Optimization of ultrasound-assisted extraction of bioactive chemicals from Hemidesmus indicus (L.) R.Br. using response surface methodology and adaptive neuro-fuzzy inference system

Food Sci Biotechnol. 2023 Jun 17;33(2):327-341. doi: 10.1007/s10068-023-01351-9. eCollection 2024 Jan.

Abstract

This study was designed to optimize the ultrasound-assisted extraction (UAE) of bioactive chemicals from Hemidesmus indicus (L.) R.Br. through RSM (response surface methodology) and ANFIS (adaptive neuro-fuzzy inference system). The effect of four independent parameters, methanol concentration (X1: 55-65%), temperature (X2: 30-40 °C), time (X3: 15-20 min) and particle size (X4: 0.5-1.00 mm) at five levels (- 2 ,- 1, 0, + 1, + 2) with respect to dependent parameters, total polyphenols content (TP) (y1), total flavonoids content (TF) (y2), %DPPHsc (y3), %ABTSsc (y4) and %H2O2sc (y5) were selected. The optimal extraction condition was observed at X1 = 65%, X2 = 40 °C, X3 = 20 min and X4 = 0.5 mm; under this circumstance, y1 = 352.85 mg gallic acid equivalents (GA)/g, y2 = 300.204 mg rutin equivalents (RU)/g and their antioxidant potentials (y3 = 81.33%, y4 = 65.04%, and y5 = 71.01%) has been attained. ANFIS was used to compare and confirm the optimized extraction parameter values. Further, GC-MS and LC-MS were performed to investigate the bioactive chemicals present in the optimized extract.

Supplementary information: The online version contains supplementary material available at 10.1007/s10068-023-01351-9.

Keywords: ANFIS; Hemidesmus indicus (L.) R.Br. bioactive chemicals; Optimization; RSM.