The authors present an example of the application of cluster analysis in commodity science. The aim of the analysis was to find, on the ground of chemical composition, groups of mineral and spring waters in which the objects of the same group exhibited the highest possible degree of similarity, while objects of different groups exhibited the lowest. Euclidean distance method was used to calculate the distance between the objects. The agglomerations were created by using the nearest neighbour algorithm.
Research was done to assess the occurrence of bacteria Pseudomonas aeruginosa in public utility surface water and artesian wells in the city area of Cracow (Poland). Samples were collected once in the summer and once in winter 2012 for each of the selected locations. While Pseudomonas aeruginosa was found at two public bathing beaches, it was not found in potable water. The contamination discovered was sampling time-dependent, revealing seasonal variations.
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