Following scaling and transformation, PCA and OPLS-DA models were constructed/fitted and evaluated to assess the influence of these data pre-treatment methods on the models’ quality, classification accuracy, feature selection/extraction, and the subsequent interpretability of the data. The data pre-treatment is an essential step in the metabolomic data analysis pipeline as it enables the preparation of the data for downstream analyses, minimizing variable redundancy and making all variables more comparable in size .