Artificial Neural Network Modeling of Ultrasound-Assisted Polysaccharides Extraction from Potentilla anserina and Anti-Platelet Aggregation Activity

Abstract:

In this study, Ultrasound-assisted extraction (UAE) was used for polysaccharides extraction from Potentilla anserina. A computer-stimulated artificial neural network (ANN) was developed to get a correlation between the input variables and the output parameter. Finally, the optimal process conditions were obtained as follows: extraction temperature 55 °C, extraction time 55 min, ratio of liquid to solid 20:1, power 175 W. Under optimized conditions, ultrasound-assisted extraction had obviously higher yield of polysaccharides than the traditional heat reflux method. The optimization procedure showed a close interaction between the experimental and simulated values for polysaccharides extraction. The R² (0.99271) and MSE (0.0425) values of model suggested good fitness and generalization of the ANN. Moreover, the results also indicated that polysaccharides have inhibitory effect on ADP-induced platelet aggregation.

• Periodical: Applied Mechanics and Materials (Volume 618)
• Pages: 367-375
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.618.367
• Online since: August 2014
• Authors: Tao Guo, Jun Qing Wei, Ya Wang*, Dan Su, Zhen Zhang, Jian Ping Ma, Bing Yun Zhang, Ping Zhao
• Keywords: Artificial Neural Network (ANN), Platelet Aggregation, Polysaccharides, Potentilla anserina, Response Surface Methodology (RSM), Ultrasound-Assisted Extraction

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