Regional and Vintage Discrimination of Romanian Wines Based on Elemental and Isotopic Fingerprinting

Evaluating the Chemical Hazards in Wine Production Associated with Climate Change

The climate warming trend challenges the chemical risk associated with wine production worldwide. The present study investigated the possible difference between chemical wine profile during the drought year 2012 compared to the post-drought year 2013. Toxic metals (Cd and Pb), microelements (Mn, Ni, Zn, Al, Ba, and Cu), macroelements (Na, Mg, K, Ca, and P), isotopic ratios (87Sr/86Sr and 206Pb/207Pb), stable isotopes (δ18O, δ13C, (D/H)I, and (D/H)II), and climatic data were analyzed. The multivariate technique, correlation analysis, factor analysis, partial least squares–discriminant analysis, and hierarchical cluster analysis were used for data interpretation. The maximum temperature had a maximum difference when comparing data year apart. Indeed, extreme droughts were noted in only the spring and early summer of 2012 and in 2013, which increased the mean value of ground frost days. The microelements, macroelements, and Pb presented extreme effects in 2012, emphasizing more variability in terms of the type of wine. Extremely high Cd values were found in the wine samples analyzed, at up to 10.1 µg/L. The relationship between precipitation and δ18O from wine was complex, indicating grape formation under the systematic influence of the current year precipitation, and differences between years were noted. δ13C had disentangled values, with no differentiation between years, and when coupled with the deuterium–hydrogen ratio, it could sustain the hypothesis of possible adulteration. In the current analysis, the 87Sr/86Sr showed higher values than in other Romanian studies. The temperature had a strong positive correlation with Pb, while the ground frost day frequency correlated with both Pb and Cd toxic elements in the wine. Other significant relationships were disclosed between the chemical properties of wine and climate data. The multivariate statistical analysis indicated that heat stress had significant importance in the chemical profile of the wine, and the ground frost exceeded the influence of water stress, especially in Transylvania.

Assessment of the Authenticity of Whisky Samples Based on the Multi-Elemental and Multivariate Analysis

Two hundred and five samples of whisky, including 170 authentic and 35 fake products, were analyzed in terms of their elemental profiles in order to distinguish them according to the parameter of their authenticity. The study of 31 elements (Ag, Al, B, Ba, Be, Bi, Cd, Co, Cr, Cu, Li, Mn, Mo, Ni, Pb, Sb, Sn, Sr, Te, Tl, U, V, Ca, Fe, K, Mg, P, S, Ti and Zn) was performed using the Inductively Coupled Plasma Mass Spectrometry (ICP-MS), Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES) and Cold Vapor-Atomic Absorption (CVAAS) techniques. Additionally, the pH values of all samples were determined by pH-meter, and their isotopic ratios of ⁸⁸Sr/⁸⁶Sr, ⁸⁴Sr/⁸⁶Sr, ⁸⁷Sr/⁸⁶Sr and ⁶³Cu/⁶⁵Cu were assessed, based on the number of counts by ICP-MS. As a result of conducted research, elements, such as Mn, K, P and S, were identified as markers of whisky adulteration related to the age of alcohol. The concentrations of manganese, potassium and phosphorus were significantly lower in the fake samples (which were not aged, or the aging period was much shorter than legally required), compared to the original samples (in all cases subjected to the aging process). The observed differences were related to the migration of these elements from wooden barrels to the alcohol contained in them. On the other hand, the sulfur concentration in the processed samples was much higher in the counterfeit samples than in the authentic ones. The total sulfur content, such as that of alkyl sulfides, decreases in alcohol with aging in the barrels. Furthermore, counterfeit samples can be of variable origin and composition, so they cannot be characterized as one group with identical or comparable features. Repeatedly, the element of randomness dominates in the production of these kinds of alcohols. However, as indicated in this work, the extensive elemental analysis supported by statistical tools can be helpful, especially in the context of detecting age-related adulteration of whisky. The results presented in this paper are the final part of a comprehensive study on the influence of selected factors on the elemental composition of whisky.

The phytochemical components of walnuts and their application for geographical origin based on chemical markers

Place of origin has an important influence on walnut quality and commercial value, which results in the requirement of rapid geographical traceability method. Thus, a method for geographical origin identification of walnuts on the basis of nutritional quality of walnut from China was conducted. The concentrations of 43 phytochemical components were analyzed in walnut samples from five different walnut-producing regions of China. Based on 14 chemical markers selected by the Random Forest method from these phytochemical components, a new discriminant model for geographical origin was built, with the corresponding correct classification rate of 99.3%. In addition, the quantitative quality differences of walnuts from five regions were analyzed, with the values of 0.17-1.43. Moreover, the top three chemical markers for the geographical origin discriminant analysis were Mo, V and stearic acid, with the contribution rates of 26.8%, 18.9% and 10.9%. This study provides a potentially viable method for application in the food authentication.

Chemometric approaches for determining the geographical origin of Japanese Chardonnay wines using oxygen stable isotope and multi-element analyses

Determining the geographical origin of wines is a major challenge in wine authentication, but little information is available regarding non-parametric statistical approaches for wines. In this study, we collected 33 domestic Chardonnay wines vinified on a small scale from grapes cultivated in Japan, and 42 Chardonnay wines imported from 8 countries, for oxygen stable isotope and multi-element analyses. Non-metric multidimensional scaling (NMDS), kernel principal component analysis (KPCA) and principal component analysis (PCA) were applied to the oxygen stable isotopic compositions (δ¹⁸O) and the concentrations of 18 elements in the wines to compare the extractions by parametric and non-parametric methods. The non-parametric methods, NMDS and KPCA, separated domestic from imported Chardonnay wines better than the parametric method, PCA. Of 19 variables, 18 were important for geographical discrimination, with the δ¹⁸O value being the most significant in all statistic methods. Non-parametric multivariate analyses will help discriminate domestic from imported Chardonnay wines.

X-ray Fluorescence Techniques for Element Abundance Analysis in Wine

The elemental composition has been extensively used to characterize wine and to find correlations with environmental and winemaking factors. Although X-ray fluorescence (XRF) techniques offer many advantages, they have been rarely used for wine analysis. Here, we show the comparison of wine elemental composition results obtained by total reflection X-ray fluorescence (TXRF) and energy dispersive X-ray fluorescence (EDXRF) for elements K, Ca, Mn, Fe, Cu, Zn, Br, Rb, and Sr. The results obtained by TXRF and EDXRF have been additionally verified by inductively coupled plasma-mass spectrometry. The important analytical features of XRF techniques in wine science have been described, the preservation of volatile elements (e.g., Br) being one of their main advantages. In addition, we have shown that XRF techniques offer an optimal analytical approach for building large data sets containing highly reliable and reproducible results of elemental abundances in wines, corresponding soils, and grape juice. Such data sets are especially important for the geographic authentication of wine. This has been shown for 37 Austrian and Croatian wines collected together with respective soils from selected wine regions. The element abundances in soil reflect in a large portion in grape juice and finished wine suggesting that the contribution of the soil, that is, the plant uptake capacity expressed as c _i(wine)/c _i(soil) concentration factors, can be a highly discriminating factor for wine fingerprinting. This indeed has been proved in the present study in comparison to discrimination based only on wine element abundances. We have identified Fe, Zn, Br, Rb, and Sr as the best discriminator elements for the geographical authentication of wine. The study opens a new perspective in extending the application of XRF techniques as a cost-effective analytical tool for creating large databases of soil, grape juice, and wine element abundances for the evaluation of soil characteristics and other environmental parameters on wine composition.

ICP–MS Analysis of Multi-Elemental Profile of Greek Wines and Their Classification According to Variety, Area and Year of Production

Major, minor and trace elements in wines from Greece were determined by inductively coupled plasma–mass spectrometry (ICP–MS). The concentrations of 44 elements (Na, Mg, P, K, Ca, Cu, Co, Cr, Zn, Sn, Fe, Mn, Li, Be, B, V, Sr, Ba, Al, Ag, Ni, As, Sn, Hg, Pb, Sb, Cd, Ti, Ga, Zr, Nb, Pd, Te, La, Sm, Ho, Tm, Yb, W, Os, Au, Tl, Th, U) in 90 white and red wines from six different regions in Greece for two consecutive vinification years, 2017 and 2018, were determined. Results for the elements aforementioned were evaluated by multivariate statistical methods, such as discriminant analysis and cluster analysis, and the wines were discriminated according to wine variety and geographical origin. Due to the specific choice of the analytes for multivariate statistical investigation, a prediction rate by cross-validation of 98% could be achieved. The aim of this study was not only to reveal specific relationships between the wine samples or between the chemical variables in order to classify the wines from different regions and varieties according to their elemental profile (wine authentication), but also to observe the annual fluctuation in the mineral content of the studied wine samples.

Vintage analysis of Chinese Baijiu by GC and 1H NMR combined with multivariable analysis

Economical-driven counterfeit and inferior aged Chinese Baijiu has caused serious concern of publicity in China. In this study, a total of 167 authentic Chinese Baijiu samples with different vintages including 3 flavor types were carefully collected. Gas chromatography (GC) was used to determine main volatile components and proton nuclear magnetic resonance (¹H NMR) spectroscopy was employed to obtain non-targeted fingerprints of Chinese Baijiu samples. Partial least squares regression (PLSR) models, which were confirmed by internal and external validation, were established for effectively identifying actual storage vintage of Chinese Baijiu with various brands, flavor types. Centering (Ctr), pareto scaling (Par), unit variance scaling (UV) data pretreatment methods, principal components (PCs), and three modified variable selection methods were proposed to successfully optimize the vintage model and effectively extract important vintage characteristic factors. This study demonstrated that NMR and GC combined with multivariate statistical analysis are effective tools for validating vintage authenticity of Chinese Baijiu.

Developing an authentication approach using SPME-GC-IRMS based on compound-specific δ 13C analysis of six typical volatiles in wine

An analytical method using gas chromatography isotope ratio mass spectrometry (GC-IRMS) combined with solid phase micro-extraction (SPME) was developed to measure the δ 13C values of six typical volatiles commonly occurring in wine (isoamyl acetate, 2-octanone, limonene, 2-phenylethanol, ethyl octanoate and ethyl decanoate) for the first time. SPME selected with a divinylbenzene/carboxen/polydimethylsiloxane fiber was combined with the GC-IRMS for pretreatment optimization. The optimized SPME parameters of extraction time, extraction temperature and salt concentration were 40 min, 40 °C and 10%, respectively. The δ 13C values measured by SPME-GC-IRMS were in good agreement with those measured via elemental analyzer (EA)-IRMS and GC-IRMS. The differences range from 0.02 to 0.44‰ with EA-IRMS and from 0 to 0.28‰ with GC-IRMS, indicating the high accuracy of the method. This newly established method measured the precision within 0.30‰ and was successfully validated to discriminate imported real wine samples with identical label but amazing price differences from different importers.

Geographical Discrimination of Croatian Wines by Stable Isotope Ratios and Multielemental Composition Analysis

The δ¹⁸O and δ¹³C (analyzed by isotope ratio mass spectrometry, IRMS) and concentration of 22 selected elements (analyzed by inductively coupled plasma—optical emission spectrometry, ICP-OES) in 190 Croatian microvinified and commercial wine samples from continental and coastal winegrowing areas and from three viticultural zones (B, CI, and CII) were measured to investigate whether multivariate statistical methods could provide the fingerprint for geographical origin determination. The highest power for discrimination of wines produced in Croatian winegrowing areas was achieved by general discriminant analysis (GDA) showing correct classification of 97.9% of all investigated samples, 100.0% of microvinified samples and 84.8% of commercial samples in the cross-validation matrix. The most significant markers for discrimination of coastal and continental areas found by GDA were δ¹⁸O and Co, followed by K, Rb, Sn, Li, and δ¹³C in descending order. GDA showed higher levels of correctly classified samples from three viticultural zones in Croatia if only microvinified samples were employed in the analysis (94.9%) than for all samples together (86.3%) or for commercial samples (66.1%) in the cross-validation matrix. The discrimination of viticultural zones B, CI, and CII in Croatia was achieved by δ¹⁸O, Co, Rb, Li, K, and Sn. The results obtained showed that the relationships between the isotopic ratios and concentrations of different considered elements combined with appropriate statistical model represent a powerful tool in discrimination of wines produced in different Croatian winegrowing areas.

Geographical Origin Classification of Chinese Wines Based on Carbon and Oxygen Stable Isotopes and Elemental Profiles

ABSTRACT

Wines from different regions have different qualities due to the impact of geographical location and climate. The sale of inferior wines seriously violates the fair-trade rights of consumers. This article provides an elemental analysis classification method for verifying the geographical origin of wines in the People's Republic of China. Inductively coupled plasma mass spectrometry, liquid chromatography isotope ratio mass spectrometry, and an isotope ratio mass spectrometer were used to analyze 142 wine samples collected from Helan Mountain, Xinjiang, Yunchuanzang, the Yanhuai Valley, and the Hexi Corridor regions. The data included elemental profiles, carbon isotope ratios (δ13C), and oxygen isotope ratios (δ18O). The results of multivariate analysis revealed that the geographical origin of wine is closely related to variations in elemental profiles and isotope ratios. Introducing δ18O and the elements Li, Mn, Ag, In, Th, Ta, and Re into the discriminant model yielded correct classification rates of the linear discriminant model of 90.8% for the training set and 87.3% for the test set.

HIGHLIGHTS

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.

The Use of Macro, Micro, and Trace Elemental Profiles to Differentiate Commercial Single Vineyard Pinot noir Wines at a Sub-Regional Level

The compositional authentication of wine is of great interest, as the geographic origin of the grapes is often associated with quality, uniqueness, and authenticity. Previous elemental fingerprinting studies mainly discriminated wines from different countries or regions within a country. Here, we report the use of element profiles to distinguish commercial Pinot noir wines from five sub-regional appellations or neighborhoods within one American viticultural area (AVA). Fifty-three single cultivar wines were collected over two harvests and analyzed using microwave plasma-atomic emission spectroscopy (MP-AES) and inductively coupled plasma-mass spectrometry (ICP-MS). Of 62 monitored elements that were quantified with fully validated methods, 24 and 32 elements differed significantly across the neighborhoods and vintages, respectively (p < 0.05). Targeted canonical variate analysis (CVA) explained 85–90% of the variance ratio across the two vintages, indicating persistent and stable elemental fingerprints of wines at a sub-regional level. A sixth, newly founded neighborhood was correctly grouped separately from the others using a Soft Independent Modeling of Class Analogy (SIMCA), indicating the potential of elemental fingerprints for wine authenticity.

Wine Authenticity and Traceability with the Use of FT-IR

Fourier transform infrared spectroscopy (FT-IR) has gained popularity in the wine sector due to its simplicity and ability to provide a wine’s fingerprint. For this reason, it is often used for authentication and traceability purposes with more than satisfactory results. In this review, an outline of the reasons why authenticity and traceability are important to the wine sector is given, along with a brief overview of the analytical methods used for their attainment; statistical issues and compounds, on which authentication usually is based, are discussed. Moreover, insight on the mode of action of FT-IR is given, along with successful examples from its use in different areas of interest for classification. Finally, prospects and challenges for suggested future research are given. For more accurate and effective analyses, the construction of a large database consisting of wines from different regions, varieties and winemaking protocols is suggested.

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.

Using neural networks to identify the regional and varietal origin of Cabernet and Merlot dry red wines produced in Krasnodar region

This paper shows a possibility of establishing the authenticity and geographic origin of wines by neural networks based on multi-element analysis. The study used 144 samples of Cabernet and Merlot dry red wines pro- duced in Krasnodar Region according to traditional technologies. The wines were provided by the producers or pur- chased in retail stores. The concentrations of 20 micro- and macroelements in red wines were determined by atomic emission spectroscopy with inductively coupled plasma. The analysis of average elemental contents showed a signi- ficant dependence of wine composition on the grape variety and place of origin, which enabled us to examine inter- relations between the elements and think of a way to identify them by means of classification models. The software STATISTICA Neural Networks was used to assess a possibility of determining the grape variety and geographical origin. The neural networks constructed in the study contained five variables corresponding to the elements with sta- tistically significant correlations between the names of the regions and the wine samples, namely Fe, Mg, Rb, Ti, and Na. These predictors were able to determine the grape variety and place of growth with a sufficiently high accuracy. In the test sample set, the accuracy reached 95.24% and 100% for variety and region identification, respectively. A software product was developed to automate the calculations based on the neural networks. The program can estab- lish the grape variety from a minimal set of microelements, and then, based on the variety and the same set of micro- elements, determine its place of origin.

Geographic classification of U.S. Washington State wines using elemental and water isotope composition

Wine fraud leaves wineries vulnerable to damage in reputation and potential lost revenue. To reduce this risk for wines from Washington State (WA), USA, advanced analytical instrumentation and statistical methods were employed to geographically classify 133 wines from 4 major wine producing regions, including 70 wines from WA. Analyses of 37 elements and 2 water isotopes were performed with Triple Quadrupole Inductively Coupled Plasma Mass Spectrometry and Cavity Ring-Down Spectroscopy, respectively. Linear discriminant analysis resulted in 96.2% discrimination, achieved with 11 parameters (Mn, Zn, Pb, Ni, As, D/H, La, Ce, Si, Zr and Sr) that were linearly combined into 3 functions. WA wines were uniquely distinguished in large part with low D/H ratios and Mn concentrations derived from the isotopically light precipitation and volcanic loess soils encountered in this region, respectively. This study is the first of its kind to focus on the authentication of WA wines.

Mineral Composition through Soil-Wine System of Portuguese Vineyards and Its Potential for Wine Traceability

The control of geographic origin is one of a highest priority issue regarding traceability and wine authenticity. The current study aimed to examine whether elemental composition can be used for the discrimination of wines according to geographical origin, taking into account the effects of soil, winemaking process, and year of production. The elemental composition of soils, grapes, musts, and wines from three DO (Designations of Origin) and for two vintage years was determined by using the ICP-MS semi-quantitative method, followed by multivariate statistical analysis. The elemental composition of soils varied according to geological formations, and for some elements, the variation due to soil provenance was also observed in musts and wines. Li, Mn, Sr and rare-earth elements (REE) allowed wine discrimination according to vineyard. Results evidenced the influence of winemaking processes and of vintage year on the wine’s elemental composition. The mineral composition pattern is transferred through the soil-wine system, and differences observed for soils are reflected in grape musts and wines, but not for all elements. Results suggest that winemaking processes and vintage year should be taken into account for the use of elemental composition as a tool for wine traceability. Therefore, understanding the evolution of mineral pattern composition from soil to wine, and how it is influenced by the climatic year, is indispensable for traceability purposes.

Discrimination of three Ephedra species and their geographical origins based on multi-element fingerprinting by inductively coupled plasma mass spectrometry

Discrimination of species and geographical origins of traditional Chinese medicine (TCM) is essential to prevent adulteration and inferior problems. We studied Ephedra sinica Stapf, Ephedra intermedia Schrenk et C.A.Mey. and Ephedra przewalskii Bge. to investigate the relationship between inorganic element content and these three species and their geographical origins. 38 elemental fingerprints from six major Ephedra-producing regions, namely, Inner Mongolia, Ningxia, Gansu, Shanxi, Shaanxi, and Sinkiang, were determined to evaluate the importance of inorganic elements to three species and their geographical origins. The contents of 15 elements, namely, N, P, K, S, Ca, Mg, Fe, Mn, Na, Cl, Sr, Cu, Zn, B, and Mo, of Ephedra samples were measured using inductively coupled plasma mass spectroscopy. Elemental contents were used as chemical indicators to classify species and origins of Ephedra samples using a radar plot and multivariate data analysis, including hierarchical cluster analysis (HCA), principal component analysis (PCA), and discriminant analysis (DA). Ephedra samples from different species and geographical origins could be differentiated. This study showed that inorganic elemental fingerprint combined with multivariate statistical analysis is a promising tool for distinguishing three Ephedra species and their geographical origins, and this strategy might be an effective method for authenticity discrimination of TCM.

Elemental profile and oxygen isotope ratio (δ18O) for verifying the geographical origin of Chinese wines

The elemental profile and oxygen isotope ratio (δ¹⁸O) of 188 wine samples collected from the Changji, Mile, and Changli regions in China were analyzed by inductively coupled plasma mass spectrometry (ICP-MS), inductively coupled plasma optical emission spectroscopy (ICP-OES) and isotope ratio mass spectrometry (IRMS), respectively. By combining the data of δ¹⁸O and the concentration data of 52 elements, the analysis of variance (ANOVA) technique was firstly applied to obtain the important descriptors for the discrimination of the three geographical origins. Ca, Al, Mg, B, Fe, K, Rb, Mn, Na, P, Co, Ga, As, Sr, and δ¹⁸O were identified as the key explanatory factors. In the second step, the key elements were employed as input variables for the subsequent partial least squares discrimination analysis (PLS-DA) and support vector machine (SVM) analyses. Then, cross validation and random data splitting (training set: test set = 70:30, %) were performed to avoid the over-fitting problem. The average correct classification rates of the PLS-DA and SVM models for the training set were both 98%, while for the test set, these values were 95%, 97%, respectively. Thus, it was suggested that the combination of oxygen isotope ratio (δ¹⁸O) and elemental profile with multi-step multivariate analysis is a promising approach for the verification of the considered three geographical origins of Chinese wines.

Trace metals transfer during vine cultivation and winemaking processes

BACKGROUND

The study was focused on Zn, Cu and Pb transfer in the system of soil-grape-must-juice-wine in a Chardonnay grape variety from Ukrainian vine growing regions. The analyses of soil, grape, must, pomace, juice and wine were done at the study plot in the south-west of Crimea.

RESULTS

Commercial white wines of Chardonnay from different vine growing regions in Ukraine were analysed for trace metals content. Results revealed that trace elements transfer was related to diverse Zn, Cu and Pb sources, trace metals bioavailability, their speciation and complexes during the wine making processes. The analysed commercial wines had lower Cu, Zn and Pb concentrations than wine from the Inkerman study plot.

CONCLUSION

Trace metals concentrations were comparable to those in European wines and lower than limits recommended by International Organization of Vine and Wine. The tentative relationship between wine and soil was found for Zn at the study plot. The method can be used to describe the relationship between the soil and wine in other study areas. © 2017 Society of Chemical Industry.

Elemental composition as a tool for the assessment of type, seasonal variability, and geographical origin of wine and its contribution to daily elemental intake

This study was designed to fill a gap, about Serbian wines, analysing 63 wines produced in 4 different regions in Serbia.