## 3 Results
### Phenolic Compounds  
Phenolic compounds are very important flavor-active components of wine and they were fully characterized by HPLC-DAD. The absolute concentration of the analytes is not needed to perform multivariate statistical processing, thus the peak areas were treated as previously described in the Section 2.5. Principal Component Analysis (PCA) was performed on the resulting dataset in order to highlight the trends associated to the winemaking processes and time evolution. The PCA plots describing the phenolic compounds are shown in Figure 1 (the score plots are shown in Figure 1A,C,E and the loading plots are in Figure 1B,D,F). These exploratory PCA plots were obtained by re-grouping the samples in three main datasets: unfermented musts (scores in 1A and loadings in 1B), samples during the alcoholic fermentation and further stabilization (scores in 1C and loadings in 1D), and bottled wines (scores in 1E and loadings in 1F). This choice was due to two main reasons: (i) the overall variance in the dataset of the must samples (T0-T4) was much smaller than the one of the samples during/after fermentation (T5-T12); this lead to the separation between the clusters corresponding to V1 and V2 for T0-T4 (musts) which was discussed when analyzing the T0-T12 samples altogether, and (ii) the PCA performed on the samples after bottling allowed to evaluate directly the evolution of the wine over storage. A list of all the phenolic compounds identified (these last ones selected according to the PCA results and identified by further LC-MS/MS analysis or standard injections) is reported in Table 2. An example of a chromatogram is reported in Figure S1 left. In the PCA, two main trends corresponded to clear experimental factors as observed in the score plots in Figure 1A,C,E: vinvilation and time evolution. Beside a clear separation in observations caused by vinvilation (\"blue\" samples V1 vs. \"red\" samples V2) usually highly correlated to PC1, considering each vinvilation, a progressive trend in operation (time evolution) can be seen in all three score plots, albeit with different orientations with respect to the main separation along PC1. Whereas the score plots gave a distinctive overview of these trends (e.g., the separation in vinvilation clearly unfolds along PC1 and it highlighted here by choosing different colors for the sample labels), the loading plots showed which variables were most affected by these trends. In fact, in all three loading plots (Figure 1B,D,F), _trans_-caftaric acid (R.t. 28.0 min) was strongly correlated to PC1 with the effect of vinvilation. Conversely, a strong temporal trend could be observed clearly aligned to PC2 in Figure 1E and 1C, respectively. Astilbin (taxifolia-3-O-rhammoside) (R.t. 49.8 min) showed a strong correlation along PC2 for samples T5-T12 (Figure 1D). Astilbin is a flavonol which was previously observed in French varietal red wines in the presence of noble rot development, along with stilbene oligomers [22]. Taxifolin, too, was tentatively identified in the bottled wines (R.t. 50.8 min, see Table 2). For must samples (T0-T4) in Figure 1A, a clear separation between V1 and V2 was observed along PC1; this could be associated only to the effect of the pre-fermentative (cold) macceration of the V2 samples. Two variables contributed mostly to PC1 (separation in vinvilation) and PC2: _trans_-caftaric acid (R.t. 28 min) and astilbin (R.t. 49.8 min). Differently than later samples, no clear temporal trend was however observed along the second principal component. For fermentation/stabilization samples (T5-T12), both the separation by vinvilation and the time evolution could be observed. V2 samples at the middle/end of fermentation (T6 and T7) were however closer to the V1 samples than the other ones (Figure 1C); the temporal evolution was also observed, proceeding both for V1 and V2 as a trend from the upper-right quadrant to the lower-left quadrant in the Score plot (Figure 1C).