Development of a Simple and Rapid HPLC-UV Method for Ultrasound-assisted Deep Eutectic Solvent Extraction optimization of Ferulic Acid and Antioxidant Activity from Ixora javanica Flowers

Nina Dewi Oktaviyanti, Finna Setiawan, Kartini Kartini, Azminah Azminah, Christina Avanti, Hayun Hayun, Abdul Mun'im

Research output: Contribution to journalArticlepeer-review

Abstract

In this work, we developed an environmental friendly extraction method to enhance ferulic acid yields and antioxidant activity of I. javanica flowers using Ultrasound-assisted extraction (UAE) method and Deep Eutectic Solvents as green solvent. To optimize the extraction method, response surface method analysis using Box Behnken designs were conducted. The results showed that the optimum extraction conditions for ferulic acid yields, DPPH scavenging capacity, ABTS scavenging capacity and Ferric-Reducing Antioxidant Power featured an extraction time of 40 min, 25% water content, and solid-to-liquid ratio of 1/27 g/mL. In this study, a rapid and simple analytical method was also validated for the quantification of ferulic acid in I. javanica flower extract using LC-UV method. The developed method was carried out under following condition: isocratic mobile phase of acetonitrile/formic acid pH 2.55 (30:70), a flow rate of 0.8 ml/min, detection at 321 nm, and C-18 column (250 mm x 4.6 mm, 5 µm). The ferulic acid and antioxidant activity of the extract obtained from the developed were higher than ethanolic extract under same extraction condition. In summary, the results of this study can provide more effective and efficient extraction method by applying the green extraction principle and be recommended to provide new potential antioxidant raw material.

Original languageEnglish
Pages (from-to)165-175
Number of pages11
JournalSouth African Journal of Chemical Engineering
Volume40
DOIs
Publication statusPublished - Apr 2022

Keywords

  • Ferulic acid, Antioxidant
  • Ixora javanica, Ultrasound-assisted extraction, Deep eutectic solvents, Response surface methodology

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