For PC analyses, the results showed that scaling and transformation methods affected the dimension of the PC-space optimized using seven-fold cross-validation, the sample clustering in the PCA scores space (e.g., constructed from the first two PCs), and the moderate outliers detected in the DModX plots (Figure 4 and Figure S5). Furthermore, the metric used to assess the model fit (or explained variation) and predictive ability of the computed PCA models were R2 and Q2 . The inspection of these diagnostic metrics shows that scaling and/or transformation remarkably affected the amount of explained variation (the goodness of fit) by the model and its predictive ability (Table 3).