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目的:探讨遗传算法用于秦皮提取液多目标混批勾兑的可行性。方法:选择指纹图谱相似度和指标性成分含量的均方根误差为共同优化目标,对10批不同来源、批次的秦皮提取液建立多目标优化模型,运用遗传算法求得勾兑系数,对各批次提取液进行混批勾兑,以相似度和均方根误差评价确定勾兑后提取液的质量。结果:各批次秦皮提取液混批勾兑后,其质量明显改善,与对照样品间的指纹图谱相似度显著提高,变异程度降低,指标性成分相对偏差小于10%。结论:遗传算法可用于秦皮提取液多目标的混批勾兑,为中药提取液的质量控制提供新思路。
Objective: To explore the feasibility of genetic algorithm for multi-objective mixed lotion of Qinpi extract. Methods: The root mean square error (RMSE) of similarity of fingerprints and the content of indicator components were selected as the common optimization target. Multi-objective optimization models were established for 10 batches of P. armeniaca extracts from different sources and batches. The genetic algorithm was used to calculate the blending coefficients. Batch extract mixed batch mixed with similarity and root mean square error assessment to determine the quality of the extracted extract. Results: The quality of lotus root bark extract was significantly improved after the batch blending. The similarity of the fingerprint of the lotus root bark extract was significantly improved and the degree of variation was decreased. The relative deviation of the index components was less than 10%. Conclusion: The genetic algorithm can be used for multi-target batch blending of Qinpi extract, providing a new idea for the quality control of Chinese herbal extract.