A novel enzyme-assisted ultrasonic approach for highly efficient extraction of resveratrol from Polygonum cuspidatum |
| |
Institution: | 1. Department of Biotechnology, Thapar Institute of Engineering and Technology, #BC-213, BC-Link Block (First floor), Patiala, Punjab 147001, India;2. Post-doctoral Fellow, Institute of Plant Protection, The Volcani Centre, Agriculture Research Organization, HaMaccabim Road 68, POB 15159, Rishon Lezion 7528809, Israel;3. Assistant Professor, School of Applied Sciences, Suresh Gyan Vihar University, Mahal Rd, Mahal, Jagatpura, Jaipur, Rajasthan 302017, India;4. University Institute of Biotechnology, Chandigarh University, H-95 Chandigarh-Ludhiana Highway, Mohali, Punjab India |
| |
Abstract: | Resveratrol is a promising multi-biofunctional phytochemical, which is abundant in Polygonum cuspidatum. Several methods for resveratrol extraction have been reported, while they often take a long extraction time accompanying with poor extraction yield. In this study, a novel enzyme-assisted ultrasonic approach for highly efficient extraction of resveratrol from P. cuspidatum was developed. According to results, the resveratrol yield significantly increased after glycosidases (Pectinex® or Viscozyme®) were applied in the process of extraction, and better extraction efficacy was found in the Pectinex®-assisted extraction compared to Viscozyme®-assisted extraction. Following, a 5-level-4-factor central composite rotatable design with response surface methodology (RSM) and artificial neural network (ANN) was selected to model and optimize the Pectinex®-assisted ultrasonic extraction. Based on the coefficient of determination (R2) calculated from the design data, ANN model displayed much more accurate in data fitting as compared to RSM model. The optimum conditions for the extraction determined by ANN model were substrate concentration of 5%, acoustic power of 150 W, pH of 5.4, temperature of 55 °C, the ratio of enzyme to substrate of 3950 polygalacturonase units (PGNU)/g of P. cuspidatum, and reaction time of 5 h, which can lead to a significantly high resveratrol yield of 11.88 mg/g. |
| |
Keywords: | Resveratrol Enzyme-assisted ultrasonic approach Response surface methodology Artificial neural network |
本文献已被 ScienceDirect 等数据库收录! |
|