首页> 中文期刊> 《安徽农业科学》 >人工神经网络-遗传算法优化密花石斛多糖超声辅助提取工艺

人工神经网络-遗传算法优化密花石斛多糖超声辅助提取工艺

         

摘要

[Objective] To investigate the process parameters for ultrasonic-assisted extraction of polysaccharides from Dendrobium densiflorum.[Method] Based on single-factor experiments and Box-Behnken design,artificial neural networks (ANN) were combined with genetic algorithms (GA) to optimize the ultrasonic-assisted extraction process parameters of polysaccharides from D.densiflorum.[Result] The optimal process parameters for ultrasonic-assisted extraction of D.densiflorum polysaccharides were as follows:ultrasonic temperature 59 ℃,ultrasonic power 424 W and ultrasonic time 99 min.The polysaccharide extraction yield was 37.99 mg/g under these conditions.[Conclusion] The study optimized the ultrasonic-assisted extraction parameters of polysaccharides from D.densiflorum,which will provide a reference for further development of D.densiflorum.%[目的]研究密花石斛多糖超声波辅助提取的工艺参数.[方法]在单因素试验的基础上,采用Box-Behnken试验设计,运用人工神经网络结合遗传算法优化密花石斛多糖的超声波辅助提取工艺参数.[结果]密花石斛多糖超声辅助提取的最佳工艺参数为:超声温度59℃,超声功率424 W,超声时间99 min;在此工艺条件下,多糖的提取率为37.99 mg/g.[结论]试验优选了密花石斛多糖的超声波辅助提取工艺,为密花石斛的进一步开发研究提供依据.

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