## 3 Results
### Untargeted Metabolomics Analysis  
#### 3.3.1 Orthogonal Partial Least Squares Discriminant Analysis OPLS-DA  
The orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) is a multivariate statistical method with supervised pattern recognition. It effectively eliminates effects \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Composition** & **Fresh Yongfu Fruit** & **Fresh Longsheng Fruit** & **Dried Yongfu Fruit** \\ \hline Total sugar & \(2.88\pm 40.37\)\({}^{\text{a}}\) & \(3.16\pm 3.04\)\({}^{\text{b}}\) & \(4.28\pm 3.95\)\({}^{\text{c}}\) \\ Total dietary fiber & \(34.97\pm 1.25\)\({}^{\text{a}}\) & \(34.12\pm 1.11\)\({}^{\text{a}}\) & \(41.99\pm 0.93\)\({}^{\text{b}}\) \\ Protein & \(7.04\pm 0.01\)\({}^{\text{a}}\) & \(7.59\pm 0.038\)\({}^{\text{b}}\) & \(10.98\pm 0.029\)\({}^{\text{c}}\) \\ Soluble dietary fiber & \(3.48\pm 0.19\)\({}^{\text{a}}\) & \(3.64\pm 0.23\)\({}^{\text{a}}\) & \(3.26\pm 0.24\)\({}^{\text{a}}\) \\ Ash & \(2.42\pm 0.01\)\({}^{\text{a}}\) & \(2.43\pm 0.01\)\({}^{\text{a}}\) & \(3.99\pm 0.02\)\({}^{\text{b}}\) \\ Crude fat & \(0.80\pm 0.003\)\({}^{\text{a}}\) & \(0.90\pm 0.003\)\({}^{\text{b}}\) & \(5.19\pm 0.02\)\({}^{\text{c}}\) \\ \hline \hline \end{tabular} Note: Different letters indicate significant differences, while the same letters indicate non–significant differences.  
\end{table} 
Table 2: Nutrient content of _S. grosvenorii_ in different groups (g/100 g). \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Mineral** & **Fresh Yongfu Fruit** & **Fresh Longsheng Fruit** & **Dried Yongfu Fruit** \\ \hline
**Ca** & \(1203.5\pm 84.64\)\({}^{\text{a}}\) & \(971.25\pm 48.62\)\({}^{\text{b}}\) & \(627.25\pm 45.09\)\({}^{\text{c}}\) \\
**Mg** & \(2254.25\pm 134.95\)\({}^{\text{a}}\) & \(1746.25\pm 1142.27\)\({}^{\text{c}}\) & \(1242.95\pm 58.48\)\({}^{\text{b}}\) \\ K & \(136.656.5\pm 760.06\)\({}^{\text{a}}\) & \(106.675.25\pm 820.34\)\({}^{\text{b}}\) & \(8528.00\pm 689.76\)\({}^{\text{c}}\) \\
**Zn** & \(221.\pm 0.34\)\({}^{\text{a}}\) & \(22.83\pm 0.59\)\({}^{\text{a}}\) & \(17.20\pm 0.18\)\({}^{\text{b}}\) \\
**Na** & \(14.83\pm 0.63\)\({}^{\text{a}}\) & \(20.46\pm 0.26\)\({}^{\text{b}}\) & \(11.03\pm 0.13\)\({}^{\text{c}}\) \\ Al & \(4.75\pm 0.17\)\({}^{\text{a}}\) & \(9.41\pm 0.13\)\({}^{\text{b}}\) & \(6.07\pm 0.09\)\({}^{\text{c}}\) \\ Fe & \(54.83\pm 1.10\)\({}^{\text{a}}\) & \(59.33\pm 1.40\)\({}^{\text{b}}\) & \(34.63\pm 0.22\)\({}^{\text{c}}\) \\ Cr & \(0.34\pm 0.01\)\({}^{\text{a}}\) & \(0.22\pm 0.004\)\({}^{\text{b}}\) & \(0.12\pm 0.002\)\({}^{\text{c}}\) \\ Cu & \(13.45\pm 0.31\)\({}^{\text{a}}\) & \(10.25\pm 0.24\)\({}^{\text{b}}\) & \(11.40\pm 0.08\)\({}^{\text{c}}\) \\ Se & \(0.0088\pm 0.0005\)\({}^{\text{a}}\) & \(0.0073\pm 0.0005\)\({}^{\text{b}}\) & \(0.02\pm 0.00096\)\({}^{\text{c}}\) \\ \hline \hline \end{tabular} Note: Different letters indicate significant differences, while the same letters indicate non–significant differences.  
\end{table} 
Table 3: Mineral Content of _S. grosvenorii_ in different groups (ug/g). unrelated to the study, thus aiding in the screening of differential metabolites. The replacement test plot effectively assesses whether the OPLS-DA model is overfitting. According to Figure 1A-D, the points of Q\({}^{2}\) and R\({}^{2}\) represent the model evaluation parameters of the actual grouping. When the predicted Q\({}^{2}\) and R\({}^{2}\) points are both lower than the original Q\({}^{2}\) and R\({}^{2}\) points in the upper right (the rightmost blue Q\({}^{2}\) point may coincide with the green R\({}^{2}\) point at the uppermost right corner in the figure), it indicates that the model is reliable. According to Figure 1E-H, the point clouds of the sample groups are distributed in distinct regions, showing clear clustering and categorical differences. Additionally, the samples from different groups are more distinctly separated with no overlap, indicating a significant change in metabolome information. Figure 1: The OPLS-DA models for the data from the positive and negative ionization modes. (**A–D**) Permutation plots.