Multi-response optimization of phenolic antioxidants from white tea (Camellia sinensis L. Kuntze) and their identification by LC-DAD-Q-TOF-MS/MS

The aim of this study was to model the extraction of phenolic antioxidants and identify the principal individual phenolic compounds of white tea by LC-DAD-MS/MS. A Box-Behnken design was applied to evaluate the effects of time, temperature and ethanol concentration in the extraction of phenolics and in vitro antioxidant activity. All mathematical models proposed by multiple regression analysis were significant (P < 0.001) and could explain up to more than 85% of the variance (R-adj(2) > 0.80). A simultaneous optimization was performed using DPPH, ABTS, FRAP, (-)-epigallocatechin gallate, and (-)-epicatechin gallate to maximize the phenolic extraction and suggested optimum conditions of 10 min, 66 degrees C and 30% ethanol solution, with absolute error lower than 7%. The suggested optimum conditions were confirmed by external validation. The principal individual compounds identified by mass spectrometry were gallic acid, 5-galloylquinic acid, caffeine, theobromine, gallocatechin, epigallocatechin, epicatechin, epigallocatechin gallate, and epicatechin gallate. (C) 2015 Elsevier Ltd. All rights reserved.