## 3 Results
### HS-GC-IMS Results  
The VOCs profile of samples was also analyzed during storage using the HS-GC-IMS analytical technique. From the analysis of 15 pre-selected VOCs, regions of spectral intensity of interest, comprising monomers and dimers, were identified in the heatmaps [27]. On  
Figure 3: Sensory profile comparison of EVOOs obtained from olives cultivated using two agronomic systems: (**a**) integrated pest management and (**b**) organic farming, evaluated at 0, 6, and 12 months of storage. Figure 2: Evolution of fruity sensory intensity (expressed as means \(\pm\) standard deviations) in all olive oil samples during 12 months of storage. Different letters above the bars indicate statistically significant differences as determined by one-way ANOVA (Tukey’s HSD, \(p\leq 0.05\)). the basis of PLS-DA calibration models built with a large database previously collected, the HS-GC-IMS data matrix was used to estimate the commercial category of samples. Specifically, combining the probability results of each model, the commercial category of samples was established (last column of Table 1): 25 samples were classified as EVOO and 1 as VOO. Six samples were identified as inconsistent (IN) (between EVOO and VOO), characterized by the inability of the models to assign a unique commercial category based on the simultaneous evaluation of the probabilities generated. All samples at T0 and T6 were instrumentally predicted as EVOO in agreement with the sensory classification. Considering the oils stored for 1 year, only one sample (2B_TI2_VS, in bold in Table 1) was estimated as VOO, as per the sensory classification (due to the presence of a rancid defect). Six of twelve samples were estimated as IN between EVOO and VOO categories due to discrepant results in terms of the probability obtained by the four models. For example, sample 4B_TI2_VS, classified as IN, showed a 79% probability of belonging to the EVOO category for the EVOO vs. no-EVOO model. However, this result was not confirmed by the PLS-DA EVOO vs. VOO model, which \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Sample**} & **EVOO vs.** & **LOO vs.** & **LOO vs.** & **EVOO vs.** & **Resulting** \\  & **No-EVOO** & **No-LOO** & **VOO** & **VOO** & **Category** \\ \hline  
\_T6\_VB & 0.90 & 0.24 & 0.08 & 0.92 & EVOO \\ \hline
1A\_TI2\_VS & 0.64 & 0.21 & 0.51 & 0.35 & IN \\
1B\_TI2\_VS & 0.85 & 0.09 & 0.23 & 0.92 & EVOO \\
1A\_TI2\_VB & 0.67 & 0.14 & 0.23 & 0.28 & IN \\
1B\_TI2\_VB & 0.84 & 0.08 & 0.18 & 0.88 & EVOO \\
2A\_TI2\_VS & 0.64 & 0.10 & 0.06 & 0.47 & IN \\
**2B\_TI2\_VS** & 0.43 & 0.16 & 0.40 & 0.21 & VOO \({}^{\star}\) \\
3A\_TI2\_VS & 0.55 & 0.07 & 0.07 & 0.19 & IN \\
3B\_TI2\_VS & 0.88 & 0.07 & 0.18 & 0.71 & EVOO \\
4A\_TI2\_VS & 0.74 & 0.19 & 0.10 & 0.62 & EVOO \\
**4B\_TI2\_VS** & 0.79 & 0.07 & 0.10 & 0.33 & IN \\
**4A\_TI2\_VB** & 0.59 & 0.08 & 0.06 & 0.29 & IN \\
**4B\_TI2\_VB** & 0.80 & 0.12 & 0.07 & 0.51 & EVOO \\ \hline \hline \end{tabular} \({}^{\star}\)This sample was the only sample classified as VOO also by panel test (rancid defect with a median score of 1.5).  
\end{table} 
Table 1: Results, in terms of probability values, of HS-GC–IMS analysis of the entire sample set applying the four previously built PLS-DA models and resulting olive oil commercial categories. indicated a 33% probability of belonging to the EVOO category. PCA was employed to visualize samples according to the storage period. As shown in Figure 4, the contribution of the first and second PCs were 42.59% and 15.64%, respectively. The score plot clearly shows a separation between fresh samples (T0 in green circles) and stored samples, along the PC1. Samples stored for 6 and 12 months were separated along the PC2, except for samples collected during the first week of harvest and stored for 12 months, which showed a better state of preservation that was more similar to samples stored for only 6 months. This highlights the importance of the time of olive harvesting for the shelf life of olive oils [38].