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Optimization of enzymatic esterification of dihydrocaffeic acid with hexanol in ionic liquid using response surface methodology

Overview of attention for article published in BMC Chemistry, May 2017
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Title
Optimization of enzymatic esterification of dihydrocaffeic acid with hexanol in ionic liquid using response surface methodology
Published in
BMC Chemistry, May 2017
DOI 10.1186/s13065-017-0276-2
Pubmed ID
Authors

Somayeh Gholivand, Ola Lasekan, Chin Ping Tan, Faridah Abas, Leong Sze Wei

Abstract

Developing an efficient lipophilization reaction system for phenolic derivatives could enhance their applications in food processing. Low solubility of phenolic acids reduces the efficiency of phenolic derivatives in most benign enzyme solvents. The conversion of phenolic acids through esterification alters their solubility and enhances their use as food antioxidant additives as well as their application in cosmetics. This study has shown that lipase-catalyzed esterification of dihydrocaffeic acid with hexanol in ionic liquid (1-butyl-3-methylimidazoliumbis (trifluoromethylsulfonyl) imide) was the best approach for esterification reaction. In order to achieve the maximum yield, the process was optimized by response surface methodology (RSM) based on a five-level and four independent variables such as: dosage of enzyme; hexanol/dihydrocaffeic acid mole ratio; temperature and reaction time. The optimum esterification condition (Y = 84.4%) was predicted to be obtained at temperature of 39.4 °C, time of 77.5 h dosage of enzyme at 41.6% and hexanol/dihydrocaffeic acid mole ratio of 2.1. Finally, this study has produced an efficient enzymatic esterification method for the preparation of hexyl dihydrocaffeate in vitro using a lipase in an ionic liquid system. Concentration of hexanol was the most significant (p < 0.05) independent variable that influenced the yield of hexyl dihydrocaffeate. Graphical abstract Synthesis of different Hexyl dihydrocaffeates in ionic liquid.

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Mendeley readers

The data shown below were compiled from readership statistics for 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 25 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 5 20%
Professor 4 16%
Professor > Associate Professor 2 8%
Researcher 2 8%
Other 1 4%
Other 0 0%
Unknown 11 44%
Readers by discipline Count As %
Chemistry 4 16%
Agricultural and Biological Sciences 3 12%
Chemical Engineering 2 8%
Environmental Science 1 4%
Biochemistry, Genetics and Molecular Biology 1 4%
Other 0 0%
Unknown 14 56%