## 3 Results and Discussion
### Process Impact Comparison Immediately after Processing  
In this work, 21 volatile compounds were detected, in the fresh and processed samples, with the headspace GC-MS approach. These compounds include ten esters (\(n\)-propyl acetate, isobutyl acetate, butyl acetate, 2-methylbutyl acetate, ethyl 2-methylbutanoate, butyl propanoate, pentyl acetate, 3-methyl-2-buten-1-yl acetate, 2-methylpropyl butanoate and hexyl acetate); seven alcohols and terpene alcohols (2-methyl-1-propanol, 1-butanol, 2-methyl-1-butanol, 1-hexanol, 1-octanol, terpinen-4-ol and \(\alpha\)-terpineol); three aldehydes (hexanal, (\(E\))-2-hexanal and octanal); and one ketone (6-methyl-5-hepten-2-one). A PLS-DA model was used to compare the volatile fraction of differently pasteurized apple juices immediately after processing. Figure 1 shows a bi-plot using LV1 and LV2. On the plot, the four samples (control, PEF, thermal and HPP) and 21 volatile compounds (small open circles) are shown. Based on the distance between the samples on the plot, the similarity and/or difference between the differently processed samples can be investigated. From Figure 1, the first clear trend is that all processed samples are projected to the right side of the plot and far away from the unprocessed/control samples. Hence, immediately after processing, there is a clear effect of the applied pasteurization technologies on Jazz apple juice volatile fraction. This difference between the processed and unprocessed samples is explained by the first LV. The second trend on the plot is the difference among the pasteurization technologies. The second LV explains the difference between PEF pasteurized samples, on the one side, and thermal and HPP-pasteurized samples on the other side. Immediately after processing, PEF processed juices seem to have a distinct headspace fraction, whereas thermal and HPP processed juices seem to have a comparable headspace fractions. A bi-plot also displays the correlation between the samples (control and processed) and individual volatile compounds. On the plot, if a volatile compound is positioned close to a certain sample this shows that it is detected with a higher amount in that particular sample compared to the other samples in the model. Volatiles that are projected in the opposite direction to a certain sample are detected in lower amounts in that sample compared to the other samples. As can be seen from Figure 1, a number of volatile compounds are detected in higher amounts in the control samples compared to the pasteurized juices, whereas few other compounds are detected in higher amounts in the processed samples. Hence, bi-plots provide relevant graphical information about the relation between volatile compounds and applied processing technologies. However, bi-plots only provide a graphical information and it is not straightforward to rank compounds based on their concentration in one processing technique compared to another one. For that reason, VID coefficients were calculated. Per sample, each volatiles were given a VID coefficient between \(-1\) and \(+1\). A positive VID coefficient in a certain sample shows a higher amount in that particular sample compared to the other samples and vice versa. Since the aim was to determine volatiles clearly affected by the applied processing or storage time, only those with an absolute VID value higher than 0.800 (discriminant volatiles) were selected and identified (Table 1, Figure 1). Figure 1: A PLS-DA biplot showing the comparison of volatile fraction of control/unprocessed apple juice (\(\blacksquare\)), thermal (72 \({}^{\circ}\)C for 15 s) (\(\bullet\)), HPP (600 MPa for 3 min) (\(\blacklozenge\)) and PEF (15.5 kV/cm and specific energy of 158 kJ/L) (\(\blacktriangle\)) pasteurized juices. The volatile compounds are represented with the open circles. Volatiles with amounts clearly different between the different samples (discriminant markers) are named. PLS-DA: partial least squares-discriminant analysis; HPP: High-Pressure Processing; PEF: Pulsed Electric Fields; LV: latent variable.