Optimization and modeling for heat reflux extraction of total yield, stevioside and rebaudioside-A from Stevia rebaudiana (Bertoni) leaves. Issue 7 (3rd May 2017)

• Record Type: Journal Article
• Authors: Ameer, Kashif; Bae, Seong-Woo; Jo, Yunhee; Chung, Namhyeok; Gao, Yaping; Kwon, Joong-Ho
• Is Part Of: Separation science and technology. Volume 52:Issue 7(2017)
• Page Start: 1193
• Page End: 1205
• Publication Date: 2017-05-03
• Subjects: ANN -- optimization -- RSM -- Stevia rebaudiana -- steviol glycosides; Separation (Technology) -- Periodicals; 660.284205
• DOI: 10.1080/01496395.2017.1285313
• Languages: English
• ISSNs: 0149-6395

Abstract

ABSTRACT: Stevia rebaudiana (Bertoni) leaves consist of stevioside and rebaudioside-A (Reb-A). This research sought to improve extraction of target steviol glycosides from stevia leaf powder using response surface methodology (RSM) and artificial neural networking (ANN) under these independent variables: ethanol concentration, X 1 (0–100%), extraction temperature, X 2 (55–75°C), and extraction time, X 3 (45–75 min). ANN outperformed as potential alternative to RSM in predicting optimum conditions. Maximum responses were obtained at 100% X 1, 55°C X 2, and 60 min X 3 . Heat reflux extraction proved superior to maceration extraction in terms of higher extraction yields with reduced energy consumption and CO2 emission.