## 3 Results
### Effect of the Type of Closure through Compositional Data Analysis
Since high concentrations of amines are difficult to remove, it is crucial to monitor their production. Amines with secondary amino groups, like dimethylamine, can lead to the formation of nitrosamines or other harmful substances [41]. On the contrary, ethyl ocanoate \((x_{9})\) was higher in the cork-stopper group. This ester compound is responsible for fruity and floral-like aromas, as commented previously. A similar pattern was observed for other volatile compounds such as isoamyl alcohol \((x_{11})\), lactamide \((x_{12})\) and 4-(2,3,6-Trimethylphenyl)-1,3-butadiene \((x_{3})\). On the other hand, the bar plot suggests that the values of octanoic acid \((x_{13})\) and alpha-ionone \((x_{16})\) are very similar in the two subgroups. A non-parametric MANOVA [74] contrast applied to the clr-scores data set confirms significant differences (\(p\) < 0.05) between the centers of cork-stopper and screw-cap closures. In this case, the homogeneity cannot be accepted, but the screw-cap group has large dispersion and a large number of samples, and the test became conservative [75]. For comparing the centers of the two groups, the bootstrap 95% percentile interval for each part is provided (Figure 6). Figure 6 shows that only intervals of the parts 1,1,5-Trimethyl  
Figure 5: Geometric-mean bar plot comparing the compositional mean of the entire sample with the compositional mean of aromatic compounds subgroups for cork stoppers and screw-cap closures. Cork stoppers are Cork 1 and Cork 2 samples. Screw caps are CC1, CC2, CC3 and CC4). 1,2-dihydronaphthalene (\(x_{1}\)) and octanoic acid (\(x_{13}\)) have a zero value (horizontal dashed line), which means no differences between the two types of closures. All the other parts do not contain the zero value indicating differences. The larger ones in the dimethylamine (\(x_{6}\)) and ethyl octanoate (\(x_{9}\)) parts are also observed in Figure 5.  
The variability of the data is displayed in Figure 11 (Appendix A), within the variation matrix, illustrating both the variance and the mean of each pairwise log-ratio. The highest variances are highlighted using a red-shaded background, while the lowest are indicated with a blue-shaded background. Additionally, the total variance and the variance of each clr component are also provided. Globally, the total variance is 51.13. Screw-cap closures exhibit higher total variance (46.46) compared to cork stoppers (13.04), showing heterogeneity between groups. Examining the pairwise log-ratios, it becomes evident that both globally and within each subgroup, the log-ratios with the highest variance are those containing the dimethylamine (\(x_{6}\)) part. However, in the screw-cap subgroup, log-ratios containing the carbon dioxide (\(x_{4}\)) part also display high variability. Furthermore, in both subgroups and globally, the log-ratios involving phenylethyl alcohol (\(x_{15}\)) and alpha-ionone (\(x_{16}\)) exhibit low variability. Figure 7 shows the compositional clr-biplot, with cork closures in red and screw closures in blue, simplifying a comparison between the subgroups. The biplot retains a relevant portion of the total variability (78.34%), ensuring the high quality of the representation. In Figure 7, the conclusion mirrors earlier findings, highlighting a clear separation between subgroups and the higher variability of the screw-cap closures group (blue). We can see the volatile compounds' characteristics associated with cork closures, such as \(x_{3}\), \(x_{9}\) and \(x_{11}\), as well as other compounds' characteristics linked to screw-cap closures such as \(x_{14}\) and \(x_{4}\), exhibiting opposite directions relative to the PC1 axis. A second compositional data analysis was carried out using all types of stoppers as subgroups (n = 6 for Cork1, CC1, CC2, CC3, CC4 and n = 7 for Cork2). The centers of each subgroup, displayed in Table 13 (Appendix A), and the geometric-mean bar plot in Figure 8, allow us to compare the compositional mean of the entire sample with the compositional mean of each type of closure.