Abstract
Background: This study is based on ethnobotanical observation and traditional medicinal utilization of fig (Ficus carica L.) by southwest Asian and Mediterranean populations.
Objective: Considering phenolics among the highly bioactive compounds for their numerous therapeutic applications, this investigation's first goal is to optimize their recovery by using Response Surface Methodology (RSM).
Methods: Prior to RSM, the single-factor method was applied to reveal the main factors influencing the extraction (solvent type, solvent concentration, sample˗to˗solvent ratio, temperature, and time of extraction). After using the optimal conditions of extraction, the second objective was the identification of fig leave phytochemicals by UPLC˗MS.
Results: The results of the preliminary optimization step through sequential methodology revealed that solvent concentration, extraction duration, and temperature were the main influencing factors. All these tested extraction parameters significantly influenced total phenolic contents (TPC) and DPPH-free radical scavenging activity (FRSA). RSM analysis using Box˗Behnken design showed that the optimal extraction conditions of total phenolic contents of fig leaves were 23.07% acetone, 51.82 °C, and 118.02 min with values of 29.44 mg GAE/g and 59.48% for TPC and FRSA, respectively. Eight phenolic compounds were detected, including chlorogenic, caffeic, and coumaric acids, rutin, isoquercetin, luteolin, quercetin, and kaempferol, well known for their bioactivities. Two non˗phenolic compounds were also found: The psoralen and an oxylipin, the 9˗oxo˗octadecadienoic acid detected for the first time in fig leaves.
Conclusion: The developed mathematical models have expressed a high level of significance through sequential and RSM optimization processes for phenolic antioxidants of Ficus carica leaves. The UPLC-MS analysis of the optimal extract revealed numerous phenolic compounds known for their bioactivities.
Keywords: Fig leaves, optimization, RSM, phenolic compounds, antioxidant activity, UPLC˗MS
Graphical Abstract
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