## 3 Results and Discussion
When grouping the relevant data, for the sake of the clarity of the work, only a simple compilation of individual results was chosen, as shown in Figure 7.  
The analysis of the data shown in Figure 7 confirmed the conclusions of the RSM models that the extraction efficiency was lowest when using 40% ethanol and was significantly higher at higher concentrations of ethanol with extraction times of at least twenty days, especially if the ethanol was preheated at the beginning. Figure 6: Model of the response surface regarding the contents of chlorogenic acid in ethanol extracts of elderberry flowers obtained from fresh raw material that was initially treated with cold ethanol at a temperature of 25 \({}^{\circ}\)C.  
Figure 7: Profiles of chlorogenic acid values in ethanol extracts for the dried raw material obtained from fresh elderberry flowers, presented separately for the hot and cold extraction variants. In order to check how the freezing process can affect the extraction efficiency of the same raw material in comparison to non-frozen raw material, the results of variants 3 and 4 were analyzed. Raw material that was frozen and thawed after a month was subjected to identical experiments. Figure 8 shows the response surface curves in variant 3, i.e., after freezing elderberry flowers and performing hot ethanol extraction. The shapes of the curves in Figure 8 were statistically significantly affected by four variability factors (Figure 5c), of which the extraction time in linear terms was the most important. The concentration of ethanol, in contrast to freshly dried raw material, was less significant. The shapes of the curves were nevertheless similar to those of variants 1 and 2. A graphical representation of the RSM model in relation to the last, i.e., the fourth variant, in which the thawed raw material treated with cold ethanol was used, is shown in Figure 9. The Pareto diagram shown in Figure 5d confirmed the similarity of this variant to the third variant in terms of the significance and the order of the variability factors influencing the final course of the RSM model curves. Moreover, the extraction time in linear terms turned out to be the most important factor, with the ethanol concentration having less importance in shaping the curves. Although the distribution of the curves in variant 4 was similar to the other three variants, the contents of chlorogenic acid were lower than in variant 3, where warm ethanol was initially used, which can also be compared in Figure 4:0 This plot also shows that the extraction efficiency in relation to chlorogenic acid was the least differentiated in this variant, i.e., the profiles (for 40, 68 and 95%) were the closest to each other and somewhat flattened. Figure 4:1 Model of the response surface regarding the contents of chlorogenic acid in ethanol extracts of elderberry flowers obtained from previously frozen raw material that was initially treated with warm ethanol at 50 \({}^{\circ}\)C.  
Figure 4:2 Profiles of chlorogenic acid values in ethanol extracts for the dried raw material obtained from previously frozen elderberry flowers, presented separately for the hot and cold extraction variants. Figure 4:3 Model of the response surface concerning the contents of chlorogenic acid in ethanol extracts of elderberry flowers obtained from previously frozen raw material that was initially treated with cold ethanol at a temperature of 25 \({}^{\circ}\)C.  
The freezing of elderberry flowers and their subsequent drying had an impact on the effectiveness of chlorogenic acid extraction compared to the tests in which fresh raw material was dried. The subsequent use of 68 or 95% ethanol and previously frozen samples was usually less effective than using fresh material. An inverse relationship was found for the use of ethanol with a concentration of 40% (Figures 7 and 10), i.e., the contents of chlorogenic acid were higher in the variants where elderberry flowers were previously frozen compared to the variants with fresh raw material.