Artificial neural network optimization of Althaea rosea seeds polysaccharides and its antioxidant activity

作者：Liu, Feng; Liu, Wenhui; Tian, Shuge^*

来源：International Journal of Biological Macromolecules, 2014, 70: 100-107.

DOI：10.1016/j.ijbiomac.2014.06.040

• Althaea rosea seed
• Polysaccharide
• Artificial neural network model
• Orthogonal test design
• Antioxidant activities

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.

• 出版日期2014-9
• 单位新疆师范大学; 新疆教育学院; 新疆医科大学