Chemometrical exploration of the wet precipitation chemistry from the Austrian monitoring network (1988-1999).

Ivana Stanimirova, Michal Daszykowski, Desire Massart, Frederik Questier, Vasil Simeonov, H. Puxbaum

Research output: Contribution to journalArticle

12 Citations (Scopus)

Abstract

The use of the classification and regression tree (CART) methodology was studied in a quantitative structure-retention relationship (QSRR) context on a data set consisting of the retentions of 83 structurally diverse drugs on a Unisphere PBD column, using isocratic elutions at pH 11.7. The response (dependent variable) in the tree models consisted of the predicted retention factor (log k(w)) of the solutes, while a set of 266 molecular descriptors was used as explanatory variables in the tree building. Molecular descriptors related to the hydrophobicity (log P and Hy) and the size (TPC) of the molecules were selected out of these 266 descriptors in order to describe and predict retention. Besides the above mentioned, CART was also able to select hydrogen-bonding and molecular complexity descriptors. Since these variables are expected from QSRR knowledge, it demonstrates the potential of CART as a methodology to understand retention in chromatographic systems. The potential of CART to predict retention and thus occasionally to select an appropriate system for a given mixture was also evaluated. Reasonably good prediction, i.e. only 9% serious misclassification, was observed. Moreover, some of the misclassifications probably are inherent to the data set applied.
Original languageEnglish
Pages (from-to)349-363
Number of pages15
JournalJournal of Environmental Management
Volume74
Issue number4
Publication statusPublished - 2005

Bibliographical note

J. Environm. Management, 74, 349-363

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