ICP MS analysis and classification of potable, spring, and mineral waters

Kraic, Filip, Mocák, Ján, Fiket, Željka and Kniewald, Goran ICP MS analysis and classification of potable, spring, and mineral waters Chemical Papers, Vol.62, No. 5, 2008, 445-450

Document type: Článok z časopisu / Journal Article
Collection: Chemical papers  

Author(s) Kraic, Filip
Mocák, Ján
Fiket, Željka
Kniewald, Goran
Title ICP MS analysis and classification of potable, spring, and mineral waters
Journal name Chemical Papers
Publication date 2008
Year available 2008
Volume number 62
Issue number 5
ISSN 0366-6352
Start page 445
End page 450
Place of publication Poland
Publisher Versita
Collection year 2008
Language english
Subject 250000 Chemical Sciences
250400 Analytical Chemistry
Abstract/Summary Ninety-three water samples were categorized into five classes as the tap, mineral, mineral carbonated, spring, and spring carbonated water, or, alternatively, into four or three categories — with all spring water samples together or as tap, mineral, and spring water, respectively. The samples originated from four European countries and thirty-one chemical descriptors (concentrations of contained elements) were used for their characterization. Analytical measurements were performed by mass spectrometry with inductively coupled plasma, allowing the determination of individual nuclides. Different water categories were characterized by chemometrical techniques, mainly by principal component analysis, cluster analysis, linear and quadratic discriminant analyses, correlation analysis, and ANOVA. Their role was to discover the nuclides important for distinct characterization of individual water categories as well as to assess the possibility of water samples from different countries being recognized from the increased/decreased content of some elements. The enhanced content of Cd, Cu, Zn, Bi, and Fe was characteristic for tap water samples, whilst mineral water samples were characterized by the elevated concentration of Sr, Li, B, Ni, Co, As, and Sb. The classification results were successful and close to 100 %, which was proved by the leave-one-out cross-validation procedure.
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