## 3 Results and Discussion
### Must, Wine and Wine  
The resulting yield obtained for the three protocols under study is represented in Table 2.  
One-Way ANOVA was conducted to compare the mean scores of _Cuvee_ must yield obtained across three different groups. The results indicated that there was no significant difference between the groups; F(2, 6) = 3.519, \(p\) = 0.097, \(\eta^{2}\) = 0.54. The volume of wine lees produced was also assessed in two stages, immediately after must clarification and after the end of alcoholic vniification, considered to calculate the final yield of the _cuvee_ wine produced. While the differences in _cuvee_ wine yield obtained after the unification process did not reach statistical significance (F(2, 6) = 1.617, \(p\) = 0.274, \(\eta^{2}\) = 0.324), it is still relevant to compare the mean values of the final cuveee wine yield. ARPEF achieved the highest mean yield (41.44%), suggesting that the application of PEF may result in a yield increase of +5.47%. In practical terms, this means that for every 100 kg of grapes, the producer can now obtain an additional 5.4 L of _cuvee_ wine. Surprisingly, while enzymes presented the highest percentage of volume extracted immediately after pressing, the final yield of _cuvee_ wine was the lowest, mainly due to the higher production of wine lees, combined with the highest variation in results obtained with enzymes (ARE). [PERSON] et al. 2020 also reported that no significant results were achieved when comparing the application of pectolytic enzymes for yield increase, with a combination of PEF and enzymes, on a white grape blend constituted by Gruner Veltliner and Traminer varieties [8]. However, several studies presented different conclusions. [PERSON] et al., 2007 performed on three white grape varieties (Muscalelle, Sauvignon and Semillon) and demonstrated an increase in total yield from 49-54% to 76-78% after applying a PEF protocol of 0.75 kV/cm and W \(\approx\) 20 kJ/kg [31]. [PERSON] et al. 2009 reported similar results (67% to 75%) in total yield for the variety Chardonnay when subjected to a PEF treatment of 0.4 kV/cm and W \(\approx\) 15 kJ/kg [48]. These contrasting conclusions may not only be attributed to the variations in the treatments applied to each grape mask but also to the inherent variability observed within the groups. Working with biological materials, such as grapes, can be challenging due to the difficulty in achieving complete homogeneity in the sample. Even when sharing a _terroir_, the variability of collected grape material cannot be completely overlooked, as individuals exhibit plasticity in response to their environment. This is explained by [PERSON] (1965) as the extent to which environmental factors influence the expression of individual traits in a genotype [49]. The unique combination of factors, such as light exposure, temperature [50], spatial soil variation among plant vines (including differences in hydric and nutritional conditions) and agricultural practices, exerts influence on each berry, resulting in varying compositions, even within the same cluster [51]. Total wine lees yield was obtained with the sum of wine lees measured over two different stages: after juice settling and after the end of AF. The results obtained translated in the highest yield of lees produced by the batch treated with pectolytic enzymes, 18.23 \(\pm\) 2.13%, with control and PEF-assisted batches demonstrating approximate values of, respectively, 14.11 \(\pm\) 0.65% and 14.78 \(\pm\) 2.08%. After performing statistical analysis, it is concluded that, \begin{table}
\begin{tabular}{c c c c c} \hline  & **Treatment** & _Cuvee_ **Must** & **Total Lees** & _Cuvee_ **Wine** \\  & **Protocol** & **Yield (\%)** & **Yield(\%)** & **Yield (\%)** \\ \hline ARC & - & 53.41 \(\pm\) 1.17\% & 14.12 \(\pm\) 0.38\% & 39.29 \(\pm\) 1.76\% \\ \hline ARE & 1.5 g/100 kg & 57.17 \(\pm\) 1.37\% & 18.23 \(\pm\) 1.23\% & 38.94 \(\pm\) 4.09\% \\ \hline ARPEF & 1 kV/cm; 2 kJ/kg & 56.21 \(\pm\) 1.13\% & 14.77 \(\pm\) 1.20\% & 41.44 \(\pm\) 1.87\% \\ \hline \end{tabular}
\end{table}