Data on the sensory evaluation of the dry red and white wines quality obtained by traditional technologies from European and hybrid grape varieties in the Krasnodar Territory, Russia

The analysis of data on the sensory evaluation of the quality of wines obtained using traditional technologies in the Krasnodar Territory, Russia, was carried out using the statistical ranking criteria – the Spearman and Kendall correlation coefficients, as well as the positional analysis – Cronbach's alpha. Data on the sensory evaluation of 60 samples of natural dry red and white wines are presented, among which 20 are white wines, 40 are red wines produced in 2010–2015. Eleven specialists aged between 32 and 66 years (the average age was 50 years; 4 females and 7 males) participated in the sensory evaluation procedure. All participants are considered experts in the field of wine, work in the wine industry and have professional experience in the field of sensory analysis. The results of the consistency study of expert evaluations, the reliability of the general score scale, as well as the analysis of the loyalty of experts in the wine quality assessment are presented in the article. The reliability of the proposed loyalty scale is shown, i.e., the scale of the sum of scores given by each expert in the evaluation of the quality of wines. The database on the sensory evaluation of the quality of wines, obtained for all wine samples using positional analysis, makes it possible to assess the contribution of each of the 60 wine samples to their ranking by mean scores. The data may be of interest to scientists and oenologists for the wine quality assessment.

of wines. The database on the sensory evaluation of the quality of wines, obtained for all wine samples using positional analysis, makes it possible to assess the contribution of each of the 60 wine samples to their ranking by mean scores. The data may be of interest to scientists and oenologists for the wine quality assessment.
© 2021 The Author(s Samples of natural red and white wines were analyzed, among which the first 20 were white wines, the remaining 40 were red. Eleven specialists aged between 32 and 66 years (the average age was 50 years; 4 females and 7 males) participated in the sensory evaluation procedure. All participants are considered experts in the field of wine, work in the wine industry and have professional experience in the field of sensory analysis. Data source location The wines were produced in 2010-2015 in the Krasnodar Territory, Russia by industrial producers (alcohol content -9-13% by volume, acidity -4-7 g/dm 3

Value of the Data
• The data provide insight into the problems and solutions of statistical analysis of the sensory evaluation and establishing the consistency of expert evaluations of wine quality. • Comparing to the traditionally applied Spearman correlation coefficient and Kendall coefficient of concordance, the Cronbach alpha criterion of the positional analysis is calculated using the initial score scale taking into account its variability and allowing to evaluate the contribution of each expert to the consistency of expert evaluations and determine the reliability of the total score scale for each wine sample. • The data can be compared with publications of other authors and/or used in comparative analysis and expert evaluation of the quality of wines.

Data Description
Data processing of the sensory evaluation of wine quality has been carried out by various statistical methods -analysis of variance (ANOVA) [1][2][3] , principal component analysis (PCA) [4] , discriminant analysis [5] , mapping on the Cartesian plane [6] , regression analysis [7 , 8] , statistical text analysis using Alceste [9] , etc. Expert methods for data processing, which describe the procedure for the sensory evaluation of wines [3 , 10-15] , have a number of limitations. The results of the sensory evaluation of wines are influenced by the composition of experts, their qualification level and quantity as well as imbalance of wines. Individual characteristics inherent in each expert along with their physical and psycho-emotional state also contribute to the subjectivity of expert evaluations. In the present paper, the problems associated with analyzing the consistency of expert evaluations of wine quality, establishing the contribution of each expert to the total consistency and reliability of the total score scale for wine samples set by each expert have been considered. To process expert evaluations, Table 1 was created containing the scores set by 11 experts based on the results of organoleptic evaluation of 60 samples of white (samples 1-20) and red dry (samples 21-60) wines. The top row contains the number of experts, the first column is the sample number, the second and subsequent columns are expert scores of the wine quality, the last column is the sum of expert scores. The calculations were conducted using the STATISTICA software [16] .
The obtained values of descriptive statistics of expert evaluations, including mean values (Mean, Median) and their ranges (Minimum, Maximum), interquartile ranges (Lower Quartile, Upper Quartile), standard deviation (Std.Dev.), are given in Tables 2-4 for all wines and separately for white and red wines.
The positional analysis of the results of organoleptic evaluation of the tested wine samples, carried out by the Reliability/Item Analysis module, allowed to calculate the Cronbach's alpha value equal to 0.843. This indicator, calculated according to the initial point scale taking into account its variability, made it possible to assess the contribution of each expert to the consistency of expert assessments. The closeness of Cronbach's alpha to 1 characterizes the reliability of the total score scale (column Sum, Table 1 ), hence the consistency of expert assessments, as high. Cronbach's alpha values, calculated with successive deletion of the assessments of experts 1, 2, 3,…, 11, allowed to determine the influence of each expert on the overall consistency of expert assessments. If Cronbach's alpha exceeds 0.843, then the expert reduces the overall consistency of expert assessments, otherwise increases it. Experts 1, 2, 3, 4, 5, 8, 9, 10, 11 were established to increase the overall consistency of assessments, while experts 6 and 7 reduced it.
During Reliability/Item Analysis module implementation, a matrix file of the Pearson pairwise correlation coefficients was formed characterizing relationships between expert evaluations ( Table 5 ).
Using pairwise correlation coefficients ( Table 5 ) and designating the group of experts decreasing the consistency of evaluations as "reduce" (6,7), while the group of experts increasing the consistency of evaluations as "increase", it can be seen that experts form the groups of homogeneity (clusters) in relation to their contribution to the consistency of evaluations. As can be seen from Fig. 1 constructed by principal component analysis (PCA), experts increasing the consistency are located on the central and left parts of the diagram, while those, which decrease the consistency, are on the right part of it.
The reliability of the total scale of scores (column Sum) and average scores given by experts (column The average) were assessed ( Table 6 ) by positional analysis of transposed Table 1 . The aggregate of average scores given by experts (column The average) is defined as the loyalty scale of experts. With the increase in the average value, the loyalty increases, otherwise the loyalty decreases.
Positional analysis of transposed data from Table 1 made it possible to evaluate the contribution of each of the 60 wine samples to the reliability of the loyalty scale ( Table 7 ). Cronbach's alpha values after successive removal of wine samples from positional analysis allowed to isolate samples reducing/increasing the reliability of the loyalty scale. Samples 1, 12, 22, 25, 29, 32, 33, 34, 38, 42, 46, 47, 48, 49, 52, 53, 54, 55, 56, 60 (in bold italics) decrease the reliability of the loyalty scale, the rest -increase.

Research objects
60 samples of natural dry red and white grape wines produced in 2010-2015 in the territory of main wineries of Krasnodar region (Russia) were analyzed: "Myskhako", "Fanagoria Number Reserve", "Kuban-Vino", "Southern wine company (SWK)", "Villa Victoria", "Chateau Tamagne",  "Chateau le Grand Vostock". All the wine samples were produced according to traditional technologies from European (Cabernet, Merlot, Aligote, Riesling, Saperavi, etc.) and hybrid grape varieties (Bianca, Viorica, Moldova, Pervenets Magaracha, etc.) and were kindly provided for research by their manufacturers. The wines were poured into dark green glass bottles with screw caps and stored until use at 10 °C. All wine samples were dry, alcohol content varied from 9 to 13% (v/v) and pH values ranged from 3.61 to 3.79. Dissolved oxygen in wines was measured by the immersion of the probe before bottling in barrels, which was less than 1 mg/dm 3 . Wines from European grape varieties obtained by traditional technologies without the use of sulfur dioxide were not considered, since this category significantly differs in taste from wines for which sulfiting was used.

Sensory analysis
All experimental studies related to sensory analysis were carried out by 11 specialists from the Federal Research Center for Horticulture, Viticulture, Winemaking (FSC HVW, Krasnodar, Russia). Participants are considered experts in the field of wine, work in the wine industry and have professional experience in sensory analysis.
The wine sample (50 cm 3 ) was poured into each glass and covered with a Petri dish with diameter of 5.7 cm 30 min before the sensory evaluation. The tests were carried out in a welllit tasting room with controlled temperature conditions. All samples were fed at 16-22 °С at tables with white napkins. Experts were prohibited to communicate during the sensory evaluation  procedure. The wines were served in transparent tulip-shaped glasses with a volume of 220 dm 3 . After evaluating each sample, participants were asked to wait at least 30 s, cleanse their palettes with water and crackers. The intervals between tasting of each sample were 2 min. During each interval, experts rinsed their mouths with water. Experts evaluated each sample in triplicate during the working week.
The sensory evaluation results of wine quality were expressed on a scale from 50 to 100 according to the well-known rating system [12] . According to this system, any wine sample is given 50 points, and based on the results of the sensory evaluation, the following maximum points can be added: appearance -up to 5 points, aroma -up to 15 points, taste -up to 20 points, overall impression and capability of aging -up to 10 points. For a consolidated assessment of the organoleptic characteristics of wines, the average scores of sensory evaluations were used according to the results of tasting by a group of experts.
In Russia, official methods for the sensory evaluation of wines express the results as points or use descriptive characteristics in terms of organoleptic indicators (transparency, color, aroma, taste). Ten or 100-point score scales are used. The 100-point system is used, as a rule, at international tasting competitions.

Data analysis
All calculations were implemented using the STATISTICA software (v. 10) [16] . The pairwise consistency of experts was determined using Spearman's rank correlation coefficient, the "individual" consistency was established by the multiple correlation coefficient, group consistency -by means of Kendall's concordance coefficient and Cronbach's alpha criterion (Reliability and Item Analysis). However, the listed statistical criteria for the consistency of expert evaluations -Spearman's rank correlation coefficients, Kendall's and Kronbach's alpha correlations do not have generally accepted ranges of variation for their interpretation in the nominal scale, therefore, we focused on the degree of their proximity to 0 and 1. If the value of the criteria is closer to 0, the consistency is lower; following this trend, if the value is closer to 1, the consistency is higher. Scatter plots for experts and wine samples were built using the Multidimensional Scaling module.

Ethical Statement
All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. All participants gave their consent in this experiment. No additional regulations were required.

Declaration of Competing Interest
The authors declare that they have no known competing financial interests of personal relationship that could have appeared to influence the work reported in this paper.