## 4 Conclusions  
This study investigated the changes in monovarietal VOOs during storage (0, 6, and 12 months) by combining sensory analysis with targeted (SPME-GC-MS), screening targeted (HS-GC-IMS), and untargeted (FGC) approaches to the analysis of VOCs. Sensory analysis results showed a decrease in the fruity attribute during storage, in alignment with the decline in volatile compounds related to this positive attribute (4,8-dimethyl-1,7-nonadiene, (\(Z\))-3-hexenal, and (\(Z\))-3-hexenyl acetate), and linked with the \"freshness\" of EVOO, that is, as already specified to its quality at time zero, i.e., immediately after the milling and filtration. Almost all samples were classified as EVOO by a panel test throughout the entire storage period. However, one sample exhibited a rancid defect after 12 months and was thus classified as VOO, in accordance with the estimation attributed by the PLS-DA models with the HS-GC-IMS screening method. Furthermore, with the same screening method and predictive models, 6 samples stored for 12 months, despite being classified as EVOO by a panel test, were classified as \"inconsistent\" (between EVOO and VOO), which can be interpreted as a \"red flag\", i.e., a risk of declassification after 12 months. To gain additional information, targeted SPME-GC-MS analysis was used to identify, quantify, and select the VOCs whose concentrations changed more during the storage period, being reasonably considered as the main variables of \"freshness\" and lipid oxidation. A PCA of SPME-GC-MS data, clustering samples based on the storage time, allowed for the selection of markers in fresh oils (4,8-dimethyl-1,7-nonadiene, (\(Z\))-3-hexenal, and (\(Z\))-3-hexenyl acetate) and in oils stored for 12 months (pentanal, hexanal, (\(E\))-2-heptenal, nonanal, (\(E\),\(E\))-2,4-heptadienal, formic acid, and propanoic acid). In this study, the variable most responsible for the downgrade of the only sample from EVOO to VOO after 12 months of storage was associated with a volatile marker well known to be linked to lipid oxidation. In fact, the concentration of (\(E\))-2-heptenal in this sample was approximately twenty times higher than its odor threshold. Untargeted FGC analysis, characterized by its rapid execution time, by PCA, clustered samples according to storage time, but with a lower effectiveness than the other techniques employed herein. However, the PCA results obtained from the three analytical techniques show that the samples are \begin{table}
\begin{tabular}{c c c c} \hline
**VOC** & **Peak Number** & **FGC Retention Time** & **r** \\ \hline methanol & 2 & 20.57 & 0.77 \\ ethanol & 3 & 22.63 & 0.72 \\ (\(\Sigma\)) 3-ethyl-1,5-ocadiene & 4 & 24.46 & 0.72 \\ (\(Z\))-3-hexenyl acetate & 21 & 95.76 & 0.76 \\ \hline \end{tabular}
\end{table} 
Table 3: Correlation matrix results (r > 0.7) between SPME-GC–MS and FGC data. FGC retention time is expressed in seconds. mainly grouped according to storage time, rather than by other factors evaluated in the study, such as agronomical practices, maturity index, and packaging type. Overall, an integrated approach, combining sensory evaluation with targeted and untargeted analysis of the volatile fraction, can help in identifying the molecules (in a targeted approach), regions of a chromatogram, or regions of a heatmap (in an untargeted one) to be considered when predicting the changes in quality occurring during the storage of olive oil, thus contributing to the indication of the correct \"best before date\" on the label. The following supporting information can be downloaded at: [[https://www.mdpi.com/article/10.3390/foods14111884/s1](https://www.mdpi.com/article/10.3390/foods14111884/s1)]([https://www.mdpi.com/article/10.3390/foods14111884/s1](https://www.mdpi.com/article/10.3390/foods14111884/s1)), Table S1: tentative identification of the 41 volatile compounds by SPME-GC-MS in olive oils stored at 0 (T0), 6 (T6), and 12 months (T12). Conceptualization, R.T., C.C., A.B. and T.G.T. ; methodology, R.T., C.C., A.B., S.B., E.C., E.V. and T.G.T.