Classification of wines according to several factors by ICP-MS multi-element analysis

Integrating mineral elements and metabolite features to distinguish Lotus seeds from different geographic origins

The characteristics of lotus seeds (LS) are influenced by variety and environment. However, it remains unknown the difference of metabolites and elements of LS from different origins. In this study, an accurate quantification method (97-107 %) for 20 mineral elements in LS was developed, and a metabolomic method was established to identify a total of 323 metabolites in LS. Mineral composition analysis revealed significant variations in the mineral element contents among LS samples from seven geographical regions. LS were rich in potassium (14,710 mg/kg), manganese (67.19 mg/kg), with a low level of sodium (210 mg/kg). A total of 10 mineral elements and 117 metabolites (p < 0.05 and VIP > 1) were identified as the potential geographical markers of LS by integration analysis. The linear discriminant analysis model showed high prediction accuracy. This study provides strong experimental evidence to maintain the authenticity and quality of LS in the food industry.

Determination of Elemental Content in Vineyard Soil, Leaves, and Grapes of Sangiovese Grapes from the Chianti Region Using ICP-MS for Geographical Identification

To fight counterfeits and to protect the consumer, the interest in certifying the origin of agricultural goods has been steadily growing in the last years. While numerous works focus on the finished product, an aspect often overlooked is the origin of the raw materials and the direct correlation between chemicals in the soil and the plants. With inductively coupled plasma mass spectrometry (ICP-MS) analysis, trace and ultratrace elements in Sangiovese grapes (the main component of Chianti wine) were measured and their levels were used to investigate the geographical origin of the samples. This was achieved despite the extreme closeness of some of the vineyard partners of this study (10-20 km range) by computing a multivariate model using selected elements as levels. The model was then validated on samples coming from different zones of the Chianti area, with good results for discriminating even extremely close regions.

Potentials of dietary fiber and polyphenols in whole grain wheat flour to release the liver function and intestinal tract injury in lead-induced mice

The presence of lead as an environmental pollutant is widespread. However, safe and effective treatments for the resulting intestinal and liver damage from high levels of lead exposure remain limited. The study aimed to investigate the protective effects of dietary fiber and polyphenols in whole grain wheat flour on lead-induced mice. The results indicated that the daily intake of 12 mg of polyphenols, 0.5 g of dietary fiber, and their combination effectively reduced blood and liver lead accumulation by approximately 50 % in mice exposed to lead, while also mitigating lead-induced oxidative stress though a reduction in malondialdehyde levels and an enhancement in antioxidant enzyme activities including superoxide dismutase, catalase, and glutathione peroxidase. Furthermore, all three treatments enhanced cytokine secretion with the combined treatment exhibiting the highest efficacy. Specifically, the combination treatment decreased tumor necrosis factor-α and interleukin 1β by 56.78 %, 47.86 % in intestinal tissue while increasing increased interleukin 4 and interleukin 10 by 81.84 %, 145.14 %. Additionally, it promoted the expression of tight junction proteins like Zonula occludens-1, Occludin and Claudin-1. The study presented a potential strategy for alleviating liver and intestinal tract damage from high-dose lead exposure.

Authentication of selected white wines by geographical origin using ICP spectrometric and chemometric analysis

An important aspect of assessing the authenticity of wines is its geographical origin. The aim of the work is to authenticate by geographical origin according to the data of the ICP-spectrometric and chemometric analysis of elemental "images" of wines produced from white grape varieties Chardonnay, Riesling and Muscat grown in four regions of the Krasnodar Territory, Russia. The difference in the contents of Al, Ba, Ca and Rb in wines was found depending on the variety, and Al, Ba, Rb, Fe, Li, Sr - depending on the region of grape growth. Different models of the experimental data processing were used for attribution of the produced varieties of wine to the area of the grape's growth. The criterion for the quality of the constructed models was the accuracy of the attribution of a wine variety to the area of the grape's growth (%). Analysis of the elemental analysis data of 153 wine samples showed that in terms of attribution accuracy, automated neural networks (100 %) are preferred among machine learning methods, followed by support vector machines (98.69 %) and general discriminant analysis (94.77 %). The applied mathematical models enabled the revealing of the cluster structure of the analyzed wine varieties and their attribution to the area of a grape growth with high accuracy. Sr, Li and Fe concentrations in wines were found as the dominating predictors in the constructed models for definition of the geographical origin of wines. The combination of ICP-spectrometric analysis data with the capabilities of statistical modeling of machine learning methods focused on large-dimensional data made it possible to successfully solve small-dimensional problems of the definition of the geographical origin of wines by their elemental composition and variety.

Deep reinforcement learning classification of sparkling wines based on ICP-MS and DOSY NMR spectra

An approach that combines NMR spectroscopy and inductively coupled plasma mass spectrometry (ICP-MS) and advanced tensor decomposition algorithms with state-of-the-art deep learning procedures was applied for the classification of Croatian continental sparkling wines by their geographical origin. It has been demonstrated that complex high-dimensional NMR or ICP-MS data cannot be classified by higher-order tensor decomposition alone. Extension of the procedure by deep reinforcement learning resulted in an exquisite neural network predictive model for the classification of sparkling wines according to their geographical origin. A network trained on half of the sample set was able to classify even 94% of all samples. The model can particularly be useful in cases where the number of samples is limited and when simpler statistical methods fail to produce reliable data. The model can further be exploited for the identification and differentiation of sparkling wines including a high potential for authenticity or quality control.

Elemental Profile in Chicken Egg Components and Associated Human Health Risk Assessment

Egg is a food product of high nutritional quality, extensively consumed worldwide. The objectives of this study were the determination of the elemental profile in eggs (egg white, yolk, and eggshell), the estimation of the non-carcinogenic health risk associated with the presence of heavy metals in investigated egg samples, and the development of statistical models to identify the best predictors for the differentiation of egg components. The assessments were carried out in a total set of 210 samples, comprising home-produced and commercial eggs, using inductively coupled plasma mass spectrometry. The results suggested measurable differences amongst hen eggs coming from different husbandry systems. The statistical models employed in this study identified several elemental markers that can be used for discriminating between market and local producer samples. The non-carcinogenic risk related to the consumption of the analyzed egg samples was generally in the safe range for the consumers, below the maximum permitted levels set by Romanian and European legislation. Food contamination is a public health problem worldwide, and the risk associated with exposure to trace metals from food products has aroused widespread concern in human health, so assessing the heavy metal content in food products is mandatory to evaluate the health risk.

Measuring trace element fingerprinting for cereal bar authentication based on type and principal ingredient

This paper introduces a method for determining the authenticity of commercial cereal bars based on trace element fingerprints. In this regard, 120 cereal bars were prepared using microwave-assisted acid digestion and the concentrations of Al, Ba, Bi, Cd, Co, Cr, Cu, Fe, Li, Mn, Mo, Ni, Pb, Rb, Se, Sn, Sr, V, and Zn were later measured by ICP-MS. Results confirmed the suitability of the analyzed samples for human consumption. Multielemental data underwent autoscaling preprocessing for then applying PCA, CART, and LDA to input data set. LDA model accomplished the highest classification modeling performance with a success rate of 92%, making it the suitable model for reliable cereal bar prediction. The proposed method demonstrates the potential of trace element fingerprints in distinguishing cereal bar samples according to their type (conventional and gluten-free) and principal ingredient (fruit, yogurt, chocolate), thereby contributing to global efforts for food authentication.

Fluorescent and Colorimetric Dual-Mode Strategy Based on Rhodamine 6G Hydrazide for Qualitative and Quantitative Detection of Hg2+ in Seafoods

In this study, a rapid fluorescent and colorimetric dual-mode detection strategy for Hg²⁺ in seafoods was developed based on the cyclic binding of the organic fluorescent dye rhodamine 6G hydrazide (R6GH) to Hg²⁺. The luminescence properties of the fluorescent R6GH probe in different systems were investigated in detail. Based on the UV and fluorescence spectra, it was determined that the R6GH has good fluorescence intensity in acetonitrile and good selective recognition of Hg²⁺. Under optimal conditions, the R6GH fluorescent probe showed a good linear response to Hg²⁺ (R² = 0.9888) in the range of 0-5 μM with a low detection limit of 2.5 × 10^-2 μM (S/N = 3). A paper-based sensing strategy based on fluorescence and colorimetric analysis was developed for the visualization and semiquantitative analysis of Hg²⁺ in seafoods. The LAB values of the paper-based sensor impregnated with the R6GH probe solution showed good linearity (R² = 0.9875) with Hg²⁺ concentration in the range of 0-50 μM, which means that the sensing paper can be combined with smart devices to provide reliable and efficient Hg²⁺ detection.

Levels of Heavy Metals in Grapevine Soil and Leaf Samples in Response to Seasonal Change and Farming Practice in the Cape Winelands

Heavy metal toxicity is a major threat to the health of both humans and ecosystems. Toxic levels of heavy metals in food crops, such as grapes, can have devastating effects on plant health and the market value of the produce. Two important factors that may influence the prevalence of heavy metals in grapevines are seasonal change and farming practices. The objectives of this study were (i) to conduct a detailed pioneer screening of heavy metal levels in soils and grapevine leaf tissues in selected wine farms and (ii) to study the influence of season and farming on heavy metal levels in soils and grapevine leaf tissues. Soil and grapevine leaf samples were collected from demarcated areas in selected vineyards in the Cape Winelands region of South Africa. The sampling was conducted in winter and summer from the same sites. The soil and leaf samples were analysed using inductively coupled plasma mass spectrometry (ICP-MS) techniques. The pooled data from the farms practising conventional or organic farming showed that seasonal variation had no significant effect (DF = 1, 22; p > 0.05) on the heavy metal contents in the soil. When the soil data from the winter and summer months were compared separately or pooled, the influence of agricultural practice was well-pronounced in As (DF = 1, 22, or 46; p < 0.05) and Cu (DF = 1, 22, or 46; p <0.05). The agricultural practice greatly influenced (DF = 1, 22; p< 0.05) Cu, As, Cr, and Hg uptake, with little effect on Ni, Co, Cd, and Hg leaf contents. Generally, the heavy metals studied (Cr, Co, Ni, Zn, As, Cd, Hg, and Pb) were substantially below the maximum permitted levels in plant and soil samples, per the recommendations of the WHO and E_r indices, respectively. However, moderate contamination of the soils was recorded for Cr, Ni, Zn, and Pb. Remarkably, the Cu levels in the organic vineyard soils were significantly higher than in the conventional vineyards. Furthermore, based on the I_geo index, Cu occurred at moderate to heavy contamination levels.

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

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

Mass spectrometry in food authentication and origin traceability

Food authentication and origin traceability are popular research topics, especially as concerns about food quality continue to increase. Mass spectrometry (MS) plays an indispensable role in food authentication and origin traceability. In this review, the applications of MS in food authentication and origin traceability by analyzing the main components and chemical fingerprints or profiles are summarized. In addition, the characteristic markers for food authentication are also reviewed, and the advantages and disadvantages of MS-based techniques for food authentication, as well as the current trends and challenges, are discussed. The fingerprinting and profiling methods, in combination with multivariate statistical analysis, are more suitable for the authentication of high-value foods, while characteristic marker-based methods are more suitable for adulteration detection. Several new techniques have been introduced to the field, such as proton transfer reaction mass spectrometry, ambient ionization mass spectrometry (AIMS), and ion mobility mass spectrometry, for the determination of food adulteration due to their fast and convenient analysis. As an important trend, the miniaturization of MS offers advantages, such as small and portable instrumentation and fast and nondestructive analysis. Moreover, many applications in food authentication are using AIMS, which can help food authentication in food inspection/field analysis. This review provides a reference and guide for food authentication and traceability based on MS.

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.

Direct analysis of wines from the province of Lower Silesia (Poland) by microplasma source optical emission spectrometry

New microplasma source optical emission spectrometry (OES) for the determination of Na, K, Mg, Ca, and Zn in wine was developed. As the microplasma source, a solution anode glow discharge (SAGD) or a solution cathode glow discharge (SCGD) were employed. The diluted samples solutions (0.5-2%) were directly analyzed (no acid digestion required) and the detection limits of Na, K, Mg, Ca, and Zn were 0.015, 0.03, 3, 12, and 0.1 µg L^-1, respectively. The developed method was used for the analysis of wine samples from the province of Lower Silesia (Poland). It was found that 1) red wines were characterized by a higher content of K and Mg, 2) it was possible to discriminate between Regent and Pinot Noir grape varieties (both red) by the concentrations of K and Ca, 3) the concentration of Na in the analyzed wines was lower than that found in wines from other European countries.

Chemical Composition and Polyphenolic Compounds of Red Wines: Their Antioxidant Activities and Effects on Human Health—A Review

Red wine, an alcoholic beverage is composed of a spectrum of complex compounds such as water, alcohol, glycerol, organic acid, carbohydrates, polyphenols, and minerals as well as volatile compounds. Major factors that affect the levels of phenolic compounds in red wines are the variety of grapes and the storage of the wines. Among the constituents of red wine, phenolic compounds play a crucial role in attributes including color and mouthfeel and confer beneficial properties on health. Most importantly, phenolic compounds such as flavanols, flavonols, flavanones, flavones, tannins, anthocyanins, hydroxycinnamic acids, hydroxybenzoic acids, and resveratrol can prevent the development of cardiovascular diseases, cancers, diabetes, inflammation, and some other chronic diseases.

From Soil to Grape and Wine: Geographical Variations in Elemental Profiles in Different Chinese Regions

Elemental profiles are frequently applied to identify the geographical origin and authenticity of food products, to guarantee quality. The concentrations of fifteen major, minor, and trace elements (Na, Mg, K, Ca, Al, Fe, Mn, Cu, Zn, Rb, Sr, Li, Cd, Cs, and Ba) were determined in soils, “Meili” grapes, and wines from six regions in China by inductively coupled plasma mass spectrometry (ICP-MS). The elemental concentrations in these samples, according to the geographical origins, were analyzed by one-way analysis of variance (ANOVA) with Duncan’s multiple comparisons. The bioconcentration factor (BCF) from soil to grape and the transfer factor (TF) from grape to wine were calculated. Mg, K, Ca, Cu, Zn, Rb, Sr, and Ba presented higher BCF values than the other seven elements. The TF values of six elements (Na, Mg, K, Zn, Li, and Cs) were found to be greater than one. Moreover, the correlation of element content between the pairs of soil–grape, grape–wine, and bioconcentration factor (BCF)–environmental factor were analyzed. Significant correspondences among soil, grape, and wine were observed for K and Li. Two elements (Sr and Li) showed significant correlations between BCF and environmental factor (relative humidity, temperature, and latitude). A linear discriminant analysis (LDA) with three variables (K, Sr, Li) revealed a high accuracy (>90%) to determine the geographical origin for different Chinese regions.

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.

Biochar and fertilizer improved the growth and quality of the ice plant (Mesembryanthemum crystallinum L.) shoots in a coastal soil of Yellow River Delta, China

Coastal soil is an important land reserve that may be used to alleviate the shortage of cultivated land; however, this soil is stressed by saline conditions and nutrient deficiency. Biochar offers the potential to reclaim coastal soil, but the response of plant growth to biochar addition in salt-affected soil is species-dependent. In this study, the response of ice plant (Mesembryanthemum crystallinum L.), an economically valuable halophyte that grows in the coastal soil of the Yellow River Delta, to wood chip biochar (WBC) either alone or in combination with chemical fertilizer was investigated using a 90-day pot experiment. The WBC enhanced the growth of ice plants in the coastal soil, but combining it with chemical fertilizer did not increase its effect. The nutritional quality of the plants was improved by the addition of WBC, regardless of whether chemical fertilizer was applied; moreover, WBC amendment enhanced photosynthesis and reduced the oxidative stress of the plants. The ameliorated soil properties (e.g., soil organic matter and water holding capacity) and increased contents of available macronutrients (e.g., P and K) and micronutrients (e.g., Mg, Mn, B and Zn) resulting from soil amendment with WBC may have contributed to the enhanced growth and quality of the ice plants. Additionally, in soil modified with WBC, an increased abundance of beneficial taxa (e.g., Erythrobacter, Sphingomonas and Lysobacter) and a shift in the microbial community may also have helped to improve the growth and quality of the ice plants. The results of our study provide useful information for developing a biochar-based technology to use in combination with valuable halophytes to reclaim degraded coastal soil and enhance food security.

Metals in Brazilian family farming grapes and estimated daily intake

The aim of this study was to determine concentrations of metals in peel, pulp, and seeds of grapes obtained from family farms in Brazil, compare them to the maximum threshold levels and to evaluate the risk by estimating the daily intake (EDI). Grape samples were collected from farms and levels of Cd, Cr, Cu, Mn, Ni, Pb and Zn were assessed via ICP-MS. The highest metal levels were found in grape peels, Cu at the highest concentration (107.6 mg kg^-1). Cr, Cu, and Pb were found at concentrations which exceeded maximum threshold levels. The EDI of Cd, Cu and Pb through consumption of grapes for the assessed Brazilian population was 0.29, 1822 and 3.02 µg/kg bw/day, respectively. The EDI of Cu was above the Provisionary Tolerable Daily Intake (PTDI). Thus, there are possible health risks due to the occurrence of Cu in Brazilian grapes.

Voltammetric Determination of Lead and Copper in Wine by Modified Glassy Carbon Electrode

This paper describes the determination of Pb and Cu with a Nafion-modified glassy carbon electrode and MnCo₂O₄ nanoparticles as working electrode for anodic stripping voltammetry. Pb and Cu were accumulated in HCl/KCl (0.1 mol dm^-3) at a potential of -1.4 V (vs. Ag/AgCl electrode) for 480 s, followed by a linear sweep anodic stripping voltammetry (ASV) scan from -1.0 to +0.5 V. Under optimum conditions, the calibration curves were linear in the range of 0.01 - 8 and 0.01 - 5 mg dm^-3 for Pb and Cu, respectively. Effect of sample dilution, accumulation time and potential were optimized. A study of interfering substances was performed. A significant increase in current was obtained at the modified electrode in comparison with the bare glassy carbon electrode. The modified electrode was successfully applied for determination of Pb and Cu in wine samples after a simple preparation procedure. Pb and Cu content in wine was used for estimation of the target hazard quotient (THQ) values for minimal and maximal levels of the metals.

Stabilization of wines with polymers and new bio-based carbon materials

Wine is a complex product which changes its properties at every production stage, however due to the different processes which take place in the production stage can result into the formation of unwanted turbidity, deposition or can lead to distortion of taste. Despite the advances in improving wine stabilization processes, the search for new materials continues. The present work focuses on clarification of wines on the basis of new polymers and carbon materials obtained from bio-renewable raw materials and byproducts from the production of 2,5-hydroxymethylfurfural (5-HMF).

Prospect on Rare Earth Elements and Metals Fingerprint for the Geographical Discrimination of Commercial Spanish Wines

This paper presents a novel tool for Spanish commercial wine discrimination according to their designation of origin (PDO). A total of 65 commercial wines from different Spanish designation of origin (Alicante, Bullas, Campo de Borja, Jumilla, Castilla la Mancha, Ribeiro, Ribera de Duero, Rioja, Rueda, Utiel-Requena, Valdepeñas and Valencia) were characterized. The rare earth elements (REEs) content was determined by a high-temperature torch integrated sample introduction system (hTISIS) coupled to inductively coupled plasma mass spectrometry (ICP-MS). The REE content was used to draw characteristic PDOs radar charts. Results indicated that the REEs fingerprint provides a good prospect to discriminate the different Spanish PDOs, except for Alicante, Castilla la Mancha, Jumilla, Utiel-Requena and Valdepeñas. Finally, for those PDOs that were not properly distinguished, a second fingerprint obtained from Ba, Co, Cr, Mn, Ni, Pb and V content was used for discrimination purposes.

Fuzzy Divisive Hierarchical Associative-Clustering Applied to Different Varieties of White Wines According to Their Multi-Elemental Profiles

Wine data are usually characterized by high variability, in terms of compounds and concentration ranges. Chemometric methods can be efficiently used to extract and exploit the meaningful information contained in such data. Therefore, the fuzzy divisive hierarchical associative-clustering (FDHAC) method was efficiently applied in this study, for the classification of several varieties of Romanian white wines, using the elemental profile (concentrations of 30 elements analyzed by ICP-MS). The investigated wines were produced in four different geographical areas of Romania (Transylvania, Moldova, Muntenia and Oltenia). The FDHAC algorithm provided not only a fuzzy partition of the investigated white wines, but also a fuzzy partition of considered characteristics. Furthermore, this method is unique because it allows a 3D bi-plot representation of membership degrees corresponding to wine samples and elements. In this way, it was possible to identify the most specific elements (in terms of highest, smallest or intermediate concentration values) to each fuzzy partition (group) of wine samples. The chemical elements that appeared to be more powerful for the differentiation of the wines produced in different Romanian areas were: K, Rb, P, Ca, B, Na.

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

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.

Toxic levels of manganese in an acidic Cambisol alters antioxidant enzymes activity, element uptake and subcellular distribution in Triticum aestivum

In the Montado system, in Portuguese Alentejo region, some Eutric Cambisols are known to promote manganese (Mn) toxicity in wheat. Variation on bioavailable Mn concentration depends on soil acidity, which can be increased by natural events (e.g. waterlogging) or human activity (e.g. excess use of chemical fertilizers). The effect of increasing soil Mn on crop element uptake, element distribution and oxidative stress was evaluated on winter wheat (Triticum aestivum). Plants were grown for 3 weeks in an acidic Cambisol spiked with increasing Mn concentrations (0, 45.2 and 90.4 mg MnCl₂/Kg soil). Calcium (Ca), phosphorus (P), magnesium (Mg) and Mn were quantified in the soil solution, root and shoot tissues and respective subcellular fractions. The activity of the antioxidant enzymes ascorbate peroxidase (APX), catalase (CAT), glutathione reductase (GR), guaiacol peroxidase (GPX) and superoxide dismutase (SOD) were determined in extracts of wheat shoots and roots. Overall, increase in soil bioavailable Mn inhibited the uptake of other elements, increased the Ca proportion in the root apoplast, promoted the translocation of Mn and P to shoot tissues and increased their proportion in the shoot vacuoles. Wheat roots showed greater antioxidant enzymes activities than shoots. These activities decreased at the highest soil Mn concentration in both plant parts. Wheat roots appear to be more sensitive to oxidative stress derived from excess soil Mn and promote Mn translocation and storage in shoot vacuoles, probably in Mn and P complexes, as a detoxification strategy. Improvement in wheat production, in acidic soils, may rely on the enhancement of its Mn detoxification strategies.

Variation in the mineral composition of wine produced using different winemaking techniques

It has been reported that the concentrations of minerals in wines can be used to discriminate their geographical origin. However, some winemaking techniques may also affect the mineral concentration of the final product. In this study, we examined the effects of various winemaking techniques, including (i) fining, (ii) aging with oak tips, (iii) maceration with grape skins, (iv) chaptalization and acidification, and (v) yeast nutrient addition for alcohol fermentation, on the concentration of 18 minerals (Li, B, Na, Mg, Si, P, S, K, Ca, Mn, Co, Ni, Ga, Rb, Sr, Mo, Ba and Pb) in a total of 154 wine samples using grapes from different production areas. Among the various winemaking techniques, maceration with grape skin had the largest effect on mineral content, significantly changing the concentrations of 17 or 18 elements (B, Na, Mg, Si, P, S, K, Ca, Mn, Co, Ni, Ga, Rb, Sr, Mo, Ba and Pb). Fining treatment using bentonites had the second largest effect, altering the concentrations of 14 elements (Li, B, Na, Si, P, S, Ca, Co, Ga, Rb, Sr, Mo, Ba and Pb). However, in principal component analysis using all data (n = 154), the wine samples were clearly clustered according to grapes used in the experiments rather than the winemaking technique. In conclusion, some winemaking techniques significantly altered the concentration of some minerals in wine; however, the principal factor influencing wine mineral composition seems to be its geographical origin.

Quantification of manganous ions in wine by NMR relaxometry

Proton relaxation in model and real wines is investigated for the first time by fast field cycling NMR relaxometry. The relaxation mechanism unambiguously originates form proton interaction with paramagnetic ions naturally present in wines. Profiles of a white Chardonnay wine from Burgundy, a red Medoc, and model wines are well reproduced by Solomon-Bloembergen-Morgan equations. Relaxation is primarily governed by interactions with Mn²⁺. A straightforward model-independent quantification of the manganese ion concentration (down to few tens of μg/L) is proposed.

Digital image-based tracing of geographic origin, winemaker, and grape type for red wine authentication

This work proposes the development of a simple, fast, and inexpensive methodology based on color histograms (obtained from digital images), and supervised pattern recognition techniques to classify red wines produced in the São Francisco Valley (SFV) region to trace geographic origin, winemaker, and grape variety. PCA-LDA coupled with HSI histograms correctly differentiated all of the SFV samples from the other geographic regions in the test set; SPA-LDA selecting just 10 variables in the Grayscale + HSI histogram achieved 100% accuracy in the test set when classifying three different SFV winemakers. Regarding the three grape varieties, SPA-LDA selected 15 variables in the RGB histogram to obtain the best result, misclassifying only 2 samples in the test set. Pairwise grape variety classification was also performed with only 1 misclassification. Besides following the principles of Green Chemistry, the proposed methodology is a suitable analytical tool; for tracing origins, grape type, and even (SFV) winemakers.

Mineral composition of organic and conventional white wines from Italy

Despite of the increased interest of consumers for organic agro-food products and of the growing demand for organic wines, scientific literature reports a limited number of studies aimed to evaluate the chemical composition of organic wine with respect to conventional wine in terms of major and trace metals. In the present study the concentrations of 19 elements (Al, As, B, Ca, Cd, Co, Cr, Cu, Fe, K, Li, Mg, Mn, Na, Ni, Pb, Sr, V, and Zn) were determined in samples of white wines from Italy, conventionally and organically produced. No significant difference in the mineral composition was found between the two groups, except for Ni, which showed a higher concentration in organic wines. By comparing our data with data from literature it can be pointed out that there is no agreement among the results presented in the different studies referring to comparisons between organically and conventionally produced wines, concluding that the mineral composition of wines depends on factors different from organic/conventional production method.

Characterization and classification of wines according to geographical origin, vintage and specific variety based on elemental content: a new chemometric approach

A highly informative chemometric approach using elemental data to distinguish and classify wine samples according to different criteria was successfully developed. The robust chemometric methods, such fuzzy principal component analysis (FPCA), FPCA combined with linear discriminant analysis (LDA), namely FPCA-LDA and mainly fuzzy divisive hierarchical associative-clustering (FDHAC), including also classical methods (HCA, PCA and PCA-LDA) were efficaciously applied for characterization and classification of white wines according to the geographical origin, vintage or specific variety. The correct rate of classification applying LDA was 100% in all cases, but more compact groups have been obtained for FPCA scores. A similar separation of samples resulted also when the FDHAC was employed. In addition, FDHAC offers an excellent possibility to associate each fuzzy partition of wine samples to a fuzzy set of specific characteristics, finding in this way very specific elemental contents and fuzzy markers according to the degrees of membership (DOMs).

An accurate and sensitive analytical strategy for the determination of palladium in aqueous samples: slotted quartz tube flame atomic absorption spectrometry with switchable liquid-liquid microextraction after preconcentration using a Schiff base ligand

This study presents a green analytical method for palladium determination by slotted quartz tube flame atomic absorption spectrometry (SQT-FAAS) following switchable liquid-liquid microextraction (SLLME). Efficient extraction of palladium was facilitated by complexation with a Schiff base ligand, synthesized specifically for this study. A three-stage thorough optimization procedure was carried out to boost the absorbance output of palladium. Complex formation was the first stage, and parameters evaluated included buffer solution pH and amount, concentration of ligand, and mixing period. The amount of switchable solvent and concentration and amount of sodium hydroxide and acid amount were optimized in the second stage. Optimization of sample and fuel flow rates and SQT parameters completed the third stage of optimization, and all optimum parameters were used to determine analytical performance of the method. The method had a broad linear dynamic range, and the calibration plots showed good linearity with R² values greater than 0.9991. The limits of detection and quantification of the SLLME-SQT-FAAS method were 15 and 50 μg/L, respectively. The precision of the method, expressed as percent relative standard deviation, was below 9.0% for all measurements. Spiked recovery results performed for a palladium electroplating bath solution gave poor results when quantified against aqueous calibration standards. Matrix matching was therefore used to improve recovery results which ranged between 97 and 105% for four different spike concentrations.

Quantification of toxic metals during different winemaking stages

Heavy metals in beverages can constitute serious problems to human health. Consumption of wine may contribute to the daily dietary intake of pollutants, especially of toxic (heavy) metals. These compounds are also known as priority pollutants due to their potential toxic effects, if concentrations are not kept under allowable limits. Many characteristics such as: quality, origin, aroma and health safety of wine are influenced by environmental and anthropogenic factors. Hence, the contamination of wine by priority pollutants may occur at different stages of vine-growing, due to the application of agricultural chemicals, or at different stage of winemaking and ageing, because of the extended contact of wine with winemaking equipment materials (aluminium, brass, glass, stainless steel and wood, etc.), or chemicals used for cleaning and sanitation. The aim of this study is to identify and quantify the heavy metal ions from red wines. A particular focus was attributed to Zn and Cd from destemming-pressing-filtration-bottling stages in Fetească neagră grape variety from Cotnari vine growing region of Romania. Results indicated that heavy metals were linked to diverse Zn and Cd sources and complexes during the winemaking processes. Concentration of Zn and Cd were generally higher in must than in wine, although heavy metals concentrations were lower than the limits recommended by the International Organization of Vine and Wine for human health safety.