Kinetics of Ultrasound-assisted Extraction of Flavonoids and Triterpenes and Structure Characterization of Chinese Northeast Black Bee Propolis
Qingzhi Ding, Ricardo Antonio Wu-Chen, Qi Wu, Hanfei Jiang, Ting Zhang, Lin Luo, Haile Ma*, Shiqiao Ma and Ronghai He* Author for corresponding; e-mail address: mhl@ujs.edu.cn
Volume: Vol.46 No.1 (January 2019)
Research Article
DOI:
Received: 20 March 2018, Revised: -, Accepted: 23 August 2018, Published: -
Citation: Ding Q., Wu-chen R.A., Wu Q., Jiang H., Zhang T., Luo L., et al., Kinetics of Ultrasound-assisted Extraction of Flavonoids and Triterpenes and Structure Characterization of Chinese Northeast Black Bee Propolis, Chiang Mai Journal of Science, 2019; 46(1): 72-92.
Abstract
Flavonoids and triterpenes from Chinese northeast black bee propolis were extracted using pulsed ultrasound-assisted extraction. The influences of extraction parameters such as ethanol concentration, liquid-solid ratio, temperature, time, and ultrasonic on-time/off-time on the extraction yield were investigated. The kinetics of the extraction process was studied. The second-order kinetic models were applied to fit the experimental data. Effects of ultrasound on microstructure of propolis were studied by Scanning Electron Microscope and Atomic Force Microscope. The results showed the great influence of extraction parameters on the extraction yield. Optimum extraction conditions were determined as: 80% ethanol concentration, 30:1 mL/g ratio, 53 °C, 16 min and 10s/5s on-time/off-time. Under these conditions, 60.34% of flavonoids and triterpenes extraction yield was achieved. Scanning electron microscope and atomic force microscope analysis indicated that the propolis matrix structure changed evidently during ultrasound. GC-MS and LC-MS analyses showed that terpenes and flavonoids content were consistent by both extraction methods, thus UAE resulted to be more efficient compared to conventional extraction by achieving extraction in shorter time. Kinetic predictions for yields distributions of ultrasound-assisted extraction are highly in agreement with the experimental data, which implies that the proposed model can be used to predict the mechanisms of the extraction process.
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