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Ethanol–water binary solvent affects phenolic composition and antioxidant ability of Pistacia lentiscus L. fruit extracts: a theoretical versus experimental solubility study

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Abstract

Pistacia lentiscus L. fruits are an excellent source of phenolic compounds endowed with antioxidant activities. Ethanol–water mixtures are in focus for plant extracts preparation due to their acceptability for human consumption. In this study, the effect of ethanol concentration in ethanol/water (EtOH/H2O) extraction solvent on the solubility of target phenolic compounds was firstly predicted using COnductor-like Screening MOdel for Real Solvents (COSMO-RS). Subsequently, the computational results were confirmed experimentally based on extraction yield, phenolic composition, antioxidant activity and RP-HPLC analysis. Extractions were achieved using bead milling by varying EtOH concentrations in order to prepare a suitable extract that could be safely used for food purposes. The obtained results highlighted a good correlation between COSMO-RS simulations and experiments. The highest polyphenol and flavonoid contents (292.04 mg GAE/g DR and 11.07 mg CE/g DR, respectively) were achieved with 70% EtOH, which is in correlation with RP-HPLC quantitative analysis, while the highest anthocyanin content (94.00 mg C3OG/100 g DR) was obtained with 80% EtOH. Concerning antioxidant activity, the best DPPH· radical scavenging activity (IC50 = 2.39 µg/mL) was obtained with 70% EtOH. Reverse Phase High Performance Liquid Chromatography (RP-HPLC) analysis showed that gallic acid was the major compound of Pistacia lentiscus fruits in all EtOH/H2O mixtures. These findings showed that the EtOH/H2O (70/30) mixture is the most suitable to obtain P. lentiscus fruit extracts with the highest phenolic compounds content and antioxidant activity.

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Chaabani, E., Abert Vian, M., Bettaieb Rebey, I. et al. Ethanol–water binary solvent affects phenolic composition and antioxidant ability of Pistacia lentiscus L. fruit extracts: a theoretical versus experimental solubility study. Food Measure 17, 4705–4714 (2023). https://doi.org/10.1007/s11694-023-01983-9

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