# Seasonal Variability of Volatile Components in _Calypogeia__integristipula_
## 2 Results and Discussion
### Statistical Analysis of the Obtained Results  
Multivariate classification analyses (PCA and heat map) performed on all 79 detected chemical compounds confirm the differentiation of the content of these compounds in the tested samples depending on the time at which the samples were collected. Four significant principal components (PCs) included in the PCA model explain 84.4% of the variation (R\({}^{2}\)X) and 71.0% of the predicted variation (Q\({}^{2}\)). Based on the value of the predictive variability Q\({}^{2}\), it was determined that the optimal number of principal components in the model is three. The 3D scatterplot revealed the presence of four distinct groups correlated with the collection time (Figures 3 and S7). The PC1 axis divided the samples collected in spring and autumn from the samples collected in summer, and these originated from the in vitro culture. The second principal component (PC2 axis) distinguishes in vitro culture samples from all others, while samples collected in spring and autumn are very well differentiated by the PC3 axis (Figures 3, S1-S3 and S8-S10). It should be emphasised that the variation between individual samples from different regions collected in the same growing season is low (Figures 3, S1-S3 and S8-S10). Figure 3: Three-dimensional PCA scatter plot based on all 79 detected compounds in samples of _Calypogeia intersigtipuula_ collected in spring, summer, and autumn in 2022 and in vitro. The percentage of explained variance (R\({}^{2}\)X) is 50.5% for PC1, 18.6% for PC2, 12.9% for PC3, and predictive ability (Q\({}^{2}\)) is 46.7%, 15.3%, and 36.0%, respectively. Samples collected in spring and autumn, samples collected in summer, and those originating from in vitro culture differ mainly in the content of compounds **1**, **10**, **23**, **30**, **42**, **45**, **52**, **59**, **65**, **67**, and **78**, which have the largest contribution to the PC1 axis. Variables **23**, **42**, and **45** had positive loading, whereas **1**, **10**, **30**, **52**, **59**, **65**, **67**, and **78** had negative loading. Samples collected in spring and autumn have a lower concentration of anastreptene (**23**), \(\delta\)-selinene (**42**), and bicyclogermacene (**45**) than those collected in summer and from in vitro culture (Table 7). Compounds **2**, **3**, **9**, **16**, **39**, and **57** distinguish samples grown in in vitro culture as the compounds have the highest loadings in PC2. Variable **39** had positive loading, **2**, **3**, **9**, **16**, and **57** were negatively loaded. Culture plants were characterised by lower concentrations of the compound **39** (not identified) and a higher content of pentanal (**2**), hexanal (**3**), benzenemethanol (**9**), phenoxyethanol (**16**), and compound **57** (not identified) than in plants growing under natural conditions. The samples collected in spring and autumn differ in the content of compounds **4** (positive loading), **13**, and **76** (negative loading), which contribute greatly to PC3. The plants collected in spring had a higher content of 1-hexanol (**4**), while the concentration of benzeneethanol (**13**) and germacra-4(15),5,10(14)-trien-1-\(\alpha\)-ol (**76**) was lower than in those collected in autumn (Table 7). The loading plots showing the contribution of individual variables to the first three principal components are presented in Figures S4-S6 and S11-S13. Similarly, the differentiation of the samples analysed according to the growing season was shown by the heat map. The analysed samples are grouped into two main clusters correlated with the date of their collection. The first cluster includes samples collected in spring and autumn, which form separate groups, and the second group includes samples collected in summer and from in vitro culture.