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投稿时间:2024-04-15
投稿时间:2024-04-15
中文摘要: 为优化太子参寡糖脱色工艺,利用紫外分光光度法,在单因素试验基础上,以树脂用量、脱色时间、pH 值为影响因素,以脱色率、回收率的综合评分为评价指标,采用Box-Behnken 响应面法结合反向传播(back-propagation,BP)神经网络建立网络模型优化寡糖脱色工艺。结果表明,最优脱色工艺为脱色时间3 h、AB-8 大孔吸附树脂用量8%、pH5,在此条件下太子参寡糖的脱色率为68.75%,回收率为84.95%,综合评分为96.17,优化后的工艺条件稳定可行。
Abstract:The decolorization process of Pseudostellaria heterophylla oligosaccharides was optimized via ultraviolet absorption spectrophotometry(UV). Based on single factor experiments,resin dosage,decolorization time,and pH value were taken as influencing factors,and the comprehensive score of decolorization rate and recovery rate was used as the evaluation indicator. Box-Behnken response surface methodology combined with back-propagation(BP)neural network was employed to establish a network model to optimize the oligosaccharide decolorization process.The results showed that the optimal decolorization process was as follows:decolorization time of 3 h,an AB-8 macroporous adsorption resin dosage of 8%,and pH5.Under these conditions,the decolorization rate and recovery rate of P. heterophylla oligosaccharides were 68.75% and 84.95%,respectively,and the comprehensive score was 96.17 points.The optimized process conditions were stable and feasible.
keywords: Pseudostellaria heterophylla oligosaccharides decolorization process optimization BP neural network
文章编号:202513012 中图分类号: 文献标志码:
基金项目:国家重点研发计划项目(2018YFC1708005);四川省药品监督管理局中药(民族药)标准提升(510201202102305);四川中医药高等专科学校2023 年度校级教师科研项目(23ZRYB02)
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