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Optimization of phenolics and flavonoids extraction conditions of Curcuma Zedoaria leaves using response surface methodology

Overview of attention for article published in BMC Chemistry, October 2017
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Title
Optimization of phenolics and flavonoids extraction conditions of Curcuma Zedoaria leaves using response surface methodology
Published in
BMC Chemistry, October 2017
DOI 10.1186/s13065-017-0324-y
Pubmed ID
Authors

Nur Fauwizah Azahar, Siti Salwa Abd Gani, Nor Fadzillah Mohd Mokhtar

Abstract

This study focused on maximizing the extraction yield of total phenolics and flavonoids from Curcuma Zedoaria leaves as a function of time (80-120 min), temperature (60-80 °C) and ethanol concentration (70-90 v/v%). The data were subjected to response surface methodology (RSM) and the results showed that the polynomial equations for all models were significant, did not show lack of fit, and presented adjusted determination coefficients (R(2)) above 99%, proving their suitability for prediction purposes. Using desirability function, the optimum operating conditions to attain a higher extraction of phenolics and flavonoids was found to be 75 °C, 92 min of extraction time and 90:10 of ethanol concentration ratios. Under these optimal conditions, the experimental values for total phenolics and flavonoids of Curcuma zedoaria leaves were 125.75 ± 0.17 mg of gallic acid equivalents and 6.12 ± 0.23 mg quercetin/g of extract, which closely agreed with the predicted values. Besides, in this study, the leaves from Curcuma zedoaria could be considered to have the strong antioxidative ability and can be used in various cosmeceuticals or medicinal applications.

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Mendeley readers

The data shown below were compiled from readership statistics for 181 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 181 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 27 15%
Student > Master 21 12%
Student > Ph. D. Student 17 9%
Researcher 10 6%
Lecturer 9 5%
Other 16 9%
Unknown 81 45%
Readers by discipline Count As %
Agricultural and Biological Sciences 25 14%
Chemistry 16 9%
Pharmacology, Toxicology and Pharmaceutical Science 12 7%
Biochemistry, Genetics and Molecular Biology 8 4%
Chemical Engineering 7 4%
Other 27 15%
Unknown 86 48%