Zaual Akhloovich Temerdashev

To control the authenticity of wines based on geographic and varietal characteristics, relationships between the mineral composition of wine, grapes, and soil from the same growing area were identified. Grape samples of the Cabernet Sauvignon and Chardonnay varieties, grown and selected from three vineyards in the Anapa region of the Krasnodar krai, were studied. The mineralogical composition of the soil samples was studied using X-ray diffraction analysis and thermal analysis. The main phases were represented by calcite, quartz, feldspars, and clay minerals (illite and nontronite). The concentrations of Al, Ba, Ca, Cd, Co, Cr, Cu, Fe, K, Li, Mg, Mn, Na, Ni, Rb, Si, Sr, Ti, and Zn in soils, grapes, and wines were determined by spectrometric analysis with inductively coupled plasma. The distributions of total contet and mobile forms of elements in the soil profile were found different for K, Li, Mg, Fe, Cr, and Al. The concentrations of Na, Ca, and Sr increased with the depth of soil sampling, while the concentrations of Co, Ni, Cu, Pb, Fe, Zn, and Mn decreased. The results of elemental analysis of grape samples showed significant differences between different growing areas, although the differences between grape varieties were not as pronounced. The scatterplot of the values of canonical roots constructed based on the concentrations of elements using the discriminant analysis showed that grapes grown in different territories were localized in a certain part of the plane to form groups of homogeneous objects, that is, clusters. It was established that the nine elements Al, Ca, Cu, K, Mn, Na, Pb, Rb, and Sr can be used as predictors in the identification model of grapes.

This study examines the preparation of different soil types for polycyclic aromatic hydrocarbon (PAH) analysis, including preliminary extract purification by dispersive solid-phase extraction (dSPE) using the QuEChERS approach with various sorbents. We investigated the influence of soil matrix components and assessed the ability of different sorbents to minimize matrix effects during sample preparation. The study evaluated the performance of silica gel functionalized with N-propylethylenediamine groups (PSA), a mixture of PSA, octadecyl (C₁₈)-bonded silica gel, and magnesium sulfate (PSA–C₁₈–MgSO₄), magnesium silicate-based Florisil, and aluminum oxide for the purification of soil extracts before gas chromatography–mass spectrometry (GC–MS) determination of PAHs. The proposed analytical procedure was used using soils with different organic matter contents. Recoveries exceeded 75% for PAHs extracted from high-humus soils and 90% for those extracted from low-humus soils. The GC–MS limits of quantification for 19 PAHs after purification of extracts from high-humus soils with Florisil or the PSA–C₁₈–MgSO₄ mixture were 5–10 μg/kg.

The paper shows the effect of organic fining agents on the formation of the elemental composition of young white wine of the Chardonnay variety. Substances of plant and animal origin and their mixtures were used as fining agents in the clarification of wines. The results were compared with clarification with activated calcium bentonite. In the untreated young wines from different areas of grape cultivation the concentrations of macroelements were 707–837 mg/L; minor elements—5.05–9.67 mg/L; microelements—0.033–0.058 mg/L; and rare earth elements (REEs)—0.001–1.350 µg/L. It was noted that organic agents have a smaller effect on the mineral composition of wine. The content of macroelements in wine decreased, regardless of the fining agent used (p < 0.01). After treatment with organic agents, the concentrations of Ti, Sr, Na and Ca increased, while the concentrations of Cu, Zr, Mo, Cs, Ba, W, Fe, Rb and K decreased. No increase in the REE content was observed. A moderate correlation (Pearson r = 0.69, 95% CI: 0.44–0.85, n = 30, p < 0.0001) was established between the applied concentration of Na in wine and its concentration in the fining agent. Despite changes, the elemental “image” of wine allows us to correctly determine the geographical origin of the drink. The most reliable markers were Li and Mn.

Based on the elemental composition of 359 samples of dry wines (Riesling, Chardonnay, Muscat, Cabernet Sauvignon, and Merlot) produced in the Krasnodar Territory (Russia), the influence of data clustering on the generalizing properties of neural network models for solving classification problems was studied. Clustering as a property of predicted classes being compact and separate from each other was evaluated using scatterplots of canonical values from discriminant analysis and the Silhouette Score, Calinski-Harabasz, Davies-Bouldin, and Dunn metrics. With a decrease in data clustering, the generalization properties of neural network models decrease despite an increase in dataset size. Since the predictive properties of neural networks are primarily correlated with the clustering of data, it seems logical to say that their growth will occur when “quantity turns into quality”, that is, clustering will increase with increasing dataset size. The validity of the assumption explains the polarity of trends observed in literature. With the growth of training datasets, some researchers record improvements in the predictive properties of models, while others record deterioration. The results obtained are of great practical importance, as they indicate the unsuitability of unlimited data accumulation and allow optimizing the costs of collecting it, which is important, especially for food quality control.

To establish the relationship between the composition of wine and its regional origin, the most stable chemical parameters are selected because their variation is easiest to trace. Together with “classical” micro- and macroelements, rare earth elements (REEs) can be used for such purposes. However, the relationship between REE content in wine and its regional origin has not been systematically studied. This study examines the migration of REEs in the “soil-grape-wine” system to identify the relationship along the entire chain and establish the geographical origin of grapes and wine. The research was carried out on grapes and wines from the Chardonnay and Cabernet Sauvignon varieties, as well as soil samples selected from different vineyards. The concentrations of La, Ce, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb and Lu in the studied samples were determined using ICP-MS. It was established that the studied soil samples are characterized by relatively low REE concentrations. Low transfer of REEs from soil to grapes was observed because the soils are rich in clay minerals that firmly retain these elements. Statistically significant differences in the REE content of grapes from different regions were detected (p < 0.05). Multidimensional analysis methods allowed us to group grape samples into clusters based on varietal and regional origin. Discriminant analysis showed the possibility of using the concentration of REEs as markers of the geographical origin of grapes. Of all the REEs, only La and Ce are reliably established in all wines. When determining the geographical origin of wine, the use of REE content is limited due to their very low concentrations in wine. In this regard, it has been proposed to use them in combination with macro- and microelements, which improves the classification performance of the model.

The aim of this work is to study the correlations of the elemental composition in the “soil–grape–wine” chain to determine the regional origin of Chardonnay grapes and wine. Soil samples (n = 40) from five vineyards in the Anapa region, Russia, taken from eight different depths, grapes from these vineyards (n = 75), and wines obtained from these grapes (n = 5) were analyzed using inductively coupled plasma atomic emission spectrometry and inductively coupled plasma mass spectrometry. The mineralogical composition of the soils was determined using thermal and X-ray phase analysis. The mineralogical composition of vineyard soils mainly consists of calcite, quartz, nontronite, vermiculite, and muscovite. According to spectrometric analysis, the distribution of both the total content and the mobile forms of elements in soil profiles turned out to be similar. The content of Na, Ca, and Sr increased with increasing sampling depth, while the content of Co, Cu, Fe, Ni, Mn, Pb, and Zn decreased. Regardless of the area of cultivation, the predominant elements in grapes are K, Ca, Na, and Mg. It is established that the elemental profiles of grapes and wine are correlated. At the same time, during the winemaking process, a decrease in the concentration of most elements (Al, Ba, Ca, Cu, K, Mg, Mn, Ni, Rb, Sr, Ti, and Zn) is observed. It has been shown that the vine is able to accumulate not only mobile but also less bioavailable forms of metals from the soil (Cu, Fe, K, Rb, Ti, and Zn), while the migration of Ca and Na remains low (<7%). Using discriminant analysis, a model of grape identification based on the concentrations of Al, Li, Mn, Na, Pb, and Rb was developed. This model demonstrated a high accuracy (100% for training and test datasets) in grape classification by region, confirming that the elemental “fingerprint” is a reliable marker of terroir.

The work is devoted to the peculiarities of chlorine and lead determination in dust emissions of gas cleaning vents of electric steelmaking by energy-dispersive X-ray fluorescence analysis (EDXRF). A technique has been developed for the express energy-dispersive X-ray fluorescence determination of chlorine and lead in dust emissions of gas cleaning vents using powder model mixtures as standard samples similar in composition to real samples of dust emissions of gas cleaning vents. The analytes were determined using the characteristic ClKα1,2 and PbLα1,2 radiation lines. The possibility of reducing interfering effects of braking and characteristic radiation from the X-ray tube with an aluminum filter in the determination of chlorine, achieved by increasing the signal to background ratio for characteristic ClKα1,2 radiation line, is considered. The uncertainty of EDXRF method for determining chlorine and lead in dust emissions of gas cleaning vents was estimated using additional model mixtures. The calculation of accuracy indicators, repeatability limits, and intra-laboratory precision was carried out for energy-dispersive X-ray fluorescence determination of chlorine and lead in dust emissions of gas cleaning vents according to the obtained equations. It was shown that the results for chlorine determination in samples were overestimated (up to 7.7 %) relative to the accepted reference value if no filter was used, and were underestimated (up to 4.4 %) when the filter was present. For lead, the maximum deviation from the accepted reference value was 10.6 %. Constructed calibration graphs and pelleted model samples are stable for several months. Satisfactory consistency of the results of energy-dispersive X-ray fluorescence determination of chlorine and lead with data from standardized methods for analyzing real samples of dust emissions of gas cleaning vents was obtained; standard deviations did not exceed 13 % for lead and 11 % for chlorine. The proposed EDXRF method for the determination of lead and chlorine in dust emissions of gas cleaning vents is more efficient and less laborious.

Procedures for the identification and determination of a number of antioxidant, anticorrosive, and dispersant additives (ionol, diphenylamine, zinc dialkyldithiophosphate, and diester oil) in mineral hydraulic oils were proposed. They included preliminary solid-phase extraction of analytes on a cartridge with hydroxylated silica gel with the subsequent detection by reversed-phase high-performance liquid chromatography. The recovery of analytes was higher than 97%, and the limits of determination and detection of functional additives in mineral hydraulic oil were 0.001 and 0.0006 wt % for ionol, 0.01 and 0.008 wt % for zinc dialkyldithiophosphate, and 0.0005 and 0.00025 wt % for diphenylamine, respectively. It was established that Shell Tellus S2 V 46 mineral hydraulic oil contained 0.16% zinc dialkyldithiophosphate and 0.2% diphenylamine, and Total Hydragri ISO VG 46 contained 0.14% ionol and 0.17% zinc dialkyldithiophosphate. The molecular-weight characteristics of polymer additives to hydraulic oil were determined by gel permeation chromatography, and the concentration of a viscosity additive in a real sample was calculated. The procedures are appropriate for the determination of functional additives and the quality control of mineral hydraulic oil.

The results of microextraction separation and ICP–MS determination of inorganic arsenic species in natural waters are presented. The necessity of the separate quantification of analytes is justified, as arsenites exhibit toxicity dozens of times higher than arsenates. Separation was performed by the selective liquid–liquid microextraction of As(III) complexes with sodium diethyldithiocarbamate into an organic phase. Extraction conditions were optimized to achieve the highest recovery of As(III) complexes at approximately 95%. The As(III) complexes with sodium diethyldithiocarbamate were extracted into the organic phase using carbon tetrachloride as an extractant and methanol as a dispersant. Matrix effects of elements on analyte extraction from water were eliminated by performing a double microextraction of the analytes. Total inorganic arsenic and As(V) concentrations were determined by an ICP–MS analysis of the original water samples and their aqueous extracts obtained after the separation of inorganic arsenic species. The concentration of As(III) in water was calculated as the difference between total arsenic and As(V) concentrations. The limits of detection for As(III) and As(V) in water were equal, at 0.010 μg/L, within a linearity range of 0.05 to 100 μg/L, R² = 0.9998. The accuracy of the determination of inorganic arsenic species in water was confirmed by the standard addition method. The analytical procedure was validated using model waters and real samples of drinking and natural waters.

Specific features of the preconcentration and determination of polycyclic aromatic hydrocarbons (PAHs) in humus-rich soils by gas chromatography–mass spectrometry (GC–MS) are studied. The QuEChERS technique and dispersive liquid–liquid microextraction (DLLME) were employed to extract PAHs from soils using acetone and binary extractants of various compositions, including acetonitrile–dichloromethane, acetonitrile–acetone, acetone–hexane, acetone–chloroform, acetone–dichloromethane, and ethyl acetate–dichloromethane. Recoveries of low- and medium-molecular-weight PAHs using these solvent mixtures reached approximately 100%, while the acetone–dichloromethane mixture yielded over 90% recovery for high-molecular-weight PAHs. Under optimized GC–MS conditions with QuEChERS extraction, the limits of quantification (LOQ) for fluoranthene, pyrene, chrysene, and triphenylene reached 5 µg/kg, and for the remaining PAHs, 10 µg/kg in humus-rich soils. It was shown that the reliable GC–MS determination of lower concentrations of PAHs requires both the elimination of the matrix effect and the preconcentration of the analytes. The sequential application of QuEChERS and DLLME techniques enabled a decrease in the limits of quantification by GC–MS to 1.8 µg/kg for fluoranthene, pyrene, chrysene, and triphenylene, and to 3.5 µg/kg for the remaining PAHs. The optimized procedure for PAH determination in humus-rich soils was validated using real chernozem samples.