Page 176 - AJWEP-22-5

Wang, et al.

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Figure 4. Differentially abundant metabolite analysis based on PCA. Each point in the graph represents a
sample. Samples from the same group are represented by the same color. “Group” indicates the grouping.
(A) The 2D PCA plot of differentially abundant metabolite analysis. (B) The 3D PCA plot for differentially
abundant metabolite analysis. Image created by the authors.
Abbreviations: PC: Principal component; PCA: Principal component analysis.

A B

C

Figure 5. OPLS-DA model diagram for pairwise comparisons of differentially abundant metabolites.
(A) A4P5 vs. A4P_. (B) A4P5 vs. A_P5. C) A_P5 vs. A4P_. The predictive parameters of the OPLS-DA
evaluation model are R X, R Y, and Q . The closer these three indicators are to 1, the more stable and reliable
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the model is. When Q > 0.5, the model can be considered effective; when Q > 0.9, it is regarded as excellent.
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Abbreviation: OPLS-DA: Orthogonal partial least squares discriminant analysis.
of Q was close to 1, indicating the high stability and model may exhibit high consistency and accuracy in
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reliability of the model. This finding indicates that the prediction and analysis.

Volume 22 Issue 5 (2025) 170 doi: 10.366922/AJWEP025150108