## 4 Discussion
The dendrograms, both vertical and horizontal, play a crucial role in clustering compounds and treatment conditions based on their similarity in expression patterns. In line with our observations, research has demonstrated how dendrograms provide insights into the relationships between compounds and treatments. The listing of compounds at the bottom of the heatmap, categorized by different chemical groups, is consistent with a systematic approach to data presentation. It enables a clear focus on the specific compounds that are central to the investigation, revealing how they are affected by the different treatments. This aligns with the common practice in chemical analysis of categorizing and presenting data for clarity and comparability [40; 43]. The supplementary graph (Figure 1) in the bottom right corner of the heatmap likely provides additional temporal or quantitative information. Such complementary information is often included to offer a comprehensive understanding of the data. In line with our approach, the literature emphasizes the importance of providing additional figures to enhance data interpretation and communicate complex findings effectively. In our Figure 2 plot, the proximity of data points is indicative of their similarity in the original dataset. Conditions that appear close to each other share similar VOC characteristics, while those positioned farther apart have more distinct profiles. For example, the Fungus and Control conditions are positioned close to each other, suggesting a degree of similarity in their profiles. This observation aligns with the concept that untreated apples and apples infected with fungus may exhibit comparable chemical profiles to some extent [33]. The arch-shaped trajectory formed by the conditions labeled in blue, such as Fun+Cin, Fun+Thy, Fun+Eug, and Fun+Thy+Cin+Eug, is indicative of incremental differences in their profiles. This suggests that these treatments follow a gradient of variations, with each condition along the path exhibiting distinct chemical profiles. Such gradual transitions in chemical composition among related treatments are well-documented in the scientific literature [23]. The conditions labeled in green, including Fun+Cin+Eug, Fun+Thy+Cin, and Fun+Thy+Eug, form a distinct cluster on the PCA plot, which implies that these treatments share unique characteristics that set them apart from the other conditions. Clustering in PCA plots is a common representation of groups of conditions or samples with similar chemical profiles or responses to treatments [23; 33]. Bridging the chemical insights with economic implications, our findings reveal a compelling narrative of essential oils (EOs) as not just a scientific intervention but a potential game-changer in post-harvest preservation. The nuanced chemical variations observed in our PCA plot directly correlate with the economic potential of these treatments. The distinct clustering and gradual chemical transitions suggest that specific EO combinations could offer targeted preservation strategies, each with unique economic advantages [44]. The economic viability of these essential oil treatments is particularly noteworthy. Our chemical analysis demonstrates that even subtle variations in EO combinations can significantly alter the chemical profile of treated apples. This aligns with economic research indicating that EOs provide cost-effective solutions for producers, with the ability to extend product shelf life and reduce economic losses [45]. The low concentration effectiveness observed in our chemical profiles translates to reduced application costs, making these treatments economically attractive for agricultural stakeholders [46]. Environmentally, the chemical diversity we have mapped shows the potential for residue-free preservation methods. The distinct clusters of EO treatments suggest that these natural compounds can provide robust protection without the environmental drawbacks of traditional preservatives.