# The Irrigation Water pH Has a Dominant Impact on the Growth and Stress Markers of Bigleaf Hydrangea
## 3 Results
### Impact of pH and EC of Irrigation Water and Hydrangea Varieties on Morpholayed Characteristics
#### 3.2.4 Impact of pH and EC of Irrigation Water and Hydrangea Varieties on Biochemical Parameters
A low positive correlation was found between flower diameter and plant height (r = 0.41), leaf number and plant height (r = 0.39), and flower weight (r = 0.31). A high negative correlation was found between MDA and leaf number (r = -0.73), as well as leaf weight (r = -0.71). A moderate negative correlation was found between proline concentration and leaf number (r = -0.68), and leaf weight (r = -0.65). A low negative correlation was found between flower diameter and stem number (r = -0.4), and flower number (r = -0.4). Furthermore, a low negative correlation was found between proline and plant height (r = -0.41), MDA and plant height (r = 0.42), and flower weight (r = -0.3). Principal component analysis (PCA) was conducted to analyze the relationships among the measured morphological parameters and to visualize the differences between Variety 1 (Early Blue, red color) and Variety 2 (Bianco, blue color) (Figure 9). The first three principal components (PCs) explained a substantial portion of the total variance in the dataset: PC1 accounted for 45.24%, PC2 for an additional 24.32%, and PC3 for 12.4%. Cumulatively, the first two components (PC1 and PC2) captured 69.56% of the total variability. Figure 8: The analysis shows the negative (–, purple) and positive (+, red) correlations between morphological properties, proline, and MDA concentrations in the Bianco hydrangea variety. The strength of the correlation and its significance are indicated by a number, while empty fields are not significant. The PCA biplots (PC1 vs. PC2 and PC1 vs. PC3) indicate a partial separation of samples based on variety affiliation, which is most pronounced along the PC1 axis. Samples belonging to Variety 1 predominantly exhibited positive scores on the PC1 axis, whereas Variety 2 samples generally showed negative scores on the same axis. Despite this trend, considerable overlap exists between the groups. The PC2 and PC3 axes contributed less to the differentiation between the two varieties. Interpretation of the variable loadings revealed that the PC1 axis is primarily defined by the contrast between plant height and flower diameter, which have strong positive correlations (loadings) with PC1, and variables such as flower number, stem number, leaf number, and leaf weight, which have strong negative correlations with PC1. Thus, PC1 effectively separates varieties characterized by greater height and flower diameter from those featuring a higher number of flowers, stems, and leaves, with greater leaf weight. The PC2 axis further differentiates samples, mainly contrasting plant height (positive loading) against most other measured growth parameters (negative loadings). The PCA analysis successfully summarizes the main sources of variation within the data. It indicates that Variety 1 and Variety 2 are partially distinct, with the primary difference (explained by PC1) being that Variety 1 tends towards taller plants with larger flower head diameters, whereas Variety 2 tends towards a higher number of flowers, stems, and leaves, and greater leaf weight. Significant variability exists within each variety.