Yang Ming, Zhou Yinmin, Chen Jialei, Yu Minying, Shi Xiufeng, Gu Xijun
Medicament Department of Longhua Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Zhongguo Zhong Yao Za Zhi. 2009 Oct;34(20):2594-8.
To explore the feasibility of genetic algorithm (GA) on multiple objective blending technology for extractions of Cortex Fraxini.
According to that the optimization objective was the combination of fingerprint similarity and the root-mean-square error of multiple key constituents, a new multiple objective optimization model of 10 batches extractions of Cortex Fraxini was built. The blending coefficient was obtained by genetic algorithm. The quality of 10 batches extractions of Cortex Fraxini that after blending was evaluated with the finger print similarity and root-mean-square error as indexes.
The quality of 10 batches extractions of Cortex Fraxini that after blending was well improved. Comparing with the fingerprint of the control sample, the similarity was up, but the degree of variation is down. The relative deviation of the key constituents was less than 10%.
It is proved that genetic algorithm works well on multiple objective blending technology for extractions of Cortex Fraxini. This method can be a reference to control the quality of extractions of Cortex Fraxini. Genetic algorithm in blending technology for extractions of Chinese medicines is advisable.
探讨遗传算法在秦皮提取多目标融合技术中的可行性。
以指纹相似度与多个关键成分的均方根误差的组合为优化目标，建立了秦皮10批次提取物的多目标优化模型。通过遗传算法获得融合系数。以指纹相似度和均方根误差为指标，评价融合后秦皮10批次提取物的质量。
融合后秦皮10批次提取物的质量有明显提高。与对照品指纹图谱相比，相似度提高，变异程度降低。关键成分的相对偏差小于10%。
证明遗传算法在秦皮提取多目标融合技术中效果良好。该方法可为秦皮提取物质量控制提供参考。遗传算法应用于中药提取融合技术是可行的。
