Application of principal component and hierarchical cluster analyses in the classification of Serbian bottled waters and a comparison with waters from some European countries

Abstract

The contents of major ions in bottled waters were analyzed by principal component (PCA) and hierarchical cluster (HCA) analysis in order to investigate if these techniques could provide the information necessary for classifications of the water brands marketed in Serbia. Data on the contents of Ca 2+ , Mg 2+ , Na + , K + , Cl-, SO 4 2-, HCO 3 and total dissolved solids (TDS) of 33 bottled waters was used as the input data set. The waters were separated into three main clusters according to their levels of TDS, Na + and HCO 3-; sub-clustering revealed a group of soft waters with the lowest total hardness. Based on the determined chemical parameters, the Serbian waters were further compared with available literature data on bottled waters from some other European countries. To the best of our knowledge, this is the first report applying chemometric classification of bottled waters from different European countries, thereby representing a unique attempt in contrast to previous studies reporting the results primarily on a country-to-country scale. The diverse character of Serbian bottled waters was demonstrated as well as the usefulness of PCA and HCA in the fast classification of the water brands based on their main chemical parameters.

Evaluation of Water and Sediment Quality of İnaltı Cave (Northern Turkey) by Using Multivariate Statistical Methods

“…Pearson's correlation index (PCI) was used in analyzing the relationships between sediment data and species found in the sediment (Alberto et al, 2001). Multivariate Hierarchical Cluster Analysis (HCA) was used in investigating the spatial differences and similarities in the cave (Cvejanov & Škrbić, 2017). Principal…”

Eco-friendly and efficient monitoring of physico-chemical parameters of some mineral water from Slanic Moldova (Romania) during storage in different conditions – a case study

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Evaluating Spatial and Temporal Variation in Tuzaklı Pond Water Using Multivariate Statistical Analysis

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