Journal
INTERNATIONAL JOURNAL OF BIOLOGICAL MACROMOLECULES
Volume 70, Issue -, Pages 100-107Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.ijbiomac.2014.06.040
Keywords
Althaea rosea seed; Polysaccharide; Artificial neural network model; Orthogonal test design; Antioxidant activities
Funding
- Xinjiang Science and Technology Fund [2014211C011]
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A combination of an orthogonal L-16(4)(4) test design and a three-layer artificial neural network (ANN) model was applied to optimize polysaccharides from Althaea rosea seeds extracted by hot water method. The highest optimal experimental yield of A. rosea seed polysaccharides (ARSPs) of 59.85 mg/g was obtained using three extraction numbers, 113 min extraction time, 60.0% ethanol concentration, and 1:41 solid-liquid ratio. Under these optimized conditions, the ARSP experimental yield was very close to the predicted yield of 60.07 mg/g and was higher than the orthogonal test results (40.86 mg/g). Structural characterizations were conducted using physicochemical property and FTIR analysis. In addition, the study of ARSP antioxidant activity demonstrated that polysaccharides exhibited high superoxide dismutase activity, strong reducing power, and positive scavenging activity on superoxide anion, hydroxyl radical, 2,2-diphenyl-1-picrylhydrazyl, and reducing power. Our results indicated that ANNs were efficient quantitative tools for predicting the total ARSP content. (C) 2014 Elsevier B.V. All rights reserved.
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