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建立了一种新的中药HPLC指纹图谱模式识别方法-指纹图谱相对峰面积差(ΔSr)等级序列模式识别法,可以综合利用指纹峰峰位定性信息及成分含量信息实现中药复方黑箱体系的鉴别及定量质量评价。测定了中药复方补中益气丸和十全大补丸无水乙醇提取物HPLC指纹图谱,建立ΔSr序列。根据正态分布定义不同相似度等级,ΔSr≤ΔSr+xSv,-3≤x≤+3,确定各样品的特征样品组,构成每个样品的分类信息。该法无须对照样品及经验知识,可以对这两种组成相似的中药复方进行准确精细的分类,品种识别率100%,而相关系数r和向量夹角余弦cosα相似度法无法准确识别两类样品。ΔSr等级序列聚类法是一种准确的HPLC指纹图谱分析方法,适用于中药复方复杂生物系统-一种黑箱系统的鉴别及质量评价。
A new pattern recognition method of HPLC fingerprinting of traditional Chinese medicine (HPLC) was developed based on the pattern recognition of the relative peak area difference (ΔSr) pattern of traditional Chinese medicine (TCM) fingerprints. Quantitative quality evaluation. The HPLC fingerprints of absolute ethanol extract of traditional Chinese medicine Buzhong Yiqi Pill and Shiquan Dabu Pill were determined and the ΔSr sequence was established. According to the normal distribution of different degrees of similarity defined, ΔSr≤ΔSr + xSv, -3≤x≤ + 3, determine the characteristic sample set of each sample to form the classification information of each sample. The method does not need to control samples and experience knowledge, and can accurately classify the two kinds of traditional Chinese medicine compounds with similar identification rate of 100%. However, the correlation coefficient r and vector cosine cosine similarity method can not accurately identify the two types of samples . The ΔSr level sequence clustering method is an accurate method for HPLC fingerprinting analysis, which is suitable for the identification and quality evaluation of complex biological system of traditional Chinese medicine complex - a black box system.