## 2 Results  
Figure 1 presents the appearance of the three varieties of peanuts, as well as the length, width, and aspect ratio values of the individual peanuts. The mean lengths of the peanut kernels of ZKH1H, ZKH13H, and CFD were 12.84 \(\pm\) 1.21 mm, 13.67 \(\pm\) 0.88 mm, and 16.32 \(\pm\) 1.48 mm, respectively. The length of the CFD variety was significantly greater than those of ZKH1H and ZKH13H by 27.07% and 19.36%, respectively (\(p<0.001\) and \(p<0.001\), respectively). There was no significant difference between the lengths of ZKH1H and ZKH13H (\(p=0.087\)) (Figure 1B). In terms of width, ZKH1H had the greatest peanut kernel width, and the CFD variety had the smallest peanut width. However, there was no significant difference in width between ZKH1H and ZKH13H (\(p=0.195\)). The width of the CFD variety was significantly less than those of ZKH1H and ZKH13H (\(p<0.001\) and \(p<0.001\), respectively) (Figure 1C). The ratio of length to width is one of the morphological indicators of peanuts, and there were significant differences in the length-width ratios among the three varieties, with the CFD variety having the largest length-width ratio and ZKH1H having the smallest (Figure 1D). Figure 1: The appearance (**A**), length (**B**), width (**C**), and length/width ratio (**D**) of the three varieties of peanuts. The data are presented as the mean \(\pm\) standard deviation (SD). In present study, the UPLC-Q-TOF/MS method was used to identify the differences between the nonvolatile metabolites of the three varieties of peanuts; the total ion current (TIC) overlap plots and multipeak detection plots of the peanut samples are shown in Figure S1. The high overlap rates of the TIC curves observed across various peanut samples provide strong evidence of the reproducibility and reliability of the evaluation outcomes. The structures of the nonvolatile metabolites were determined via a comparative analysis with the MWDB database, and 417 nonvolatile metabolites in the following 10 classes were identified from the three peanut species (Figure 2A): organic acids and their derivatives (28.9%); organic oxygen compounds (21.9%); lipids and lipid-like molecules (12.6%); organoheterocyclic compounds (9.9%); nucleosides, nucleotides, and analogues (9.4%); benzenoids (7.8%); phenylpropanoids and polyketides (6.1%); organic nitrogen compounds (2.7%); lignans, neoligans, and related compounds (0.5%); and alkaloids and their derivatives (0.3%). To analyze the differences among the three peanut varieties, the samples were subjected to principal component analysis (Figure 2B), which revealed that the contribution of principal component 1 was 35.6% and that of principal component 2 was 18%. The peanut samples in each group were clustered together within the group, and the intragroup variability was small and highly reproducible. The groups were clearly separated, indicating that the metabolite fractions of different peanut samples were significantly different. After the metabolite data were normalized, cluster analysis was performed on all the samples. There were different clustering patterns among the different species (Figure 2C). Furthermore, K-means plots were utilized to cluster the relative contents of the nonvolatile metabolites obtained from the screening of all subgroups. All the metabolites were classified into nine subclasses, containing 5, 62, 3, 9, 332, 20, 20, 1, and 3 metabolites (Figure 3). Figure 2: Different main nonvolatile metabolites in the three varieties of peanut samples were identified through a widely targeted metabolic method and method reliability evaluation. (**A**) Classification of the 417 nonvolatile metabolites detected in the three varieties of peanut samples. (**B**) PCA score plot. (**C**) Heatmap analysis. To gain a deeper insight into the variations in non-VOCs among the three varieties, OPLS-DA was used to further screen out the differential non-VOCs between the pairwise comparisons of ZKH1H, ZKH13H, and CFD (Figure 4).