近红外光谱和聚类分析法无损快速鉴别小儿抽风散

doi:10.3964/j.issn.1000-0593.2008.02.023

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摘要：以小儿抽风散不同缺味复方的近红外图谱作为聚类分析的对象，在建立混合成分模型的基础上，采用SIMCA聚类分析法对小儿抽风散不同缺味复方进行了快速的分类研究。实验中，在保证其他配伍组分完整的基础上，分别设缺少蜈蚣、全蝎、僵蚕、土鳖虫和蝉蜕的5个阴性样品。结果表明：尽管各样品的近红外谱图很相似，难以直接区别，但采用近红外光谱和聚类分析相结合的方法可以鉴定小儿抽风散的不同缺味复方。各样品之间光谱聚类的结果较理想，盲样检测的正确率可达90％以上。此外，如果能够获得足够多的样本，增加训练集样本数和采样的代表性，加强操作的标准程度，该法的准确率将会大大提高。因此，近红外光谱与聚类分析法相结合可以快速、无损识别中药复方。

关键词：红外光谱;小儿抽风散;聚类分析法;无损鉴别

Abstract：On the basis of building a model of main components and with the fingerprint infrared spectrum as the object- Xiaoerchoufeng powders were rapidly classified and closely studied by using the method of clustering analysis. Because of the tiny difference between the spectra of different compound recipes, including the compound recipe without scolopendra, the compound recipe without scorpio, the compound recipe without bombyx batryticatus, the compound recipe without eupolyphaga seu steleophaga and the compound recipe without periostracum cryptotympanae, the outcome of the clustering is ideal. When tested with the blind samples (which were picked out from the chosen samples) the accuracy of clustering reaches up to 90%. In order to increase the clustering accuracy, the number of the samples should be increased and also these samples should be more characteristic. On the whole, with the combination of the fingerprint spectrum and the clustering analysis, the compound recipe can be distinguished rapidly.

Key words：FTIR spectroscopy;Xiaoerchoufeng Powder;Clustering analysis;Undamaged determination

收稿日期: 2007-02-08 修订日期: 2007-05-12

中图分类号:

R282.5

通讯作者: 张贵君,孙素琴 E-mail: guijunzhang@163.com

引用本文:

王晶娟¹,张贵君^1*,周群²,孙素琴^2*. 近红外光谱和聚类分析法无损快速鉴别小儿抽风散[J]. 光谱学与光谱分析, 2008, 28(02): 327-330.
WANG Jing-juan¹,ZHANG Gui-jun^1*,ZHOU Qun²,SUN Su-qin^2*. FTIR and Classification Study on the Chinese Compound Recipe. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2008, 28(02): 327-330.

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