Chemometrics and Intelligent Laboratory Systems
| Autor: | Bueno, Maria Izabel Maretti Silveira, Castro, Martha Teresa Pantoja de Oliveira, Souza, Aline Moreira de, Oliveira, Erica Borges Santana de, Teixeira, Alete Paixão |
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| Jazyk: | angličtina |
| Rok vydání: | 2005 |
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| Zdroj: | Repositório Institucional da UFBA Universidade Federal da Bahia (UFBA) instacron:UFBA |
| Popis: | Texto completo: acesso restrito.P.96–102 Submitted by Edileide Reis (leyde-landy@hotmail.com) on 2013-11-13T11:49:48Z No. of bitstreams: 1 Maria Izabel Maretti Silveira.pdf: 367801 bytes, checksum: f9adca3441e89af449907007e4d1aca8 (MD5) Made available in DSpace on 2013-11-13T11:49:48Z (GMT). No. of bitstreams: 1 Maria Izabel Maretti Silveira.pdf: 367801 bytes, checksum: f9adca3441e89af449907007e4d1aca8 (MD5) Previous issue date: 2005 Mild variations in organic matrices, which are investigated in this work, are caused by alterations in X-ray Raman scattering. The multivariate approaches, principal component analysis (PCA) and hierarchical cluster analysis (HCA), are applied to visualize these effects. Conventional energy-dispersive X-ray fluorescence equipment is used, where organic compounds produce intense scattering of the X-ray source. X-ray Raman processes, before obtained only for solid samples using synchrotron radiation, are indirectly visualized here through PCA scores and HCA cluster analysis, since they alter the Compton and Rayleigh scattering. As a result, their influences can be seen in known sample characteristics, as those associated with gender and melanin in dog hairs, and the differentiation in coconut varieties. Chemometrics has shown that, despite their complexity, natural samples can be easily classified. |
| Databáze: | OpenAIRE |
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