## 3 Results and Discussion
### Aroma Profiling
\begin{table}
\begin{tabular}{c c c c c} \hline
**COMPOUNDS** & **RT** & **CTR** & **CV** & **CO** & **HD** \\ \hline \(\alpha\)-cubebene & 28.15 & x & nd & nd & x \\ nuciferol & 28.25 & x & x & X & x \\ cuparene & 28.34 & x & x & X & x \\ (e)-\(\beta\)-famesene & 28.39 & x & nd & X & x \\ cedrene & 28.72 & x & x & X & nd \\ \(\alpha\)-himachalene & 29.12 & x & x & X & x \\ \(\gamma\)-muroclene & 29.57 & x & x & nd & x \\ \(\alpha\)-ylangene & 30.14 & x & x & nd & nd \\
**OTHERS (I)** & & & & & \\
2 methylfuran & 16.87 & x & x & X & x \\ \hline \end{tabular}
\end{table} 
Table 4: _Cont._  
Figure 1: Chromatographic profiles total ion current (TIC) of red _Topepo_ fruits obtained by cultivation: (**A**) without fertilizers (CTR); (**B**) horse dung (HD); (**C**) olive compost (CO); (**D**) vegetable compost (CV). 4-hexen-1-ol acetate was detected, exclusively, in the CTR and HD treated samples. 4-methyl-1-pentanol was the main alcohol. Principal component analysis (PCA) confirmed the above results (Figure 2). The changes in volatile fraction composition of the samples due to the organic fertilizers used gave rise to chemical compounds and different chromatographic profiles that were used for the purpose of classification using chemometrics. The screen plot of the variance captured by each PC, shows that the total variability of the data can be concentrated in just few new coordinates (Figure 2). The first two principal components captured 83.39% of the whole data variance. The first PC alone is enough to separate three groups (CTR, HD, and CV), while the second PC allows the discrimination of CO samples. A detailed evaluation of the chromatographic peaks allowed to establish the relationship between PCs and chemical classes, and more specifically, the distribution of the samples in the PC space revealed the high contribution of pyrazines and terpenens. The processing of the UFGC results using the AroChemBase software allowed the identification of thirty volatile compounds while the odor maps of the red _Topepo_ fruits, representing the \"Odor fingerprints\" (Figure 3), were extrapolated from the chromatographic profiles. The comparison of the Heracles II odor profiles (Figure 3) showed, clearly, the differences between the samples treated with different organic fertilizers and between these and control. Figure 2: Bi-plots PCA (principal component analysis) of SPME-GC-QTOF/MS (solid-phase micro-extraction coupled to gas chromatography separation and quadrupole time-of-flight mass spectrometry detection) dataset. According to SPME-GC-QTOF/MS results, 2-isobutyl-3-methoxypyrazine was identified in all the analyzed samples and it was present in the greatest amount in CV treated red _Topepo_. In all the samples, between alcohols and aldehydes, a great amount of heptanal, 2-nonenal, and 1- octen-3-ol compounds which give flavor notes of freshly cut grass or ground leaves, and 2-methyl-propanal, which gives the typical cacao spicy, were identified [64]. Myrtenol, citronello1, thymol, \(\beta\)-farnesene, \(\alpha\)-phellandrene, and linalool, among the terpen, were also pointed out. The UFGC profiles, in the form of a numerical relationship between the retention time and the area of the peaks, were analyzed by using PCA. To ensure proper description of the real input data, it was assumed that the first two components described more than 80% of input set variance [66]. In order to reduce the dataset measurements consisting of all the peak areas of each analyzed chromatograms, the most discriminant peak areas of specific compounds were extrapolated ((Z)-2-nonenal, pentan-2-ol 2-methyl propanal) and then treated as an input dataset for PCA analysis [67]. Figure 3: Radar plots (odor maps or fingerprints), obtained by using an electronic nose with MXT-5 column and MXT-1701 column, of red _Topepo_ fruits cultivated (**a**) without fertilizers (CTR); (**b**) with vegetable compost (CV); (**c**) with olive compost (CO); (**d**) with horse dung (HD).