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

Abstract

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.

Can Rare Earth Elements Be Considered as Markers of the Varietal and Geographical Origin of Wines?

“…The average minimum content of the total REE is observed in the BT samples of the fourth (7.93 µg/g), then the second (10.03 µg/g), the first (11.83 µg/g), and the third (12.32 µg/g) groups. BT significantly increases the content of REE in wine materials and there is a multiple increase in the concentrations of Ce (4-6), Y (2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19), and La (2-24) relative to their initial content in the wine materials, probably due to ion exchange (Table 2). The concentrations of Tm and Lu in the wine material of the Cabernet Sauvignon variety, Pr, Ho, Tm, and Lu in Merlot and Pr, Tb, Ho, and Tm in Moldova change the least.…”

“…In this case, the identification of the origin of wines is controlled by the characteristic components or elemental profiles (electrophoretic, chromatographic, and elemental) inherent to the studied sample of wine [1][2][3][4]. Due to the specificity of the obtained profiles, this approach makes it possible to determine the quality and affiliation of wines, to detect counterfeit products, and to identify wines by variety and origin [5][6][7].…”

Wine characterisation according to geographical origin using analysis of mineral elements and rainfall correlation of oxygen isotope values

“…Mg elements is a natural constituent taken up from soil by wine grape varieties, and may be taken from added carbonates (as deacidification) during the winemaking. Russian winemaking, based on traditional technology, also shows that Mg content in different varieties and regions is diverse (Temerdashev et al ., 2019).…”

The Influence of the Soil Profile on the Formation of the Elemental Image of Grapes and Wine of the Cabernet Sauvignon Variety

“…In many wine-producing countries of the world, the mineral composition is used as a tool for identifying the geographical origin of wines [6,7,[9][10][11][12][13][14]. This approach makes it possible to determine the quality of wines, identify counterfeits, and also identify wines by name and origin, due to the specificity of the resulting sample profiles [15][16][17][18].…”