## 3 Results and Discussion
### Multivariate Analysis  
#### 3.2.1 PCA  
In order to reduce the number of dimensions, PCA was employed to investigate the relationship between apple varieties and volatile compounds, and which were the most important volatiles for different apple cultivars. The correlation matrixes are in the Supplementary Materials (Tables S3 and S4). The PCA results were shown in Figure 3, including the score plots and loading plots over two years.  
In the first year, the eigenvalues of eight principal components (PCs) were higher than one, and the cumulative contribution was 82.18%. The first two PCs were accounted for at 25.61% and 19.17%, respectively, explaining 44.78% of the total variance in the data set. It can be seen from Figure 3a, most of the apple varieties were closely located, which indicated they were similar from a volatile point of view and may be difficult to distinguish. However, MG and HAH, located in the positive region of PC1, were distinctly separated from most apple varieties, which demonstrates that they are highly different from others. Combined with the loading plot in Figure 3b, hexanal (4), E-2-hexneal (9), butyl 3-methylbutanoate (12), hexyl propionate (18), nonanal (20), ethyl octanoate (25), 2-ethylhexanol (27), naphthalene (36) and dodecanol (39) were the main contributors for MG, leading to these differences. It was worth noting that most of these compounds were aldehydes and alcohols, which implied that MG was more related to aldehyde or alcohol like variety. As for HAH, butyl propionate (5), propyl hexanoate (16), butyl hexanoate (22), 1-heptanol (26), pentyl hexanoate (28) and hexyl octanoate (37) were the main characterized volatile compounds. Because most of these compounds are esters, HAH may be an ester like apple variety.  
Figure 3: _Cont._  
In the second year, there were also eight PCs. A total 53.23% of the variance could be explained by the first two PCs, which occupied 43.1% and 10.13% respectively. PN, SR and CF were positioned away from other apple varieties, which revealed that the differences in volatiles were great (Figure 3c). PN was highly influenced by butyl acetate (3), butyl butyrate (10), butyl hexanoate (22), hexyl butyrate (23), hexyl 2-methylbutanoate (24), 2-ethylhexanol (27), 1-octanol (32), butyl octanoate (34) and dodecanol (39). The main contributed volatiles of SR were ethyl 2-methylbutyrate (2), ethyl hexanoate (11), pentyl butyrate (15), propyl hexanoate (16), hexyl propionate (18), butyl hexanoate (22) and pentyl hexanoate (28), which were positively correlated to PC1. Moreover, all of them were esters, implying that SR might be an ester like variety. CF was in the negative area of PC2 and near the axis of PC1. It was highly associated with butyl propionate (5), butyl 3-methylbutanoate (12), 1-heptanol (26), linalool (30) and naphthalene (36).  
It should be noticed that most of the contribution of volatile compounds mentioned above was not at a high percentage level, excluding butyl acetate (3), hexanal (4), E-2-hexenal (9), hexyl 2-methylbutanoate (24) and 1-heptanol (26). It may be concluded that the low volatile concentration percentages such as propyl hexanoate (16), ethyl octanoate (25), linalool (30), naphthalene (36), hexyl octanoate (37) and dodecanol (39), may have a greater influence on variety discrimination. To conclude, the two year results for the apple varieties MG, HAH, PN, CF and SR did not reveal similar positions in score plots and locate outside the confidence area (95%). These 5 varieties may be more sensitive and unstable with environmental changes. In general, PCA was not an effective method to distinguish apple varieties based on the volatile profiles.