摘要
目的:采用显微近红外光谱技术结合判别分析法,建立天然牛黄与人工牛黄快速无损的鉴别方法。方法:利用主成分分析法观察天然牛黄和人工牛黄主成分的空间分布,并采用判别分析法建立定性鉴别模型,考察不同数据预处理方法下模型预测结果。结果:天然牛黄和人工牛黄原始光谱的主成分空间分布明显不同,天然牛黄和人工牛黄可以单独地聚为一类;在不同的光谱预处理方式下,模型预测的正确率均为100%。结论:判别分析法所建模型预测性能好,可以用于未知牛黄品种的预测分类;利用显微近红外光谱技术可以有效提取牛黄药材中的多种信息,能够达到快速、无损、整体分析鉴别人工牛黄和天然牛黄的目的。
Objective: A rapid and straightforward analytical tool for the identification of bezoar and artificial bezoar powder using Near Infrared microspectroscopy was presented. Methods: Two qualitative methods were selected to establish identification model. The Principal Component Analysis was used to observe the spatial distribution of bezoar and artificial bezoar. The Discriminant Analysis was used to determine the classes of bezoar and artificial bezoar by computing their distance from each class center in Mahalanobis distance units. Different data pre-processing methods were explored before modeling with the discrimination rate as indicator. Results: The results showed that there was a great difference in principal component spatial distribution. The predictions obtained were quite accurate. Conclusion: Near infrared microspectroscopy could act as an effective method of distinguishing bezoar from artificial bezoar.
出处
《中华中医药杂志》
CAS
CSCD
北大核心
2014年第1期84-87,共4页
China Journal of Traditional Chinese Medicine and Pharmacy
基金
国家科技重大专项(No.2011ZX11201-201-24)~~
关键词
天然牛黄
人工牛黄
显微近红外光谱
主成分分析
判别分析
Bezoar
Artificial bezoar
Near infrared microspectroscopy
Principal component analysis
Discriminant analysis