Impact of fat and muscle in energy dispersive X-ray diffraction-based identification of heroin using multivariate data analysis

被引:4
|
作者
Li, Wei [1 ,2 ]
Zhang, Fang [1 ,3 ,4 ]
Yu, Daoyang [1 ]
Sun, Bai [1 ]
Li, Minqiang [1 ]
Liu, Jinhuai [1 ]
机构
[1] Chinese Acad Sci, Inst Intelligent Machines, Res Ctr Biomimet Funct Mat & Sensing Devices, Hefei 230031, Peoples R China
[2] Univ Sci & Technol China, Dept Automat, Hefei 230026, Peoples R China
[3] Univ Sci & Technol China, Dept Chem, Hefei 230026, Peoples R China
[4] Wuhan Inst Technol, Sch Mat Sci & Engn, Wuhan 430073, Peoples R China
基金
中国国家自然科学基金;
关键词
heroin identification; multivariate data analysis; principal component analysis; partial least squares; energy dispersive X-ray diffraction;
D O I
10.1002/cem.1409
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
As for the detection of drug body packing, skin is a typical interference factor. In this paper, multivariate data analysis was proposed to analyze the impact of fat and muscle on heroin identification based on the profile of spectra of energy dispersive X-ray diffraction. In the space of principal components, the results showed that different pure samples (heroin, muscle, fat) clustered in different areas, whereas the location of mixture samples moved between locations of pure samples. The impact of fat and muscle lies in moving the feature points between pure materials in the space of principal components. Furthermore, the model of heroin covered by fat and muscle of different thicknesses was set up, and a linear relationship was proven to be suitable. Our findings indicate that multivariate data analysis would be a promising method in the detection of drug body packing. Copyright (C) 2011 John Wiley & Sons, Ltd.
引用
收藏
页码:631 / 635
页数:5
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