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基于遗传算法优化绿豆煮马钱子的加压炮制工艺
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| 篇名： | 基于遗传算法优化绿豆煮马钱子的加压炮制工艺 |
| TITLE： | Optimization of the pressurized processing technology of Strychnos nux-vomica boiled with mung beans based on genetic algorithm |
| 摘要： | 目的 优选绿豆煮马钱子的加压炮制工艺。方法采用最小二乘法建立炮制时间、炮制压力、绿豆用量和加水量4个因素对士的宁、马钱子碱含量的一元模型函数，通过对一元模型函数进行分析提出多元模型假设；基于正交实验，利用遗传算法对模型中的未定系数进行求解，构建基于士的宁、马钱子碱含量的双目标优化模型，求解模型函数得到最佳工艺，并对其进行验证。结果最佳炮制工艺为：马钱子与绿豆在2.393MPa饱和蒸汽压力下煮5.5h，捞出；冲洗除去绿豆，并刮去马钱子皮毛，切顶刀片0.6mm厚；每500g马钱子用绿豆180g、水15L。结论优化后的加压炮制工艺稳定、可行，可为绿豆煮马钱子炮制工艺优化提供参考。 |
| ABSTRACT： | OBJECTIVE To optimize the pressurized processing technology of Strychnos nux-vomica boiled with mung beans. METHODS The least squares method was used to establish a one-dimensional model for the effects of four factors， namely， processing time， processing pressure， mung bean dosage and water added， on the contents of strychnine and toxiferine， and the multivariate model hypothesis was proposed by analyzing the function of one-dimensional model. Based on the orthogonal experiment， the genetic algorithm was used to solve the undetermined coefficients in the model. A bi-objective optimization model based on strychnine and toxiferine content was constructed according to the actual conditions， and the optimal technology was obtained by solving the model function and validated. RESULTS The optimal processing technology was boiling S. nux-vomica with mung beans at 2.393 MPa saturated steam pressure for 5.5 h， and then draining； rinsing to remove mung beans， scraping off the bark of S. nux-vomica and cutting into slice of 0.6 mm； using 180 g of mung beans and 15 L of water per 500 g of S. nux- vomica. CONCLUSIONS The optimized pressurized processing technology is stable and feasible， and can provide a reference for the optimization of processing technology of S. nux-vomica boiled with mung beans. |
| 期刊： | 2023年第34卷第19期 |
| 作者： | 王一鸣；张宏伟；张红伟；张振凌；赵永琪 |
| AUTHORS： | WANG Yiming，ZHANG Hongwei，ZHANG Hongwei，ZHANG Zhenling，ZHAO Yongqi |
| 关键字： | 绿豆煮马钱子饮片；炮制工艺；最小二乘法；遗传算法 |
| KEYWORDS： | Strychnos nux-vomica boiled with mung beans； processing technology； least squares method； genetic algorithm |
| 阅读数： | 37 次 |
| 本月下载数： | 5 次 |
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