## 4 Conclusions  
The conducted research showed that the use of the RSM method to assess the effectiveness of chlorogenic acid extraction is very effective. Statistical analyses confirmed the higher effectiveness of chlorogenic acid extraction in the variants in which warm ethanol (at a temperature of 50 \({}^{\circ}\)C) was used with dried elderberry flowers compared to the variants in which cold ethanol (at a temperature of 25 \({}^{\circ}\)C) was used.  
The freezing of elderberry flowers and their subsequent drying caused a relatively slight decrease in the effectiveness of chlorogenic acid extraction compared to freshly dried raw material but only in the case of using 68% or 95% ethanol. In the case of samples obtained with the use of 40% ethanol, the efficiency of the extraction after freezing elderberry flowers was higher.  
In all four analyzed variants of the experiment, significant impacts of variability factors, i.e., the ethanol concentration and extraction time in linear or square terms as well as their interaction, on the response surface methodology models were found.  
In the case of freshly dried raw material, the concentration of ethanol had the greatest impact on the optimization response surface models, while the extraction time had the greatest impact for previously frozen raw material.  
The response surface models indicated the possibility of shortening the extraction time (to 20 days instead of 30) and using ethanol with a lower concentration (approx. 68% instead of higher concentrations, even up to 95%) with the acceptance of only a slightly lower yield (i.e., the content of chlorogenic acid), especially in the case of frozen raw material.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Variant of the** **Experiment** & **Formula for Calculating the Content of Chlorogenic Acid (Z)** \\  & **Depending on the Concentration of Ethanol (x) and the Extraction Time (y)** \\ \hline
1 & \(Z=-397.7552+16.4189*\chi-0.1264*\chi^{2}+2.4900*y-0.2958*y^{2}+0.2004*\chi \\ \hline
2 & \(Z=-196.0283+8.9028*\chi-0.0715*\chi^{2}+2.0315*y-0.2967*\chi^{2}+0.1788* \chi y\) \\ \hline
3 & \(Z=-53.11946+8.5781*\chi-0.0748*\chi^{2}-0.5344*y-0.1536*y^{2}+0.1418*\chi y\) \\ \hline
4 & \(Z=44.43774+3.9641*\chi-0.0372*\chi^{2}+0.2506*y-0.1305*y^{2}+0.1099*\chi y\) \\ \hline \hline \end{tabular}
\end{table}
Table 2: Formulas for Calculating the Content of Chlorogenic Acid (ug/cm3) in ethanol extracts, depending on the research variant.  
Based on the obtained results, it can be concluded that the optimization of the efficiency of the technological processes in the processing of herbs can be supported by the use of advanced computational techniques such as response surface analysis.  
Conceptualization, M.O. and A.N.-O.; methodology, M.O. and A.N.-O.; software, M.O.; validation, M.O., A.N.-O. and D.M.; formal analysis, M.O. and A.N.-O.; investigation, M.O., A.N.-O. and D.M.; resources, M.O. and D.M.; data curation, M.O.; writing--original draft preparation, M.O.; writing--review and editing, A.N.-O. and M.O.; visualization, M.O.; supervision, M.O. and A.N.-O. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The data are archived on the server of the Wroclaw University of Environmental and Life Sciences.  
The authors declare no conflict of interest.