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Journal
2013 | 11 | 4 | 610-618
Article title

Selection of mineralised methods to analyse different types of matrices. Applying the Box-Cox transformation to chemometrics study the coexistence of heavy metals in natural samples

Content
Title variants
Languages of publication
EN
Abstracts
EN
Chemometric methods are mostly used to optimise technological processes and analytical procedures. Applying chemometric methods in environmental tests may reveal relationships among chemical elements in biomes. Cluster analysis and principal component analysis (PCA) are very helpful for detecting relationships among studied parameters. However, large amounts of data may have a negative effect on this analysis and can lead to misinterpretation of the results. This situation was observed when the samples, taken from several places in the Silesian Province, were used to test the relationship between heavy metals contained in various environmental matrices. Samples were collected from a small area and were characterised by a single biome (pine forest) because direct interpretation of PCA and CA was insufficient to correctly describe such data. The solution to this problem was the use of the Box-Cox transformation, which is a rapid method to normalise input data. [...] The application of chemometric tools enabled the relationships between sampling sites (industrialised and non-industrialised) to be examined and was very helpful in illustrating the relationship between the methodologies of plant preparation samples. Furthermore, the results may indicate the need for further data analysis. The tools described in this paper can be useful for choosing the optimal mineralisation method according to the type of test matrix.
Publisher

Journal
Year
Volume
11
Issue
4
Pages
610-618
Physical description
Dates
published
1 - 4 - 2013
online
23 - 1 - 2013
Contributors
author
  • Department of Analytical Chemistry, Faculty of Chemistry, Silesian University of Technology, 44-100, Gliwice, Poland
References
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Document Type
Publication order reference
Identifiers
YADDA identifier
bwmeta1.element.-psjd-doi-10_2478_s11532-012-0196-x
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