Figure 2.

Multivariate data analysis of compositional differences in hydromethanolic extracts of Bidens pilosa tissues types. (A) A PCA scores scatterplot of the Pareto-scaled data set obtained from LC-MS experiments. The six-component model (with PC 1 and PC 2 explaining 65.3% of the variation) indicate the general clustering within the datasets of B. pilosa tissues (leaves (blue), stems (red) and roots (green) samples). The quality parameters of the model are: explained variation/goodness-of-fit R² = 0.890 and the predictive variance Q² = 0.874. The ellipse in the PCA score scatterplot indicates the Hotelling’s T² at 95% confidence interval. (B) Hierarchical cluster analysis of the hierarchical structure of the data in dendrogram format. The model computed (using Euclidean distance and Ward’s minimum variance as a dissimilarity and linkage rule, respectively) shows tissue-specific clustering into two major groups, grouping roots and stems tissues together.