Extraction of Phenolic compounds from Artemisia absinthium L.: otimization through ultrassound assisted extraction using the Response surface methodology - Terisotto, María Sol (2021)
Plants throughout history have been a human resource available to be used for food and feeding and treatment of diseases, thus being considered as natural medicine agents. Plants are a huge source of secondary metabolites which have been described as strong health promoters and can be divided in primary metabolites, responsible for the processes of photosynthesis, respiration, solute transport, translocation, nutrient assimilation and differentiation; and secondary metabolites (terpenes, phenolic compounds, organic acids, among others), which are important for plant protection and pollination [1]. Recent studies have shown the relevant biological activities of phenolic compounds, consisting in their antioxidant, antimicrobial, and also cytotoxic effects activity. Among the medicinal plants it is possible to find the Artemisia absinthium L., an aromatic plant [2], that grows in temperate regions of Europe, Asia and North Africa. In addition to the renowned wormwood application in preparation of absinth and related beverages, ​A. absinthium has been used since ancient times for medical purposes. From the ethnopharmacological point of view, this plant has been used for its antihelmintic, stomachic, antibacterial, antifeedant, antifertility, antipyretic, cytostatic, antitumor, and antimalarial actions [3]. This work intended to optimize the extraction parameters of the ultrasound assisted extraction to obtain highly enriched extracts in phenolic compounds. This was possible using the response surface methodology (RSM) that is able to model data within certain parameters chosen by the researcher, but prior to start running multiple experiments without knowing the behaviors of certain factors involved, this technique would be only able to visualize certain magnitudes and not all the optimum point, therefore, strong complex and random screening analysis have to be performed in order to work the RSM in the optimal conditions and be able to properly model datasets. Thus, 4 different screening analyses (Fractional Factorial design, 2 factors multilevel, and 1 factorial design) were developed using a 12-run array mixture which was randomized and codify using statistical software (Design Expert). Three factors were tested in this experiment (Power [50-100%], Solvent percentage [0-50%] and Time [20-600s]) and for the interpretation of the fractional factorial design factors were aliases and estimated as Intercept= Intercept + ABC; A= A + BC; B= B + AC; and C= C + AB. Data was processed through an ANOVA analysis employing Pareto plots and the least significant difference (LSD) test. The response analysis was achieved through the phenolic compounds content, analyzed by HPLC-DAD-Ms. According to the obtained results, the UAE ideal conditions for the screening analysis were 100% power, 20% ethanol and 240 s allowing a total phenolic content in the concentrations of 13.79 mg of TPC/g of extract, being chlorogenic acid derivatives, the main compounds. These results highlight the richness of ​A. absinthium in phenolic compounds and validate the UAE as an efficient extraction technology.