## 3 Results and Discussion
### Influence of the Foliar MeI and ACP-MeI Treatments on Must Volatile Compounds
For other aroma compounds, like hexyl acetate and methyl jasmonate, both MeJ treatments increased the concentration of hexyl acetate and decreased the concentration of methyl jasmonate with respect to the control samples. As regards the season factor, some compounds were found in greater quantities in 2019 and others in 2020 (Table 4). In 2019, the terpenoids: geraniol, geranic acid, and geranyl acetone; the C\({}_{13}\) norisoprenoids: \(\beta\)-ionone, and \(\beta\)-cyclocitral; the benzenoid compounds: 2-phenylethanal, eugenol, benzyl alcohol and the total benzenoid compounds; the alcohols: 1-octon-3-ol, and 2-ethyl-1-hexanol, and the total alcohols; the carbonyl compounds: heptanal, (E)-2-octenal, (E)-2-nonenal, (E,E)-2,4-hexadienal, (E,E)-2,4-nonadienal, and 6-methyl-3,5-heptadien-2-one, and the total carbonyl compounds; and the C6 compound: n-hexanal, were found in greater quantities than in 2020. On the contrary, in the second season, the terpenoids: limonene, and p-cymene and the total terpenoids; the C\({}_{13}\) norisoprenoids: (E) and (Z)-\(\beta\)-damascenone, and TDN, and the total C\({}_{13}\) norisoprenoids; the benzenoid compound: 2-phenylethanol; the alcohols: n-octonal, and n-nonanol; the carbonyl compounds: nonanal, and \(\gamma\)-declactone; the C6 compounds: n-hexanol, (Z)-3-hexel-1-ol + (E)-2-hexen-1-ol, and (E)-2-hexenal, and the total C6 compounds; and the hexyl acetate and methyl jasmonate were found in higher amounts than those from 2019. In this case, the treatment-season interaction was significant for all compounds except \(\beta\)-ionone, n-octonal, (E)-2-octenal, and (E)-2-hexenal (Table 4). In order to classify the different samples, discriminant analysis was performed on data expressing the concentration of volatile compounds in control, MeJ, and ACP-MeJ samples. The results are shown in Figure 4. In 2019 season (Figure 4a), Function 1 explained a very high percentage of variance 90.5% and Function 2 explained only 9.5%, so the total of variance explained was 100%. The variables that contributed the most to the discriminant model were \(\alpha\)-terpineol, 2-ethyl-1-hexanol, geraniol, and 1-hexanol (Function 1) and 2-ethyl-1-hexanol, geraniol, and TDN (Function 2). The discriminant model showed a good separation among the different samples. In the case of the data from 2020 (Figure 4b), Function 1 explained 89.8% and Function 2 explained 10.2%, (total variance explained = 100%). The variables that contributed the most to the discriminant model were: (Z)-3-hexen-1-ol, \(\beta\)-ionone, 2-phenylethanol, and 6-methyl-3,5-heptadiene-2-one for Function 1 and 2-phenylethanol, 2-ethyl-1-hexanol, and (E)-2-octenal for Function 2. Again, the discriminant showed a very good separation among the different samples. Figure 4c shows the discriminant analysis for both seasons, with treatment as factor. It can be observed that there is a good separation between the treatments. Function 1 explained 56.4% of the variance and Function 2 explained 43.6% (total variance = 100%). The variables with the highest contribution were p-cymene, and (E)-2-nonenal for Function 1, and heptanal, (E)-2-nonenal, and decanal for Function 2. Considering the sample as factor (Figure 4d), Function 1 explained almost all the variance 98.7%, and Function 2 only 0.7%, so the total of variance explained was 99.4%. Again, the discriminant shows a good separation between all samples. The variables that contributed the most to the discriminant model were (E)-\(\beta\)-damascenone, p-cymene, 1-octanol, and linalool for Function 1, and p-cymene, 2-phenylethanol, 1-octanol, and 1-hexanol for Function 2.