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Optimization and Modeling of Ultrasound-assisted Extraction of Polysaccharides from Cynomorium songaricum and α-glucosidase Inhibitory Activity

並列摘要


In the study, the extraction processing of polysaccharides from Cynomorium songaricum was optimized by Response Surface Methodology (RSM) and projected by a computer-stimulated Artificial Neural Network (ANN). The optimal process conditions were obtained as follows: extraction temperature 55℃, solid-liquid ratio 1:10, power 175W. Under optimized conditions, The R^2 value of 0.99391 and an MSE value of 0.0495 suggested a good generalization of the network and showed a good agreement between the experimental and predicted values. On the other hand, the results also suggested that polysaccharides from Cynomorium songaricum had α-glucosidase inhibitory activity with an IC_(50) of 8.316μg/mL and may be a potential α-glucosidase inhibitory.