Confirms the Matchless Discriminatory Power of Monoterpenes and Provides In-Depth Volatile Profile Information for Highly Efficient White Wine Varietal Differentiation

To differentiate white wines from Croatian indigenous varieties, volatile aroma compounds were isolated by headspace solid-phase microextraction (HS-SPME) and analyzed by comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry (GC×GC-TOF-MS) and conventional one-dimensional GC-MS. The data obtained were subjected to uni- and multivariate statistical analysis. The extra separation ability of the GC×GC second dimension provided additional in-depth volatile profile information, with more than 1000 compounds detected, while 350 were identified or tentatively identified in total by both techniques, which allowed highly efficient differentiation. A hundred and sixty one compounds in total were significantly different across monovarietal wines. Monoterpenic compounds, especially α-terpineol, followed by limonene and linalool, emerged as the most powerful differentiators, although particular compounds from other chemical classes were also shown to have notable discriminating ability. In general, Škrlet wine was the most abundant in monoterpenes, Malvazija istarska was dominant in terms of fermentation esters concentration, Pošip contained the highest levels of particular C₁₃-norisoprenoids, benzenoids, acetates, and sulfur containing compounds, Kraljevina was characterized by the highest concentration of a tentatively identified terpene γ-dehydro-ar-himachalene, while Maraština wine did not have specific unambiguous markers. The presented approach could be practically applied to improve defining, understanding, managing, and marketing varietal typicity of monovarietal wines.

Polyphenols: Natural Antioxidants to Be Used as a Quality Tool in Wine Authenticity

Polyphenols are a diverse group of compounds possessing various health-promoting properties that are of utmost importance for many wine sensory attributes. Apart from genetic and environmental parameters, the implementation of specific oenological practices as well as the subsequent storage conditions deeply affect the content and nature of the polyphenols present in wine. However, polyphenols are effectively employed in authenticity studies. Provision of authentic wines to the market has always been a prerequisite meaning that the declarations on the wine label should mirror the composition and provenance of this intriguing product. Nonetheless, multiple cases of intentional or unintentional wine mislabeling have been recorded alarming wine consumers who demand for strict controls safeguarding wine authenticity. The emergence of novel platforms employing instrumentation of exceptional selectivity and sensitivity along with the use of advanced chemometrics such as NMR (nuclear magnetic resonance)- and MS (mass spectrometry)-based metabolomics is considered as a powerful asset towards wine authentication.

Electrochemical Sensors Coupled with Multivariate Statistical Analysis as Screening Tools for Wine Authentication Issues: A Review

Consumers are increasingly interested in the characteristics of the products they consume, including aroma, taste, and appearance, and hence, scientific research was conducted in order to develop electronic senses devices that mimic the human senses. Thanks to the utilization of electroanalytical techniques that used various sensors modified with different electroactive materials coupled with pattern recognition methods, artificial senses such as electronic tongues (ETs) are widely applied in food analysis for quality and authenticity approaches. This paper summarizes the applications of electrochemical sensors (voltammetric, amperometric, and potentiometric) coupled with unsupervised and supervised pattern recognition methods (principal components analysis (PCA), linear discriminant analysis (LDA), partial least square (PLS) regression, artificial neural network (ANN)) for wine authenticity assessments including the discrimination of varietal and geographical origins, monitoring the ageing processes, vintage year discrimination, and detection of frauds and adulterations. Different wine electrochemical authentication methodologies covering the electrochemical techniques, electrodes types, functionalization sensitive materials and multivariate statistical analysis are emphasized and the main advantages and disadvantages of using the proposed methodologies for real applications were concluded.

Authentication of the geographical origin of Australian Cabernet Sauvignon wines using spectrofluorometric and multi-element analyses with multivariate statistical modelling

With the increased risk of wine fraud, a rapid and simple method for wine authentication has become a necessity for the global wine industry. The use of fluorescence data from an absorbance and transmission excitation-emission matrix (A-TEEM) technique for discrimination of wines according to geographical origin was investigated in comparison to inductively coupled plasma-mass spectrometry (ICP-MS). The two approaches were applied to commercial Cabernet Sauvignon wines from vintage 2015 originating from three wine regions of Australia, along with Bordeaux, France. Extreme gradient boosting discriminant analysis (XGBDA) was examined among other multivariate algorithms for classification of wines. Models were cross-validated and performance was described in terms of sensitivity, specificity, and accuracy. XGBDA classification afforded 100% correct class assignment for all tested regions using the EEM of each sample, and overall 97.7% for ICP-MS. The novel combination of A-TEEM and XGBDA was found to have great potential for accurate authentication of wines.

Chemical typicality of South American red wines classified according to their volatile and phenolic compounds using multivariate analysis

In this study, 83 wines representating four commercial categories: "Argentinean Malbec", "Brazilian Merlot", "Uruguayan Tannat" and "Chilean Carménère" were analyzed according to their phenolic and volatile compounds. The objective was to identify the chemical compounds that would typify each category. From approximately about 600 peaks obtained by chromatographic techniques, 169 were identified and 53 of them were selected for multivariate statistical analysis. Chilean Carménère was the best discriminated group by the methods applied in our study, followed by Argentinean Malbec. Brazilian Merlot mixed mainly with some Carménère, whileTannat mixed with all wines categories, especially Malbec. In general, Chilean Carménère wines can be characterized by a bluish color, higher amounts of sulphur dioxide, higher content of octanoic acid, isobutanol, ethyl isoamyl succinate and catechin and a smaller amount of quercetin. These data can contribute for further process of authenticity or typification of South American red wines.

Single-nucleotide polymorphism (SNP) genotyping assays for the varietal authentication of 'Nebbiolo' musts and wines

'Nebbiolo' (Vitis vinifera L.) is renowned for its use in producing monovarietal high-quality red wines, such Barolo and Barbaresco. The fight against fraud to safeguard high-quality productions requires an effective varietal identification system applicable in musts and wines. 'Nebbiolo'-specific single-nucleotide polymorphisms (SNPs) were identified starting from available databases and 260 genotypes analysed by Vitis18kSNP array. Two SNPs were sufficient to identify 'Nebbiolo' from 1157 genotypes. The SNP TaqMan® genotyping assays developed in this work successfully identified 'Nebbiolo' in all musts and wines collected at different experimental wine-making steps. The high sensitivity of the assays allowed identification of must mixtures at 1% and wine mixtures at 10-20% with non-'Nebbiolo' genotypes. In commercial wines, the amplification efficiency was limited by the low amount of grapevine DNA and the presence of PCR inhibitors. The TaqMan® genotyping assay is a rapid, highly sensitive and specific methodology with remarkable potential for varietal identification in wines.

Application of Spectroscopic UV-Vis and FT-IR Screening Techniques Coupled with Multivariate Statistical Analysis for Red Wine Authentication: Varietal and Vintage Year Discrimination

One of the most important issues in the wine sector and prevention of adulterations of wines are discrimination of grape varieties, geographical origin of wine, and year of vintage. In this experimental research study, UV-Vis and FT-IR spectroscopic screening analytical approaches together with chemometric pattern recognition techniques were applied and compared in addressing two wine authentication problems: discrimination of (i) varietal and (ii) year of vintage of red wines produced in the same oenological region. UV-Vis and FT-IR spectra of red wines were registered for all the samples and the principal features related to chemical composition of the samples were identified. Furthermore, for the discrimination and classification of red wines a multivariate data analysis was developed. Spectral UV-Vis and FT-IR data were reduced to a small number of principal components (PCs) using principal component analysis (PCA) and then partial least squares discriminant analysis (PLS-DA) and linear discriminant analysis (LDA) were performed in order to develop qualitative classification and regression models. The first three PCs used to build the models explained 89% of the total variance in the case of UV-Vis data and 98% of the total variance for FR-IR data. PLS-DA results show that acceptable linear regression fits were observed for the varietal classification of wines based on FT-IR data. According to the obtained LDA classification rates, it can be affirmed that UV-Vis spectroscopy works better than FT-IR spectroscopy for the discrimination of red wines according to the grape variety, while classification of wines according to year of vintage was better for the LDA based FT-IR data model. A clear discrimination of aged wines (over six years) was observed. The proposed methodologies can be used as accessible tools for the wine identity assurance without the need for costly and laborious chemical analysis, which makes them more accessible to many laboratories.

How to integrate wet lab and bioinformatics procedures for wine DNA admixture analysis and compositional profiling: Case studies and perspectives

The varietal authentication of wines is fundamental for assessing wine quality, and it is part of its compositional profiling. The availability of historical, cultural and chemical composition information is extremely important for quality evaluation. DNA-based techniques are a powerful tool for proving the varietal composition of a wine. SSR-amplification of genomic residual Vitis vinifera DNA, namely Wine DNA Fingerprinting (WDF) is able to produce strong, analytical evidence concerning the monovarietal nature of a wine, and for blended wines by generating the probability of the presence/absence of a certain variety, all in association with a dedicated bioinformatics elaboration of genotypes associated with possible varietal candidates. Together with WDF we could exploit Bioinformatics techniques, due to the number of grape genomes grown. In this paper, the use of WDF and the development of a bioinformatics tool for allelic data validation, retrieved from the amplification of 7 to 10 SSRs markers in the Vitis vinifera genome, are reported. The wines were chosen based on increasing complexity; from monovarietal, experimental ones, to commercial monovarietals, to blended commercial wines. The results demonstrate that WDF, after calculation of different distance matrices and Neighbor-Joining input data, followed by Principal Component Analysis (PCA) can effectively describe the varietal nature of wines. In the unknown blended wines the WDF profiles were compared to possible varietal candidates (Merlot, Pinot Noir, Cabernet Sauvignon and Zinfandel), and the output graphs show the most probable varieties used in the blend as closeness to the tested wine. This pioneering work should be meant as to favor in perspective the multidisciplinary building-up of on-line databanks and bioinformatics toolkits on wine. The paper concludes with a discussion on an integrated decision support system based on bioinformatics, chemistry and cultural data to assess wine quality.

Alternative Methods to SO2 for Microbiological Stabilization of Wine

The use of sulfur dioxide (SO₂ ) as wine additive is able to ensure both antioxidant protection and microbiological stability. In spite of these undeniable advantages, in the last two decades the presence of SO₂ in wine has raised concerns about potential adverse clinical effects in sensitive individuals. The winemaking industry has followed the general trend towards the reduction of SO₂ concentrations in food, by expressing at the same time the need for alternative control methods allowing reduction or even elimination of SO_2. In the light of this, research has been strongly oriented toward the study of alternatives to the use of SO₂ in wine. Most of the studies have focused on methods able to replace the antimicrobial activity of SO₂ . This review article gives a comprehensive overview of the current state-of-the-art about the chemical additives and the innovative physical techniques that have been proposed for this purpose. After a focus on the chemistry and properties of SO₂ in wine_, as well as on wine spoilage and on the conventional methods used for the microbiological stabilization of wine, recent advances on alternative methods proposed to replace the antimicrobial activity of SO₂ in winemaking are presented and discussed. Even though many of the alternatives to SO₂ showed good efficacy, nowadays no other physical technique or additive can deliver the efficacy and broad spectrum of action as SO₂ (both antioxidant and antimicrobial), therefore the alternative methods should be considered a complement to SO₂ in low-sulfite winemaking, rather than being seen as its substitutes.

Polyphenol Fingerprinting Approaches in Wine Traceability and Authenticity: Assessment and Implications of Red Wines

Like any other food/feed matrix, regardless of the employed analytical method, wine requires authentication strategies; a suitable qualitative and quantitative analysis represents the fingerprint which defines its identity. Until recently, fingerprinting approaches using liquid chromatography applications have been regarded as an effective tool for the assessment of wines employing polyphenol profiles. These profiles are of considerable importance for grapes and wines as they influence greatly the color, sensory, and nutritional quality of the final product. The authenticity and typicity characters are fundamental characteristics, which may be evaluated by the use of polyphenol fingerprinting techniques. Under these conditions, the evolution of polyphenols during the red wine elaboration and maturation processes shows a high importance at the level of the obtained fingerprints. Moreover, the environment factors (vintage, the area of origin, and variety) and the technological conditions significantly influence wine authenticity through the use of polyphenol profiles. Taking into account the complexity of the matter at hand, this review outlines the latest trends in the polyphenol fingerprinting of red wines in association with the transformations that occur during winemaking and storage.

High-Resolution Mass Spectrometry Identification of Secondary Metabolites in Four Red Grape Varieties Potentially Useful as Traceability Markers of Wines

Liquid chromatography coupled to high-resolution mass spectrometry (LC-Q/TOF) is a powerful tool to perform chemotaxonomic studies through identification of grape secondary metabolites. In the present work, the metabolomes of four autochthonous Italian red grape varieties including the chemical classes of anthocyanins, flavonols/flavanols/flavanones, and terpenol glycosides, were studied. By using this information, the metabolites that can potentially be used as chemical markers for the traceability of the corresponding wines were proposed. In Raboso wines, relatively high abundance of both anthocyanic and non-anthocyanic acyl derivatives, is expected. Potentially, Primitivo wines are characterized by high tri-substituted flavonoids, while Corvina wines are characterized by higher di-substituted compounds and lower acyl derivatives. Negro Amaro wine’s volatile fraction is characterized by free monoterpenes, such as α-terpineol, linalool, geraniol, and Ho-diendiol I. A similar approach can be applied for the traceability of other high-quality wines.

From the Field to the Bottle—An Integrated Strategy for Wine Authenticity

The wine sector is one of the most economically important agro-food businesses. The wine market value is largely associated to terroir, in some cases resulting in highly expensive wines that attract fraudulent practices. The existent wine traceability system has some limitations that can be overcome with the development of new technological approaches that can tackle this problem with several means. This review aims to call attention to the problem and to present several strategies that can assure a more reliable and authentic wine system, identifying existent technologies developed for the sector, which can be incorporated into the current traceability system.

High-resolution mass spectrometry metabolomics of grape chemical markers to reveal use of not-allowed varieties in the production of Amarone and Recioto wines

INTRODUCTION

Grape varieties allowed to produce Amarone della Valpolicella and Recioto DOCG wines are strictly regulated by their disciplinary of production. These are Corvina Veronese and Corvinone grapes, to a lesser extent also Rondinella can be used. The use of other varieties, is not allowed.

OBJECTIVES

To identify chemical markers suitable to reveal addition of two not allowed grape varieties to the Corvina/Corvinone blend, such as Primitivo or Negro Amaro.

METHODS

The identification of the secondary metabolites of the four grape varieties was conducted by high-resolution mass spectrometry (HRMS) metabolomics. By using the signals of these metabolites the indexes able to identify the presence of Primitivo or Negro Amaro grapes in the Corvina/Corvinone 1:1 blend were calculated.

RESULTS

Indexes of laricitrin (Lr), delphinidin (Dp), and petunidin (Pt) signals were effective to identify the use of 10% Primitivo, while α-terpineol pentosyl-hexoside and linalool pentosyl-hexoside reveal the presence of Negro Amaro in the grape blend.

CONCLUSIONS

Varietal markers useful to detect the presence of Primitivo and Negro Amaro in the grape blend were identified by HRMS metabolomics, a method suitable to check the identity of grapes on arrival at the winery, as well as the fermenting musts. The effectiveness of the identified markers in the final wines have to be confirmed. Potentially, a similar approach can be used to reveal analogous frauds performed on other high-quality wines.

Microsatellite High-Resolution Melting (SSR-HRM) to Track Olive Genotypes: From Field to Olive Oil

The need to support food labelling has driven to the development of PCR-based techniques suitable for food analysis. DNA-based markers have been successfully employed for varietal tracing in Protected Designation of Origin (PDO) olive oils. In this study, we report a fast, sensitive, and easy-to-use strategy for PDO olive varietal identification. To achieve this aim four different DNA extraction methods were tested and compared, based on initial volume, extraction time, the gDNA concentration, and quality ratios. The optimized DNA extraction protocol from extra virgin olive oils, based on CTAB-hexane-chloroform extraction, proved to be the most effective. High-resolution melting (HRM) DNA assay was developed based on nuclear microsatellites (gSSR) and plastid DNA (cpDNA) aiming an accurate identification of the olive varieties present in the olive oil samples. After PCR reproducibility evaluation, six molecular markers: three SSRs and three cpDNA loci were chosen based on their discrimination power. The SSR-HRM strategy assays were designed to target UDO99-011, UDO99-039, UDO99-024, and ssrOeUA-DCA16 loci. All SSR-PCR products generated from these primers were analyzed by capillary electrophoresis (CE) for HRM data validation. The SSR coupled with HRM melting curve analysis generated 14 HRM profiles sufficient to genotype all varieties, highlighting their potential use for varietal discrimination. The locus ssrOeUA-DCA16 generated a specific melting curve that allow a high-throughput discrimination of the Picual and Cobrançosa varieties in olive oil samples. Further, the UDO99-024 was also tested by SSR-HRM assay in commercial olive oil samples with promising results. Considering time, cost, and performance SSR-HRM proved to be a reliable method suitable for varietal tracing of olive oils. PRACTICAL APPLICATION: Olive oil authenticity is a form of protecting producers and consumers against fraudulent practices. Herein, we present a DNA barcode suitable for the identification of olive varieties, allowing an accurate identification of the olive varieties in olive oil samples using SSR-HRM assay. Its applicability in commercial olive oil samples is viable. This methodology can be used as a tool for Extra Virgin Olive Oil (EVOO) adulterations detection.