Optimization of ultrasound-assisted enzymatic extraction and <i>in vitro</i> antioxidant activities of polysaccharides extracted from the leaves of <i>Perilla frutescens</i>

LI, Huizhen; ZHANG, Hongjiao; ZHANG, Zhijun; CUI, Lixia

doi:10.1590/fst.29518

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Food Science and Technology

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Original Article • Food Sci. Technol 40 (1) • Jan-Mar 2020 • https://doi.org/10.1590/fst.29518 copy

Optimization of ultrasound-assisted enzymatic extraction and in vitro antioxidant activities of polysaccharides extracted from the leaves of Perilla frutescens

Authorship SCIMAGO INSTITUTIONS RANKINGS

Abstract

A Box-Behnken design was employed to optimize ultrasound-assisted enzymatic extraction of polysaccharides from perilla leaves. Four independent variables, namely, liquid-to-solid ratio, enzymatic time, enzymatic temperature, and ultrasonic power were investigated. Under the optimal liquid-to-solid ratio of 41:1, enzymatic time of 40 min, enzymatic temperature of 49 °C, and ultrasonic power of 204 W, the experimental polysaccharide yield was 3.84% (n = 3), which was close to the value predicted by response surface methodology (3.9%). Four polysaccharides (PLP1, PLP2, PLP3, and PLP4) were obtained with DEAE-cellulose-52 and Sephadex G-100 chromatography, and their antioxidant activities were investigated with various antioxidant assays in vitro. All the four polysaccharides possessed good antioxidant properties in a concentration-dependent manner, and PLP3 presented the highest antioxidant activity. Thus, the novel polysaccharides extracted from perilla leaves could be promising bioactive macromolecules that can be applied as potential antioxidants in medical and food industries.

Keywords:
perilla leaves; polysaccharide; ultrasound-assisted enzymatic extraction; antioxidant activities

Run	Liquid-solid ratio X1 (mL:g)	Enzymatic time X2 (min)	Enzymatic temperature X3 (°C)	Ultrasonic power X4 (W)	Polysaccharides yield (%)
Run	Liquid-solid ratio X1 (mL:g)	Enzymatic time X2 (min)	Enzymatic temperature X3 (°C)	Ultrasonic power X4 (W)	Experimental values	predicted values
1	40	50	50	240	2.59	2.49
2	50	40	60	200	2.89	2.91
3	30	40	60	200	2.16	2.25
4	40	40	50	200	3.87	3.89
5	30	50	50	200	2.28	2.29
6	50	30	50	200	2.51	2.48
7	40	40	50	200	3.87	3.89
8	40	40	50	200	3.97	3.89
9	40	40	50	200	3.87	3.89
10	40	50	50	160	2.28	2.27
11	40	40	40	240	2.51	2.58
12	40	50	40	200	2.98	3.10
13	40	30	60	200	2.87	2.84
14	40	30	50	160	2.03	2.07
15	50	40	50	160	2.07	2.16
16	40	30	40	200	2.25	2.34
17	40	30	50	240	2.59	2.53
18	30	30	50	200	2.68	2.67
19	50	40	40	200	2.86	2.70
20	30	40	40	200	2.91	2.82
21	30	40	50	240	2.24	2.24
22	40	40	50	200	3.86	3.89
23	40	50	60	200	2.24	2.24
24	50	40	50	240	2.79	2.87
25	30	40	50	160	2.24	2.25
26	40	40	60	160	2.14	2.05
27	40	40	40	160	2.44	2.40
28	50	50	50	200	3.02	3.01
29	40	40	60	240	2.54	2.56

source	Sum of squares	df	Mean square	F value	P-value^a Prob F
Model	10.05	14	0.718	84.58	< 0.0001
X ₁	0.221	1	0.221	26.09	0.0002
X ₂	0.018	1	0.018	2.078	0.1714
X ₃	0.103	1	0.103	12.10	0.0037
X ₄	0.354	1	0.354	41.68	< 0.0001
X ₁ X ₂	0.207	1	0.207	24.40	0.0002
X ₁ X ₃	0.152	1	0.152	17.93	0.0008
X ₁ X ₄	0.130	1	0.130	15.27	0.0016
X ₂ X ₃	0.462	1	0.462	54.50	< 0.0001
X ₂ X ₄	0.016	1	0.016	1.842	0.1963
X ₃ X ₄	0.027	1	0.027	3.209	0.0949
X ₁ ²	2.472	1	2.472	291.3	< 0.0001
X₂²	2.813	1	2.813	331.6	< 0.0001
X ₃ ²	2.334	1	2.334	275.1	< 0.0001
X ₄ ²	5.150	1	5.150	607.0	< 0.0001
Residual	0.119	14	0.008
Lack of fit	0.110	10	0.011	5.203	0.0630
Pure error	0.008	4	0.002
Cor total	10.17	28
R ²	0.9883
Adj.R²	0.9766
Adeq precision	27.74

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[1] *Corresponding author: zjzhang@nuc.edu.cn