Ultrasound-aided enzyme-assisted efficient extraction of bioactive compounds from Gymnema sylvestre and optimization as per response surface methodology

被引:9
|
作者
Saeed, Ramsha [1 ]
Ahmed, Dildar [1 ]
Mushtaq, Muhammad [2 ]
机构
[1] Forman Christian Coll, Dept Chem, Lahore, Pakistan
[2] Govt Coll Univ, Dept Chem, Lahore, Pakistan
来源
关键词
Gymnema sylvestre; Enzyme -assisted extraction optimization; Bioactive compounds; Polyphenols; Antioxidant activity; PHENOLIC-COMPOUNDS; LEAVES; PLANT;
D O I
10.1016/j.scp.2022.100818
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
The herb Gymnema sylvestre is known for its bioactivities. Though several studies have reported extraction of medicinal compounds from it, extraction efficiency is still an issue. The goal of the current project was, therefore, to explore an efficient and green method for the extraction of medicinal biomolecules from the plant with extraction optimization. Ultrasound-aided enzyme -assisted extraction (UAE-EAE) was carried out as per RSM (response surface methodology) with four factors, time, temperature, pH, and amount of enzyme, and the responses were % yield, TPC, TFC, and antioxidant activity. For the highest desirability, time, temperature, pH, and amount of enzyme cocktail were 150 min, 64.80 ?, 5.64, and 7.49 mL, respectively. On optimized conditions, % yield, TPC, TFC and antioxidant activity were 32.35%, 108.79 mg/g gallic acid equivalents, 54.20 mg/g rutin equivalents and 68.15%, respectively. The EAE-UAE proved to be highly effective as it was almost 3 times more efficient than the conventional maceration carried out as the control. Morphological studies conducted by scanning electron microscopy (SEM) confirmed the formation of large cavities in plant cell walls (30.6-56.3 mu m) as compared to the control (6.2-11.4 mu m). The Energy Dispersive X-ray (EDX) analysis of the sample showed the presence of various elements (Zn, Al, K, Ca, Se, Mg, Na, Mo, S, P, and Cl) in it. Validation studies had very low error rates (1.47-4.08%) in the responses indicating high fitting of the predicted models. The discovered method was not only efficient but also green and relatively cost-effective and has the potential to be explored for application on an industrial scale.
引用
收藏
页数:15
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