Optimization of water extraction technology of Xiangqin jiere granules by orthogonal design based on G1-entropy weight compared with BP neural network

CHENG Bingduo; LUO Liqin; LI Yuanzeng; JIANG Jie; CHEN Yiying; ZHAO Ji; XUE Rui; MA Yunshu

doi:10.6039/j.issn.1001-0408.2024.01.05

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Optimization of water extraction technology of Xiangqin jiere granules by orthogonal design based on G1-entropy weight compared with BP neural network

更新时间：2024-01-11

- Optimization of water extraction technology of Xiangqin jiere granules by orthogonal design based on G1-entropy weight compared with BP neural network
- ZHONGGUO YAOFANG Vol. 35, Issue 1, Pages: 27-32(2024)
- 作者机构：
  
  1.云南中医药大学中药学院，昆明　650500
  2.云南省傣医药与彝医药重点实验室，昆明　650500
  3.云南省高校外用给药系统与制剂技术研究重点实验室/云南省南药可持续利用研究重点实验室/云南省药食同源饮品工程中心，昆明　650500
- 作者简介：
- 基金信息：
- DOI：10.6039/j.issn.1001-0408.2024.01.05
  CLC： R917
- Published：15 January 2024，
  
  Received：04 July 2023，
  
  Revised：13 November 2023，
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程炳铎,罗丽琴,李元增等.基于G1-熵权法的正交实验设计对比BP神经网络优化香芩解热颗粒水提工艺 ^Δ[J].中国药房,2024,35(01):27-32.

CHENG Bingduo,LUO Liqin,LI Yuanzeng,et al.Optimization of water extraction technology of Xiangqin jiere granules by orthogonal design based on G1-entropy weight compared with BP neural network[J].ZHONGGUO YAOFANG,2024,35(01):27-32.
程炳铎,罗丽琴,李元增等.基于G1-熵权法的正交实验设计对比BP神经网络优化香芩解热颗粒水提工艺 ^Δ[J].中国药房,2024,35(01):27-32. DOI： 10.6039/j.issn.1001-0408.2024.01.05.

CHENG Bingduo,LUO Liqin,LI Yuanzeng,et al.Optimization of water extraction technology of Xiangqin jiere granules by orthogonal design based on G1-entropy weight compared with BP neural network[J].ZHONGGUO YAOFANG,2024,35(01):27-32. DOI： 10.6039/j.issn.1001-0408.2024.01.05.

摘要

目的

优化香芩解热颗粒的水提工艺。

方法

以加水倍数、提取时间、提取次数为考察因素，以连翘酯苷A、黄芩苷、连翘苷、千层纸素A-7-

-D-葡萄糖醛酸苷、汉黄芩苷、黄芩素、汉黄芩素含量和出膏率为评价指标，设计3因素3水平的正交实验，并利用G1-熵权法对上述指标进行综合评分，得正交实验优化的水提工艺。以9组正交实验结果为测试和训练数据，以加水倍数、提取时间、提取次数为输入节点，以综合评分为输出节点，利用BP神经网络建模进行网络模型优化和水提工艺寻优。验证并比较两种方法所得水提工艺参数，确定香芩解热颗粒的最佳水提工艺。

结果

香芩解热颗粒经正交实验优化后的水提工艺为加水倍数8倍、提取次数3次、提取时间1 h，综合评分为96.84分（RSD为0.90%）。BP神经网络建模优化后的水提工艺为加水倍数12倍、提取次数4次、提取时间0.5 h，综合评分为92.72分（RSD为0.77%），略低于正交实验所得工艺。

结论

本研究成功优化了香芩解热颗粒的最佳水提工艺，具体为加水倍数8倍、提取次数3次、提取时间1 h。

Abstract

OBJECTIVE

Optimizing the water extraction technology of Xiangqin jiere granules.

METHODS

The orthogonal test of 3 factors and 3 levels was designed， and comprehensive scoring was conducted for the above indexes by using G1-entropy weight to obtain the optimized water extraction technology of Xiangqin jiere granules with water addition ratio， extraction time and extraction times as factors， using the contents of forsythoside A， baicalin， phillyrin， oroxylin A-7-

-D-glycoside， wogonoside， baicalein and wogonin， and extraction rate as evaluation indexes. BP neural network modeling was used to optimize the network model and water extraction process using the results of 9 groups of orthogonal tests as test and training data， the water addition multiple， decocting time and extraction times as input nodes， and the comprehensive score as output nodes. Then the two analysis methods were compared by verification test to find the best water extraction process parameters.

RESULTS

The water extraction technology optimized by the orthogonal test was 8-fold water， extracting 3 times， extracting for 1 h each time. Comprehensive score was 96.84 （RSD＝0.90%）. The optimal water extraction technology obtained by BP neural network modeling included 12-fold water， extracting 4 times， extracting for 0.5 h each time. The comprehensive score was 92.72 （RSD＝0.77%）， which was slightly lower than that of the orthogonal test.

CONCLUSIONS

The water extraction technology of Xiangqin jiere granules is optimized successfully in the study， which includes adding 8-fold water， extracting 3 times， and extracting for 1 hour each time.

关键词

香芩解热颗粒水提工艺G1-熵权法正交实验BP神经网络

Keywords

water extraction technologyG1-entropy weightorthogonal testBP neural network

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