# E-Nose Quality Evaluation of Extra Virgin Olive Oil Stored in Different Containers
## 3 Results and Discussion
### E-Nose Discrimination of VOO Stored in Different Containers  
VOO stored in different containers was analyzed using an E-nose. Through sensor measurements versus time, a response curve measuring responses over one second intervals was generated to characterize the sensor response curves. An algorithm function was then used to extract the data of each sensor in the samples studied: the maximum value of the signal minus the minimum, plus 100, minus one in our case was used to obtain a data vector with 11 rows for each sample as a result of a feature extraction algorithm. Once all measurements were obtained, a baseline manipulation pre-processing was performed following Equation (1). \[\textit{Characteristic value}=(\textit{Reference/Sample})\cdot 100, \tag{1}\]  
where _Characteristic value_ is the pre-processed value, _Reference_ is the steady value (average of the last five values) reached during the clean air measurement phase, and _Sample_ is the steady value during the sample measurement phase. E-nose data of each container type were then individually processed using principal component analysis (PCA) with the objective of exploring whether there were any natural groupings throughout the storage time (Figure 4). The PCA results showed that more than 70.0% of the total variance of data was explained by only PC1 in all the containers studied. When comparing the two first principal components, a clear progression of the scores over storage time could be observed, regardless of the containers used. This was most notable with the Dark crystal bottles, where four groups of samples correlated with the storage time (Figure 3). The first group, with negative scores for both components, included samples of t0, t1, and t2; the second (positive values for PC1 and negative values for PC2) with t3 samples; the third (positive and negative scores for PC1 and PC2) with samples of t4 and t5; and the fourth (negative scores for PC1 and positive scores for PC2) with samples of t6. Groups three and four clearly differed from the other two. These results support the sensory analysis carried out by the tasting panel, which showed that in the last three samplings (t4-t6), the oils lost fruity aromatic intensity, defects increased, and the Extra category was lost. In the case of the Green PET bottles, only three different groups can be observed in the PCA scores biplot (Figure 3): the first group (positive scores values for PC1 and PC2) with samples from t0 to t3, the second group (negative scores for both PC1 and PC2) with t4 and t5 samples, and the third group (negative scores for PC1 and positive scores for PC2) with samples of t6. In this container, and in line with the results of the sensorial analysis, samples from t0 to t3 continued to maintain the extra category (EVOO). However, the E-nose classified samples from t4 as VOO, while the tasting panel still classified t4 as EVOO. This contradiction could be considered as supportive of the fact that many authors have questioned the accuracy of human panels and indicate that they should be aided by instrumental tools [37]. Lastly, in the case of olive oil samples conserved in Tinplate, although the same three groups could be observed as with the Green PET bottles, the differences between them were not significant, except for the samples t6. In this case, samples did not show any variation over storage time, in line with the sensorial analysis and, as a result, all samples were categorized as EVOO. It is notable that the behavior of the t6 samples was very similar in all containers, with identical score values (negative scores for PC1 and positive scores for PC2), corresponding to a loss of quality in all cases. Samples from the Tinplate containers, as concluded by the tasting panel, were still considered to be of EVOO category, although the intensity of the fruitiness had decreased (Table 1). However, the results obtained from the E-nose indicated that the quality of EVOO had significantly decreased.