No abstract

The present study continues the 2015–2016 research project on biological characteristics of stable isotopes fractionation in grapes taking into account the agro-climatic growth conditions of this representative of the C3-pathway of photosynthesis group of plants in different geographical Black Sea regions. The first parts of the project were presented at the 39th and 40th Congresses of OIV in Bento Gonçalves (Brazil) and Sofia (Bulgaria). The scientific data on compositions of 13C/12C carbon and 18O/16O oxygen stable isotopes in carbohydrates, organic acids, and intracellular water were obtained for grapes of 2015–2016 growing seasons in the four areas of the Crimean peninsula as well as in several areas of the Don Basin and the Western Caspian region. This report presents the results of the 2017 season study of 13C/12C carbon and 18O/16O oxygen stable isotopes in carbohydrates and intracellular water of 12 red and white grape varieties (Aligote, Rkatsiteli, Sauvignon Zeleny, Chardonnay, Cabernet Sauvignon, Sauvignon Blanc, Merlot, Risling, Pinot Noir, Cabernet Franc, Sira, Krasnostop) as well as in ethanol of wines made from corresponding grapes from the Crimean Peninsula and South-West Coast of the Greater Caucasus. To measure the ratio of carbon isotopes 13C/12C in grape (must) carbohydrates and wine ethanol the Flash-Combustion technique (FC-IRMS/SIRA) has been used, while the method of isotopic equilibration (EQ-IRMS/SIRA) has been used for the measurement of 18O/16O oxygen isotopes ratio in the intracellular water of grapes (must) and in the water fraction of wine. The GC-Combustion technique (GC-IRMS/SIRA) has been used for the first time to measure the carbon isotopes 13C/12C distribution in ethanol of studied wines. It has been found that the δ13CVPDB values for carbohydrates of red and white grape varieties as a result of biological fractionation of carbon isotopes in the agro-climatic conditions of plant growth (2017 season) for the studied geographical areas formed the following quantitative ranges: from − 26.72 to − 23.35‰ (the Crimean Peninsula) and from − 25.92 to − 23.87‰ (South-West Coast of the Greater Caucasus). The δ13CVPDB values for wine ethanol are in the following ranges: from − 28.15 to − 24.47‰ (the Crimean Peninsula) and from − 27.29 to − 25.78‰ (South-West Coast of the Greater Caucasus). The δ18OVSMOW values in intracellular water of grapes of the 2017 season range from − 1.24 to 2.17‰ (the Crimean Peninsula) and from 1.08 to 4.09‰ (South-West Coast of the Greater Caucasus). The results of this study show, in comparison with the results of studies of the 2015 and 2016 seasons, a decrease in the δ13CVPDB values for carbohydrates of grapes and ethanol of wine, which is explained by the changed climatic conditions of grapes growing in the vegetation period of 2017.

Рассмотрены методы оценки цвета вин на основе принципов органолептического анализа и оптической спектроскопии. Особое внимание уделено показателям хроматических характеристик вин: оттенок (T) и интенсивность (I) цвета, доля красной окраски (dA), доли красных (D 420), желтых (D 520) и синих (D 620) пигментов, угловой оттенок цвета (tg α), показатель желтизны (G). Существующие подходы к инструментальной оценке цвета преимущественно основываются на определении расчетных показателей с учетом значений оптической плотности при длинах волн 420, 520 и 620 нм. Показано, что основными их недостатками являются малоинформативность, сложность прикладного использования, противоречивость в интерпретации. Значительное влияние на визуальную оценку вин оказывают освещение и восприятие человека; отсутствие общепринятой классификации цвета, перечня терминов и понятий для его описания не позволяют сопоставлять результаты, полученные в разных исследованиях. Одним из альтернативных способов характеристики и описания цвета пищевых продуктов, в том числе вин, является трихроматическая модель CIELab, позволяющая не только воспроизводить цвет по установленным координатам с помощью конвертера цвета, но и оценивать колориметрическую разницу между образцами. Это представляет интерес, так как применение данной системы поможет унифицировать результаты оптического и органолептического анализов. Практическое использование метода может быть перспективным с точки зрения стандартизации органолептических показателей и воспроизведения продукции с заявленными характеристиками. Ключевые слова: вино, оптические показатели, интенсивность и оттенок цвета, модель CIELab.

Wines with a clear geographical origin are more attractive for customers. The geographical origin of wine is stated on its label, but no official standards guarantee its reliability. The present research objective was to analyze the existing methodological approaches to wine authentication. The study featured domestic and foreign publications indexed in Dimensions and Elibrary in 2017–2022 with such keywords as wine authentication, geographical origin of wine, and chemometrics. The research revealed no single methodological solution to wine authentication because food science knows a wide range of parameters, methods, analytical equipment, and data processing models. Chemometric methods are reliable because they are able to process large arrays of analytical research results structured in a data bank using the so-called fingerprint principle. They involve 2–65 markers that are individual for each geographical region, country, zone, or terroir. Another promising method is the quantitative and qualitative nuclear magnetic resonance spectroscopy (qNMR) of protons 1H and deuterium 2H(D) nuclei, as well as other elements (13C, 17O, 31P, 14N). The review resulted in an integrated approach based on a combination of isotopic testing with cation-anionic profiling. The analytical support involved the methods of atomic absorption and atomic emission spectroscopy, spectrometry with inductively coupled plasma, isotope ratio mass-spectrometry, and quantitative and qualitative nuclear magnetic resonance spectroscopy. This combined approach could provide background for an all-Russian state standard with a single algorithm for wine authentication tests. The new approach will be used to develop enochemical profiles of wines from a particular region, as well as to choose the most effective chemometric models for geographical authentication.

New methodological approach for rapid control of wine authenticity without sample preparation, based on the quantitative NMR spectroscopy (qNMR) of the protium 1H and deuterium 2H nucleus is suggested. The content of dominant (e.g. water, ethanol) and some minor (e.g. glycerol, organic acids) components of wine are determined from qNMR 1H spectra for authentication of molecular composition. The sum of all exchanging hydrogen atoms of wine's components provide the 1H signal with a chemical shift of 4.8 ppm. Accounting for their content from 1H spectrum allows us calculate the 2H isotopic content in wine water from integral intensity of corresponding signal in the 2H qNMR spectrum using an internal or external standard with a known content of the 2H isotope. The possible addition of water can be found from comparison of this value with values of surface and/or ground waters from corresponding viticulture areas. This approach was used for white and red wines from the Black Sea region (Krasnodar area & Crimea peninsula). The 2H contents in investigated wines range from 157 to 165 ppm. The maximum 2H isotope content in surface waters does not exceed 148 ppm. A qNMR measurement of wine according to the proposed approach takes some minutes, that significantly exceeds the laboriousness of methods based on IRMS/SIRA (e.g. δ13C, δ18O). The error of qNMR measurements is less than 2.0%. The qNMR screening of deuterium (2H) in ethanol can be used for detection of possible wine chaptalization. This approach is similar to the known SNIF-NMR method. The positive difference with this method is the use of minimal quantity of enriched 2H standard and measurement of integral intensities of all signals instead of heights. It allows to reduce measurements' time as well as to measure the 2H content of all fragments of ethanol molecules – CH3−, CH2−, OH-groups. The publication has been prepared with the support of the “RUDN University Program 5–100”.