Optimization of salt-processing technology for <italic style="font-style: italic">Anemarrhena asphodeloides</italic> by Box-Behnken response surface methodology versus GA-BP neural network

PAN Luoxing; ZHAO Yiman; YUAN Hui; LI Zehua; XUE Dongsheng; ZHAO Qing

doi:10.6039/j.issn.1001-0408.2025.19.07

您当前的位置：

首页 >

文章列表页 >

Optimization of salt-processing technology for Anemarrhena asphodeloides by Box-Behnken response surface methodology versus GA-BP neural network

更新时间：2025-10-11

- Optimization of salt-processing technology for Anemarrhena asphodeloides by Box-Behnken response surface methodology versus GA-BP neural network
- ZHONGGUO YAOFANG Vol. 36, Issue 19, Pages: 2399-2403(2025)
- 作者机构：
  
  1.河北大学中医学院河北省中医药管理局中药资源产业化过程协同创新重点研究室，河北保定　071000
  2.河北百合健康药业有限公司，河北保定　071299
  3.保定市市场监督管理局，河北保定　071023
- 作者简介：
- 基金信息：
- DOI：10.6039/j.issn.1001-0408.2025.19.07
  CLC： R943.1
- Received：30 April 2025，
  
  Revised：2025-08-22，
  
  Accepted：25 August 2025，
  
  Published：15 October 2025
- 稿件说明：
移动端阅览
潘罗星,赵一曼,袁慧,等.Box-Behnken响应面法对比GA-BP神经网络优化知母盐炙工艺[J].中国药房,2025,36(19):2399-2403.

PAN Luoxing,ZHAO Yiman,YUAN Hui,et al.Optimization of salt-processing technology for Anemarrhena asphodeloides by Box-Behnken response surface methodology versus GA-BP neural network[J].ZHONGGUO YAOFANG,2025,36(19):2399-2403.
潘罗星,赵一曼,袁慧,等.Box-Behnken响应面法对比GA-BP神经网络优化知母盐炙工艺[J].中国药房,2025,36(19):2399-2403. DOI： 10.6039/j.issn.1001-0408.2025.19.07.

PAN Luoxing,ZHAO Yiman,YUAN Hui,et al.Optimization of salt-processing technology for Anemarrhena asphodeloides by Box-Behnken response surface methodology versus GA-BP neural network[J].ZHONGGUO YAOFANG,2025,36(19):2399-2403. DOI： 10.6039/j.issn.1001-0408.2025.19.07.

摘要

目的

优化知母的盐炙工艺。

方法

以闷润时间、炒制温度及炒制时间为考察因素，以芒果苷、新芒果苷、异芒果苷、知母皂苷BⅡ、知母皂苷AⅢ、知母皂苷BⅢ、总黄酮、总皂苷含量为考察指标，采用Box-Behnken响应面法设计实验，利用熵权法确定各指标权重，并计算综合评分，得Box-Behnken响应面法优化的知母盐炙工艺。以17组Box-Behnken响应面法结果为基础，以闷润时间、炒制温度、炒制时间为输入层，以综合评分为输出层，采用遗传算法（GA）-反向传播（BP）神经网络优化知母盐炙工艺。验证并比较两种方法所得盐炙工艺参数，以确定知母的最佳盐炙工艺。

结果

经Box-Behnken响应面法优化的知母盐炙工艺条件为闷润时间23 min、炒制温度160 ℃、炒制时间12 min，综合评分为63.370 2分；GA-BP神经网络优化后的工艺条件为闷润时间24 min、炒制温度163 ℃、炒制时间12 min，综合评分为65.163 8分。GA-BP神经网络优化结果优于Box-Behnken响应面法所得结果。

结论

本研究成功优化了知母的盐炙工艺，具体为每50 g饮片加入0.1 g/mL盐水15 mL，闷润24 min后，在163 ℃条件下炒制12 min。

Abstract

OBJECTIVE

To optimize the salt-processing technology for

Anemarrhena asphodeloides

METHODS

Taking soaking time， stir-frying temperature， and stir-frying time as factors， Box-Behnken response surface methodology was employed to optimize the salt-processing technology of

A. asphodeloides

using the contents of mangiferin， neomangiferin， isomangiferin， timosaponin BⅡ， timosaponin AⅢ， timosaponin BⅢ， total flavonoids， and total saponins as evaluation indicators. The entropy weight method was applied to determine the weight of each indicator and calculate the comprehensive score. Based on the 17 sets of Box-Behnken response surface methodology results， a genetic algorithm （GA）-back propagation （BP） neural network was used to further optimize the salt-processing technology， with soaking time， stir-frying temperature， and stir-frying time as input layers and the comprehensive score as the output layer. The salt

-processing parameters obtained from the two methods were validated and compared to determine the optimal salt-processing technology for

A. asphodeloides

RESULTS

The optimal salt-processing conditions obtained via the Box-Behnken response surface methodology were as follows： soaking time of 23 min， stir-frying temperature of 160 ℃， and stir-frying time of 12 min， yielding a comprehensive score of 63.370 2. The GA-BP neural network optimization resulted in the following conditions： soaking time of 24 min， stir-frying temperature of 163 ℃， and stir-frying time of 12 min， with a comprehensive score of 65.163 8. The GA-BP neural network optimization outperformed the results obtained by Box-Behnken response surface methodology.

CONCLUSIONS

This study successfully optimized the salt-processing technology for

A. asphodeloides.

Specifically， the technology involves adding 15 mL of 0.1 g/mL saline solution to 50 g of the herbal slices， allowing them to moisten for 24 minutes， and then stir-frying at 163 ℃ for 12 minutes.

关键词

Keywords

references

国家药典委员会 . 中华人民共和国药典：一部 [M ] . 2025年版 . 北京：中国医药科技出版社， 2025 ： 229 - 230 .

张香玉，才子航，高洁，等 . 知母化学成分和药理作用研究进展 [J ] . 上海中医药大学学报， 2024 ， 38 （ 5 ）： 83 - 93 ．

笔雪艳 . 知母性味的物质基础研究 [D ] . 哈尔滨：黑龙江中医药大学， 2018 ．

代涛，李光燕，徐茂红 . 知母炮制方法的历史沿革与现代研究 [J ] . 中成药， 2020 ， 42 （ 12 ）： 3255 - 3258 ．

国家药典委员会 . 中华人民共和国药典：一部 [M ] . 2020年版 . 北京：中国医药科技出版社， 2020 ： 222 .

国家药典委员会 . 中华人民共和国药典：三部 [M ] . 2025年版 . 北京：中国医药科技出版社， 2025 ： 775 - 781 .

马天成，孙宇，刘雷，等 . 响应曲面法优化知母总黄酮提取工艺及其抗氧化活性研究 [J ] . 齐齐哈尔医学院学报， 2018 ， 39 （ 6 ）： 621 - 625 ．

张正，王洪东，喻璐哲，等 . 基于化学计量学与灰色关联度：逼近理想解排序法模型的知母药材质量评价方法 [J ] . 安徽中医药大学学报， 2024 ， 43 （ 5 ）： 91 - 98 ．

魏晴，冷宗瑶，杨思慧，等 . 基于熵权法结合响应面法和反向传播人工神经网络优化姜炙厚朴的炮制工艺 [J ] . 中国医院药学杂志， 2023 ， 43 （ 13 ）： 1419 - 1424 ．

郭媛，罗严，曾良才 . GA-BP神经网络在液压缸故障诊断仿真中的应用 [J ] . 机械设计与制造， 2022 （ 11 ）： 48 - 52，57 ．

陈香茗，李倩，任海硕，等 . 基于多指标权重分析及正交试验优选知母炮制工艺 [J ] . 时珍国医国药， 2023 ， 34 （ 10 ）： 2404 - 2407 ．

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Optimization of the pressurized processing technology of Strychnos nux-vomica boiled with mung beans based on genetic algorithm

Optimization of natural deep eutectic solvent extraction of phenylethanoid glycosides from Cistanche deserticola by response surface methodology coupled with genetic algorithm

Related Author

ZHANG Hongwei

ZHANG Zhenling

ZHAO Yongqi

WANG Yiming

ZHANG Hongwei

DONG Jiani

ZHAO Longshan

BO Yukun

Related Institution

School of Pharmacy， Henan University of Chinese Medicine

Henan Engineering Research Center of Traditional Chinese Medicine Special Processing Technology

Henan Provincial Research Center for Integrated Engineering Technology of Traditional Chinese Medicine Production

Key Laboratory for Quality Control of Traditional Chinese Medicine and Decoction Pieces， State Drug Administration

Henan Institute for Drug and Medical Device Inspection

Address：8th Floor, Sihuan Building, No. 129 Daping Main Street, Yuzhong District, Chongqing, China Postal code：400042
Technical support is provided by Beijing Founder Electronics co., LTD 渝ICP备15012710号公网安备50010302001817
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.

⁰

Optimization of salt-processing technology for Anemarrhena asphodeloides by Box-Behnken response surface methodology versus GA-BP neural network

DOI：10.6039/j.issn.1001-0408.2025.19.07

摘要

Abstract

关键词

Keywords

references