## 3 Results and Discussion
It must be mentioned that the influence of yeasts on the aromatic character of wines has been previously presented in various studies at an international level [8; 9; 41; 56; 57]. The values obtained within this study for the detected volatile compounds were compared with the literature, the results being consistent, proving that strains can enhance the aromatic profile of red wines. The volatile compounds codes for PCA analysis are highlighted in Table 1.  
Figure 5 displays the Pearson correlation coefficients between volatile phenols, alcohols, esters, and fatty acids identified in Pinot noir, Feteasca Neagra, Burgund Mare, Syrah, and Novac wines. This matrix indicates a strong positive correlation between V2 (4-vinylguaiacol) and A1 (1-hexanol) with a coefficient of 0.712, as well as between A4 (2-pentanol) and A5 (2-phenylethanol) with a coefficient of 0.688, suggesting that these compounds tend to increase together. The very strong positive correlation between E1 (3-nonenoic acid, ethyl ester) and E2 (ethyl cinnmate) with a coefficient of 0.929 suggests that these esters likely vary together, while the correlation between F1 (butanetioic acid) and E5 (diethyl succinate)  
Figure 4: Esters concentrations sum (\(\upmu\)g/L) in red wines obtained using commercial and native culture yeasts (ESFC, VS, SCR297, SCR462). with a coefficient of 0.567 reflects a moderate positive correlation. Negative correlations, such as V1 (tyrosol) and A4 (2-pentanol) with a coefficient of \(-\)0.605, A3 (2-nonanol) and F6 (isovaleric acid) with a coefficient of \(-\)0.696, and A5 (2-phenylethanol) and F4 (decanoic acid) with a coefficient of \(-\)0.586, indicate an inversely proportional relationship. Several moderate correlations (ranging from 0.3 to 0.6) are also observed, such as between A2 (2,3-butanediol) and E1 (3-nonenoic acid, ethyl ester) (0.553) and A7 (benzyl alcohol) and E3 (phenyl acetate) (0.640). Similarly, F5 (hexanoic acid) and F6 (isovaleric acid) show a moderate negative correlation of \(-\)0.388, indicating an inverse relation. Many of the fatty acids (F1 to F7) exhibit complex interrelations, with some showing strong negative correlations with alcohols and other classes. This suggests that the metabolic processes during fermentation with different yeast strains may lead to varying concentrations of these compounds. Understanding these correlations can provide insights into how different yeast strains affect the flavor profiles of wines by influencing the concentrations of specific volatile compounds. For winemakers, knowledge of these interactions can be crucial for crafting wines with desirable aroma and flavor profiles. Principal component analysis (PCA) was applied to determine the volatile compounds detected in wines produced using commercial and native yeast strains ESFC, VS, SCR297, and SCR462. In the PCA plot (Figure 6), the length of each eigenvector is proportional to the variation in the data for independent factors, and the angle between the eigenvectors denotes the correlation among wine, yeast strain, and volatile compound. \begin{table}
\begin{tabular}{c c} \hline
**Aroma** & **Code** \\ \hline tyrosol & V1 \\
4-vinylguaiacol & V2 \\
1-hexanol & A1 \\
2,3-butandiol & A2 \\
2-nonanol & A3 \\
2-pentanol & A4 \\
2-phenyl ethanol & A5 \\
3-methylthio-1-propanol & A6 \\ benzyl alcohol & A7 \\ e-3-hexenol & A8 \\ isopentyl alcohol & A9 \\ beta-linalool & A10 \\ n-amyl alcohol & A11 \\ n-propanol & A12 \\ terpineol & A13 \\ trans-geraniol & A14 \\
3-nonenoic acid, ethyl ester & E1 \\ ethyl cinnamate & E2 \\ phenyl acetate & E3 \\ ethyl lactate & E4 \\ diethyl succinate & E5 \\ ethyl hexanoate & E6 \\ ethyl butyrate & E7 \\ ethyl decanoate & E8 \\ butandioic acid & F1 \\ butyric acid & F2 \\ caprylic acid & F3 \\ decanoic acid & F4 \\ hexanoic acid & F5 \\ isovaleric acid & F6 \\ octanoic acid & F7 \\ \hline \end{tabular}
\end{table} 
Table 1: Volatile compounds codification for PCA.