Microwave-assisted extraction of peppermint polyphenols – Artificial neural networks approach

Abstract

© 2019 Institution of Chemical Engineers Microwave-assisted extraction (MAE) of natural resources was the focus of investigation for great number of researches recently, however great potential of this technique is still not fully utilized. The aim of this work was evaluation of MAE parameters (ethanol concentration, extraction time and liquid-solid ratio) on total polyphenols yield (TP) and antioxidant activity (DPPH, FRAP and ABTS) of peppermint (Mentha piperita L.) extracts. Experiments were performed within face-centered central composite design and artificial neural network (ANN) approach was used for extraction system modeling. Good fit of applied model and experimental data was achieved for almost all responses which provided influence analysis and optimization. Ethanol concentration was the most influential MAE factor. TP, FRAP and ABTS were selected responses included in separate and multi-response optimization. Narrow range of ethanol concentration (49.75–51.07%) and lower L/S ratio (13.04–18.88 mL/g) provided different solutions for optimal conditions. LC–MS/MS analysis suggested that flavonoids, phenolic acids and stilbenes were the most dominant in polyphenolic fraction, while GC–MS results showed that menthomenthene, menthone, 1,8-cineole, D,L-limonene and p-cimene were the most abundant volatiles. Therefore, MAE was successfully applied for co-extraction of polyphenolics and terpenoid bioactives and production of liquid extracts with high antioxidant potential.