# Untargeted Profiling and Differentiation of Volatiles in Varieties of Meat Using GC Orbitrap MS
## 3 Results and Discussions
### Statistical Analysis  
Volatiomics, utilizing the metabolomic pipelines, aims to characterize comprehensively a wide range of volatile molecules with the masses less than 550 Da, helps to compare the global profile of volatile compounds between groups of samples accurately, as well as identifies discriminatory compounds. PCA was performed to visualize how the volatile profiling differed between the five different meats (Figure 4). Based on all identified volatile compounds, the first two PCs, explaining over 60% of the total variance between the samples, showed a clear separation of the profiles of the five different meats. The clustering of the five replicate samples indicated that the applied analytical methods of GC-Q/orbitrap high resolution MS coupled with SPME were of good reproducibility and robustness, which are very important in untargeted studies for differentiation. Another aim of this study was to define the specific compounds which are pivotal for the discrimination between the different meat samples. With the unpaired t-test, compounds responsible for the differences between the sample groups were found, as shown in Table 2. With the comparison of every two kinds of meats, dozens of compounds were present at abundances two times higher or lower (fold change > 2 or fold change < 0.5). In the comparison of mutton and beef meats, there were only 38 differentiating compounds found. In the formation pathways of meat aroma, lipid oxidation was one of the primary pathways. Saturated fatty acids (SFA) and monosaturated fatty acids (MUSFA) were the dominant fatty acids, and their levels in mutton and beef meats were similar [35]. In addition, the levels of polyunsaturated fatty acids (PUSFA) in both mutton and beef were relatively low. Therefore, this would lead to the similar pattern of volatile compounds produced through lipid autoxidation, resulting in the fewest differentiating compounds between mutton and beef. However, when comparing pork, duck, and chicken meats, the number of the differentiating volatile compounds would be elevated. It was convinced that PUSFAs [35], including linoleic acid, linoleic acid, and arachidonic acid, were the most easily autoxidized fatty acids. These fatty acids could produce complex patterns and large volumes of volatile compounds during heating procedures. Figure 4: PCA plot according to the volatiles’ profiling in five different meats. From the results based on the PLS-DA analysis for the five meat categories, complete separation between every two meat categories was achieved. The model showed good interpretability, predictability, and non-overfitting due to the high value of R2 (cum, 98.6%) and Q2 (cum, 96.2%). Each meat category showed compact groups, indicating the authenticity of different meat species. In addition, 58 discriminant compounds were screened (VIP \(\geq\) 1). Figure 5 shows 15 most important discriminant compounds. Interestingly, the levels of 2-pentyl furan, 2-butyl furan, 2-hexyl furan, 1-octen-3-ol, and 1-octen-3-one in duck meat, produced from the oxidation of n-6 fatty acids, were higher than those in the other four categories of meats. The highest levels of linoleic acid and arachidonic acid in duck meat [35] would contribute to the discrimination. In addition, carbon disulfide, dimethyl sulfoxide, fatty acid methyl esters including methyl butanoate, methyl octanoate, and methyl nonanoate were the most important discriminants for beef. Methyl esters would be produced through lipid degradation [36]. Carbon disulfide and dimethyl sulfoxide should come from the sulfur-containing amino acids such as methionine and cysteine. Taken together, five categories of meat could be apparently distinguished according to the volatiles' profiling. The profile pattern would vary a lot with specific volatiles generated from certain aroma-precursors such as lipids or amino acids. In addition, nowadays, volatile profiling combined with chemometric models show great potenti