ZHANG Xue-jiao, JIN Chen-zhong, HU Yi-hong, TAN Xian-sheng, HE Li-fang, WANG Yan, CHEN Yong. Ultrasonic- assisted extraction technology optimization of polyphenols from Hibiscus syriacus L.[J]. Science and Technology of Food Industry, 2015, (21): 228-231. DOI: 10.13386/j.issn1002-0306.2015.21.039
Citation: ZHANG Xue-jiao, JIN Chen-zhong, HU Yi-hong, TAN Xian-sheng, HE Li-fang, WANG Yan, CHEN Yong. Ultrasonic- assisted extraction technology optimization of polyphenols from Hibiscus syriacus L.[J]. Science and Technology of Food Industry, 2015, (21): 228-231. DOI: 10.13386/j.issn1002-0306.2015.21.039

Ultrasonic- assisted extraction technology optimization of polyphenols from Hibiscus syriacus L.

  • The ultrasonic- assisted extraction of polyphenols from Hibiscus syriacus L. was optimized by using response surface methodology.According to the previous study of single variable test, an ultrasonic procedure for the extraction of polyphenols from H. syriacus L.was established. A three- level- four- factor test was employed in this study to optimize the factorial parameters ( ultrasonic power, ultrasonic time, ratio of solvents to raw material, and ethanol concentration) by employing Box- Behnken design ( BBD) of response surface methodology, and the polyphenols yield was taken as the response of the designed experiments. The results showed that the optimal extraction conditions for the extraction of polyphenols from H. syriacus L. were ultrasonic power 112 W, ultrasonic time 49 min, ratio of solvents to raw material 1∶36 ( g / m L) , and ethanol concentration 69%, respectively.Under these conditions, the yield of H. syriacus L.polyphenols was 20.507 mg / g, close to the theoretical value 20.518 mg / g.Extraction rate of the ultrasonic assisted extraction of polyphenols from H.syriacus L.was increased by 12.91% as compare to the ethanol extraction.The study revealed that this ultrasonic- assisted methodology, which was simply and high efficient, was suitable for extraction of H.syriacus L.polyphenols, and the regression model was reliable for the yield prediction in practice.
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