## 3 Results and Discussion
\begin{table}
\begin{tabular}{c c} \hline \hline
**Sample** & **Compounds (Peak Number)** \\ \hline \multirow{4}{*}{AZAC} & methyl 4-methyl-3-pentenoate (**11**), 2-octanone (**21**), methyl \\  & 3-methyl-3-hexenoate (**32**), eremophilene (**115**), \\  & (4a\(R\),8a\(S\))-4a-methyl-1-methylene-7-(propan-2-ylidene)decahydronaphthalene \\  & **(129) \({}^{\star}\), and selina-3,7(11)-diene (**131**); \\ \hline \multirow{4}{*}{CASC} & 4,4-dimethyl-2-buten-4-olide (**13**), \(\beta\)-thujene (**17**), 2,2,4,6,6-pentamethylheptane (**23**), \\  & isomyrconel (**51**), \(\alpha\)-bourbonene (**95**), cis-\(\alpha\)-bergamotene (**102**), and \\  & \(\alpha\)-curcumene (**113**); \\ \hline \multirow{2}{*}{ENIG} & (_E_)-1,3-nonadiene (**8**), \(\alpha\)-phellandrene (**27**), neo-allo-ocimene (**60**), (_AE_,_6_E_)-allocimene (**61**), \(\gamma\)-selinene (**111**), and cadine-1,4-diene (**127**); \\ \hline \multirow{4}{*}{LORA} & amyl isobutyrate (**37**), hexyl propanoate (**56**), fenchol (**58**), \(\alpha\)-terpineol (**67**), dodecane (**69**), \(\alpha\)-citral (**75**), perillaldehyde (**77**), n-octyl propionate (**81**), \(\beta\)-bourbonene (**94**), \\  & tetradaceane (**98**), 7-epi-\(\alpha\)-cadinence (**110**), 2-tetradanone (**134**), and \\  & (_E_,_Z_)-5,7-dodecadien-1-ol acetate (**137**); \\ \hline \multirow{4}{*}{ZAPP} & isobutyl propionate (**3**), methyl isoheptanoate (**20**), 9-methyl-1-decene (**40**), \\  & 2-methylbutyl butanoate (**41**), methyl 2-methylheptanoate (**43**), \\  & 3-methylbut-2-en-1-yl pivalate (**62**), methyl 6-methylocanoate (**64**), methyl \\ \cline{1-1}  & undecenoate (**101**), and geranyl propionate (**109**). \\ \hline \hline \end{tabular} \({}^{\star}\)Even though an enantioselective column was not used, and so no chirality of a compound can be assessed, this was the entry returned by the database search.  
\end{table} 
Table 4: Suggested unique marker compounds in each of the hop samples. power of separation of GC\(\times\)GC through a clear distinction between the classes of MHyd, OM, SHyd, and OS. The classes of compounds represented in this study may be considered descriptors of the composition of the hop, displaying the metabolite formation and the identity of the cone. Figure 4 represents the compositional profile of each hop according to the percentage obtained by our methodology (subject to the limitations of reporting peak areas by using SPME), by a clear distinction of the samples. According to Figure 4, all the hops expressed the highest concentration of sesquiterpene hydrocarbons as the major class present, as expected based on the presence of carryophyllene (**103**) and humulene (**108**), with the largest amounts for AZAC, LORA, and CASC, respectively. The hop ENIG and ZAPP expressed a considerable concentration of monoterpene hydrocarbons, which differentiates these from the other hop; this characteristic can be related to the high concentration of \(\beta\)-myrcene (**22**). Furthermore, \(\beta\)-myrcene has a direct relationship with the amount of essential oil produced by the hop with regards to its biosynthetic pathway, giving a different complexity for the hop [4]. Figure 3: (**A**) Apex plot of the compounds present in the hop samples AZAC, CASC, ENIG, LORA, and ZAPP showing the classes of compounds (refer to Table 3 for abbreviations). (**B**) Apex plot showing clustering of MHyd, OM, SHyd, and OS classes. The amount of data provided by GC\(\times\)GC illustrates the ease in profiling and describing the sample composition, which should be translated into multivariate statistics, a powerful tool to aid this data interpretation. Considering the data in Table 3, a principal component analysis (PCA) interpretation was applied to the compounds present. For the PCA, the model was built with the relative peak area (%) related to each compound with the selection of autoscale as preprocessing and 3 PCs representing 81.70% of the variance with 34.19% for PC1, 24.24% for PC2, and 23.27% for PC3.