## 3 Results and Discussion
### General Evaluation  
Our multivariate statistical analyses revealed intricate relationships between melatonin application and various physiological parameters, providing novel insights into the complex mechanisms of melatonin's action in post-harvest preservation (Figure 2). The results present compelling evidence for melatonin's multifaceted role in maintaining fruit quality and modulating oxidative responses. The correlation analysis unveiled patterns that shed light on the interconnected nature of quality parameters and biochemical responses to melatonin treatment. Particularly striking were the strong positive correlations between color values (L\", a\", b\") and sugar content (glucose, fructose, sucrose), suggesting that melatonin's influence on the fruit quality parameters operates through coordinated physiological pathways. This observation aligns with the findings of [PERSON] et al. [19], who demonstrated similar correlations in melatonin-treated fruits during post-harvest storage. Interestingly, our results show even stronger correlations than previously reported, possibly due to the specific concentration ranges we employed. In our results, the robust negative correlations between oxidative stress markers (H\({}_{2}\)O\({}_{2}\), MDA) and the quality parameters were particularly noteworthy. This inverse relationship strongly suggests that melatonin's protective effects against oxidative damage directly contribute to quality preservation, supporting and extending the conclusions drawn by [PERSON] et al. [21]. In our view, this finding represents a crucial mechanistic link between melatonin's antioxidant properties and its practical applications in post-harvest preservation. On the other hand, the PCA results (Figure 3) were remarkably revealing, with the first two components explaining an impressive 95.01% of the total variance--a level of explanation that exceeds many similar studies in the field. The clear separation of treatments based on physiological responses provides compelling evidence for melatonin's concentration-dependent effects. The loading patterns we observed, particularly the clustering of color values and sugars on PC1's positive axis with optimal representation by 100 and 1000 uM treatments, align with but also extend the findings of [PERSON] et al. [49]. What we find particularly intriguing is how the PCA results suggest a possible threshold effect in melatonin's action. The clustering of oxidative stress markers (MDA, H\({}_{2}\)O\({}_{2}\)) and antioxidant parameters (TPC (TFFM), DPPH, CUPRAC) on PC1's negative axis, predominantly represented by the control and 10 uM treatments, indicates that there might be a critical concentration threshold below which melatonin's protective effects are not fully activated. This observation is supported by the recent findings from [PERSON] et al. [34] regarding ROS signaling in melatonin-mediated responses, but our results provide a more nuanced understanding of this concentration-dependent relationship. Perhaps the most striking aspect of our analysis was revealed through the hierarchical clustering, which provided an elegant visualization of melatonin's dual functionality in stress protection and quality enhancement (Figure 4). The clear separation of parameters into distinct clusters not only validates our experimental approach but also reveals previously unrecognized patterns in melatonin's mode of action. Our findings build upon and significantly extend the work of [PERSON] et al. [17], particularly in understanding the relationship between the antioxidative processes and quality parameters. The remarkable performance of the 100 uM treatment, especially in terms of sorbitol and \(\beta\)-carotene accumulation, suggests an optimal concentration range for practical applications. This observation is particularly relevant when considered alongside the recent findings of [PERSON] et al. [33], though our results suggest even broader implications for post-harvest treatment protocols.