# The Impact of GoLo Technology on the Quality Properties of Dealcoholised Wines
## 3 Results and Discussion
### Volatile Compound Analysis
In other words, these results indicate a significant decrease in these aromas after the dealcoholisation process using GoLo technology. To determine correlations between significant oenological parameters (polyphenols and turbidity), the initial concentration of the different volatile compounds studied, and the total concentration of the volatile compounds in the different wines analysed, a correlation matrix was constructed between predictor variables for all the analysed wines. Correlations were considered significant for a Pearson correlation coefficient (r) of absolute value \(\geq\) 0.5, shown in Figure 6 with asterisks. The total concentration of volatile compounds according to the score showed a great correlation to total polyphenols (0.783), esters (0.853), and alcohols (0.718) and a lower one to norisoprenoids (0.516). Although there are no similar studies in the literature, it is related to the fact that they are the volatile compounds that are mostly found and have been studied in different types of wines [47]. Figure 6 also shows that there is a positive correlation between the total polyphenol content and alcohols (0.826) and esters (0.727) and a negative correlation with acids (\(-\)0.714). Likewise, the turbidity shows a slight positive correlation with alcohols (0.523) and a negative correlation with phenols (\(-\)0.536). The relationship between esters and alcohols may be influenced by the complexity of the fermentation processes or the synergistic effects of other compounds, such as pyruvate acid [48; 49]. The negative correlation between turbidity and phenols can be explained by the different oxidation processes, that can take place in wines, and which mainly affect phenolic groups [50] and the positive correlation by the amount of alcohol present that can generate precipitation processes increasing the turbidity of the wines [51]. Other less significant correlations, both in terms of their Pearson correlation coefficient value and their interpretation in the wines studied, were found between turbidity and phenols and alcohols, as well as acids with terpen, norisoprenoids, and phenols. To go further and determine if the total concentration of volatile compounds after the dealcoholisation process using GoLo technology is correlated with the volatile compound content, total polyphenols, and turbidity, a multiple linear regression analysis was per formed. The Akaike information criterion (AIC) was used as an estimator of prediction error and, thereby, the relative quality of statistical models was studied [52], resulting in the following linear equation:  
Concentration of total aromas (ng/mL) = \(-\)1.796 \(\times\) 10\({}^{3}\) + 27.25 \(\times\) PP\({}^{\star}\) (mg/L) + 1.856 \(\times\) 10\({}^{4}\)\(\times\) TURB (NTU) + 1.408 \(\times\) ALCOHOLS (ng/mL) \(-\) 990.3 \(\times\) ALDEHYDES (ng/mL) + 3.56 \(\times\) ACIDS\({}^{\star}\) (ng/mL) + 1.737 \(\times\)10\({}^{5}\)\(\times\) NORISOPRENOIDS\({}^{\star}\) (ng/mL) + 69.55 \(\times\) PHE NOLS (ng/mL)  
The linear equation has an adjusted R-squared of 0.828 with a \(p\)-value of 0.00029, and more significant terms (\(p\)-value < 0.05) such as the volatile compounds are marked with an asterisk (\({}^{\star}\)). The linear regression model, developed through several iterations using the AIC, has eliminated the terms related to esters and terpenes. These compounds are associated with the highest percentage of reduction listed in Table 4 for all types of wines analysed. Despite the significance of these compounds in contributing to volatile compounds and their connection to grape varieties [53], the model disregarded them due to the variability observed in the results (see Figures 4 and 5). For instance, compounds such as _cis_-linalo oxide, linalool, and nerolidol experienced varying degrees of loss during the dealcohlisation process. This behaviour was previously observed in dealcohlised Merlot red wine for linalool and nerolidol compounds [54].