화학공학소재연구정보센터
홈 로그인 로그아웃 연락처 사이트맵
Korean Journal of Chemical Engineering, Vol.34, No.8, 2284-2292, August, 2017
DOI10.1007/s11814-017-0106-1  Export Citation
Comparative study of modeling the stability improvement of sunflower oil with olive leaf extract
Selin Şahin†, Ezgi Sayim, and Ruya Samli1
  • Department of Chemical Engineering, Engineering Faculty, Istanbul University, 34320 Avcilar, Istanbul, Turkey
  • 1Department of Computer Engineering, Engineering Faculty, Istanbul University, 34320 Avcilar, Istanbul, Turkey
E-mail:
Commercially available sunflower oil was enriched in polyphenols by adding olive leaf extract. After extracting the dried and ground olive leaves with the assistance of homogenizer, total phenolic content (TPC) and oleuropein concentration of the extract were determined. The dried extract was partially dissolved into the sunflower oil to increase the quality and shelf-life of the oil enriched by the substances in the plants by means of solid-liquid extraction method. A face central composite design (FCCD) through response surface methodology (RSM) was used to investigate the effects of enrichment conditions (extract content, time and mixing speed) on the responses, TPC and oleuropein concentration of the enriched sunflower oil as well as to design of experiments, to model and to optimize the process. The enriched sunflower oil obtained at optimum conditions was evaluated in terms of its TPC, oleuropein, total carotenoid content (TCC), antioxidant activity (AA), peroxide value (PV) and induction time (IT), depending on those of the crude oil. Furthermore, artificial neural networks (ANN) were also employed to compare the predicted results of RSM.
Keywords:Edible Oils;Natural Antioxidants;Mathematical Modeling;Response Surface Methodology;Artificial Neural Networks
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