## Results and Discussion
### Volatile Profile of Different Peach Cultivars Using GC-IMS
#### 3.2.2 The Volatile Fingerprints of Eight Cultivars Using GC-IMS  
The results of the qualitative analysis of the VOCs of the sample using GC-IMS are shown in Table 4. According to the NIST gas phase retention index database and the IMS migration time database built into the flavor analyzer (FlavourSpec(r)) software, 53 signal peaks were detected and 26 typical volatiles were identified, including 11 aldehydes, 5 esters, 4 alcohols, 2 ketones, 2 terpenes and 2 furans. There are 12 substances that were not identified. The most abundant substances detected in peach fruit using GC-IMS in this study were aldehydes, while other researchers [31; 38] have detected esters, which are closely related to factors such as peach ripeness and variety selection. The compounds of 2-hexanal, 1-hexanal, acetic acid ethyl ester, benzaldehyde, 1-hexanol, methyl acetate, 2-butanone, pentanal, 2-methylbutanal, 3-methyl butanal, (Z)-3-hexenyl acetate, 2-methylpropyl acetate and (E)-2-pentenal exhibited more than two peaks. This is due to the fact that during ionic drift, when the concentration of a substance increases, two or more molecules will share a proton or electron, forming a dimer or monomers [14; 39]. The 53 signals obtained were used to draw fingerprint profiles based on peak intensities to compare the differences in volatiles between samples, which can give clearer results (Figure 5). Each row of the figure indicates the signal peaks of all volatiles in the same sample, and each column indicates the signal intensity of the same compounds in different samples. The areas where the signal is more pronounced are boxed out for easier analysis.  
Figure 5: The VOCs fingerprints of different peach cultivars using GC-IMS. Box (A) 14 compounds highly accumulated in cv. ‘HH’; Box (B) four compounds highly accumulated in ’JXIANG’; Box (C) four compounds highly accumulated in ’JXIIU’; Box (D) five compounds highly accumulated in cv. ‘JC’; Box (E) eleven compounds highly accumulated in ’HJML’.  
As shown in box A, some alcohols, ketones and unknown compounds were the most abundant in the HH, and these were the main reasons for the differences in the overall fingerprint profile of the HH compared to the other samples. Aldehydes, namely (E)-2-pentenal, 3-methyl butanal, 2-methylpropanal and pentanal, dominated in JC and JXIANG (box B and D), which differed from the GC-MS, where aldehydes were mainly dominated by 2-hexenal and hexanal. Among the overall peak signals of JXIU, box C had the strongest signals of substances that were not characterized; it is therefore necessary to characterize these unknown compounds in future research. Box E demonstrates that HJML had high concentrations of methyl acetate, acetic acid ethyl ester, 2-methylpropyl acetate, and the flavor of these compounds is discriminingly fruity. None of these were found in GC-MS. As we can see, 12 unknown compounds have strong peak signals in the fingerprints, indicating that these compounds were present at high levels in the samples, and characterizing these substances is essential for the establishment of a complete GC-IMS-based peach fingerprint.  
Combining Tables 2 and 4, the types of VOCs detected by the two techniques differed significantly, with GC-MS detecting more than GC-IMS. Lactones, typical VOCs in peaches, were not found in GC-IMS due to their high molecular weight, which makes them difficult to be detected. Although both techniques are used in conjunction with GC, their focus is dissimilar. GC-MS works under a vacuum and at a high temperature and focuses on the accuracy of qualitative and quantitative information, while GC-IMS performs detection at atmospheric pressure and normal temperature and focuses more on reflecting the authenticity of the sample flavor [40; 41].