## 2 Results
### Untargeted LC-MS/MS Fingerprinting  
In total, more than one hundred compounds were tentatively identified with the untargeted LC-HRMS/MS analysis. These metabolites were classified as phenols (43%), amino acids and their derivatives (5 and 12%, respectively), organic acids (4%), lipids (4%), carbohydrates (3%), and several other metabolite categories (Figure 3). Phenolic compounds of interest concerning GRBD were further classified into flavonoids (13%), flavan-3-ols (7%), anthocyanins (6%), phenolic acids (5%), stilbenes (4%), anthocyanin (2%), flavones (1%), and other categories. A detailed list of tentative identifications from the untargeted metabolomic study is included in the Supplementary Materials (Table S1). A principal component analysis (PCA) of LC-HRMS/MS data showed a greater separation between wine vintage (2018 and 2019) compared to treatment (ABA and CON), with no apparent separation of treatment groups within each year (Figure 4). This observation suggested no overall effect of ABA application on nonvolatiles in wines produced from GRBV-positive vines. Several compounds were found to differ between treatment groups, eight compounds in 2018 \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Compound 1**} & \multicolumn{2}{c}{**Vintage 2018**} & \multicolumn{4}{c}{**Vintage 2019**} \\ \cline{2-7}  & **ABA** & **CON** & \(\boldsymbol{p}\)**-Value 2** & **ABA** & **CON** & \(\boldsymbol{p}\)**-Value 2** \\ \hline \multirow{2}{*}{\begin{tabular}{c} linalool \\ nerol \\ \(\alpha\)-terpinol \\ total \\ \end{tabular} } & 8.4 \(\pm\) 0.3 \({}^{\text{a}}\) & 9.6 \(\pm\) 0.8 \({}^{\text{b}}\) & 0.006 & 7.7 \(\pm\) 0.2 & 9.3 \(\pm\) 2.1 & 0.084 \\  & 9.1 \(\pm\) 2.9 \({}^{\text{a}}\) & 5.1 \(\pm\) 2.1 \({}^{\text{b}}\) & 0.020 & 3.0 \(\pm\) 0.1 & 3.8 \(\pm\) 1.1 & 0.129 \\  & 3.8 \(\pm\) 0.2 & 4.0 \(\pm\) 0.6 & 0.524 & 4.5 \(\pm\) 0.6 & 4.9 \(\pm\) 1.1 & 0.399 \\  & 60 & 57 & 44 & 47 & 47 & \\ \hline \multirow{6}{*}{\begin{tabular}{c} l l} \hline \hline \multirow{2}{*}{\
\begin{tabular}{c} l l l l l l} \hline \hline \multirow{2}{*}{**Compound 1** \\ \(\alpha\)-terpinol \\ total \\ \end{tabular} } & \multicolumn{2}{c}{**Vintage 2018**} & \multicolumn{4}{c}{**Vintage 2019**} \\ \cline{2-7}  & **ABA** & **CON** & \(\boldsymbol{p}\)**-Value 2** & **ABA** & **CON** & \(\boldsymbol{p}\)**-Value 2** \\ \hline \multirow{2}{*}{
\begin{tabular}{c} linalool \\ nerol \\ \(\alpha\)-terpinol \\ total \\ \end{tabular} } & 8.4 \(\pm\) 0.3 \({}^{\text{a}}\) & 9.6 \(\pm\) 0.8 \({}^{\text{b}}\) & 0.006 & 7.7 \(\pm\) 0.2 & 9.3 \(\pm\) 2.1 & 0.084 \\  & 9.1 \(\pm\) 2.9 \({}^{\text{a}}\) & 5.1 \(\pm\) 2.1 \({}^{\text{b}}\) & 0.020 & 3.0 \(\pm\) 0.1 & 3.8 \(\pm\) 1.1 & 0.129 \\  & 3.8 \(\pm\) 0.2 & 4.0 \(\pm\) 0.6 & 0.524 & 4.5 \(\pm\) 0.6 & 4.9 \(\pm\) 1.1 & 0.399 \\  & 60 & 57 & 44 & 47 & 47 & \\ \hline \hline \end{tabular}
\end{table} 
Table 2: _Cont._  
Figure 2: Score plot of principal component analysis on wines from GRBV-positive Pinot noir under exogenous abscisic acid (ABA) application and no abscisic acid control (CON) across two seasons (\(n=6\)) in Oregon’s Willamette Valley. The plot was generated using the wine volatile profiles. Dash circles represent 95% confidence interval. wines and eleven compounds in 2019 wines (Figure 5); however, no compounds were common across both years. Of the 19 compounds found to be different across treatment groups, six phenols were identified, including hyperoside, quercetin-3-Hmmnose, procyanidin B2, transpiceid, resveratrol, and isoquercetin. In 2018, total LC-HRMS/MS abundances of phenolic compounds were lower in the ABA treatment group. In contradiction, phenolic compounds increased with ABA treatment compared to the unsprayed control in 2019. The untargeted LC-HRMS/MS analysis showed the vintage year had a greater impact in the relative abundance of compounds on GRBV-positive wines than ABA treatments.