## 3 Results
### Multiple Factor Analysis (MFA)  
#### 3.3.1 Pinot Gris Wines  
In Figure 5, the MFA model for Pinot Gris wines is presented, which includes all datasets joined in a unique model not influenced by the shear numerosity of the variables within the specific datasets themselves (as it would with PCA). In this case, these datasets are as follows: basic enological parameters, sensory attributes, volatile compounds, phenolic compounds, and proanthocyanidins. The results of the separate PCA conducted on each dataset allow for better understanding of the relationship between the observations and the variables. Figure 5A represents the projection onto the partial axes space representing a total variance of 40%. From the observations plot in Figure 5B, the analyzed wines from Argentina, South Africa (dry land), and New Zealand (Gisborne) were well separated along F1; however, analyzed wines from Italy (Sicily/Puglia), New Zealand (Marlborough), Italy (Veneto/Friuli), and South Africa (irrigated land) were close to each other and separated mostly in the F2. It can be clearly observed that the analyzed wines from Italy (Sicily/Puglia) were mostly separated due to the contribution of phenolic compounds, proanthocyanidins--F1, and % ratios of cyclic proanthocyanidins (c-PAC%)--F1. Similarly, phenolic compounds--F2 contributed to the separation of the analyzed wines from Argentina; c-PAC%--F2 and sensory attributes--F2 contributed to the separation of the wines from South Africa (dry land). The wines from New Zealand were separated due to the contribution of basic enological parameters--F2 and --F1, sensory attributes--F1, and the overall quality judgement (OQJ). Wines from Veneto/Friuli (Italy) were separated due to volatile compounds--F1, and the rest of the analyzed wines from South African from irrigated land were separated due to the contribution of volatile compounds--F1 and proanthocyanidins--F2. The residual sugars were the highest in the analyzed wines from New Zealand (Gisborne) and showed high correlation with these wines in Figure 5C. The total tittatable acidity, on the other hand, was highly correlated with the analyzed wines from Italy (Veneto/Friuli) and New Zealand (Marlborough). In terms of the sensory attributes, the analyzed Argentinian wine samples were characterized by \"green\" color, \"woody\" aroma, and \"warmness\", and showed anti-correlation with the OQJ while the wines from New Zealand (Gisborne) were strongly correlated with the OQJ, and were characterized by attributes, such as \"floral\" aroma, \"stone-fruit\" flavor, \"yellow\" color, \"caramelized\" aroma, and \"tropical fruit\" aroma. The volatile compounds that characterized the analyzed wines from New Zealand (Gisborne) were III: isobutyl alcohol, responsible for alcohol, pungent, solvent, or bitter aromas [29], XXVII: benzenebutanal, XXV: ethyl phenylacetate, esters responsible for fruit, sweet odors [30], and XXVI: phenethyl acetate, known for the contribution of fruity notes in wine [31]. In Figure 5F, the correlations of the distributions of the phenolic compounds with specific samples are shown. Only the compounds that show a higher correlation with the overall quality are highlighted. The full MS and fragmentations of the phenolic compounds from our analysis were compared with the current literature reports and, hence, were identified tentatively. The ions x57 (_m/z_ 157 at 6.7 min), x60 (_m/z_ 259 at 6.8 min), x79 (_m/z_ 175.1 at 7.6 min), x89 (_m/z_ 113 at 9.2 min), and x91 (_m/z_ 177 at 9.5 min) contributed in the separation of the analyzed Argentinian wines from other origins and showed a negative correlation with the OQJ, while ions x1 (_m/z_ 193 at 1.1 min), x29 (_m/z_ 391.1 at 4.3 min) x55 (_m/z_ 315.1 at 6.6 min), x61 (_m/z_ 311.1 at 6.9 min), x102 (_m/z_ 435.3 at 12.4 min), and x105 (_m/z_ 449.2 at 14.2 min) showed a higher contribution in the separation of the analyzed wines from New Zealand (Gisborne) and were positively correlated with the OQJ.