Characterisation of mineral waters by pattern recognition methods

Abstract

Eighty‐three samples of mineral water from four different wells in the same district were analysed for 23 parameters. Nineteen parameters were chosen for multivariate analysis. Principal components analysis provided a feature reduction to two or three dimensions without substantial loss of information. The data set is well separated into four clusters using hierarchical and non‐hierarchical methods; samples from different wells are generally assigned to different clusters. © 1998 SCI.

Impairment of ascorbic acid’s anti-oxidant properties in confined media: Inter and intramolecular reactions with air and vanadate at acidic pH

“…Since monoanionic ascorbate is more reactive towards oxygen, changes in pH in the microemulsions [72][73][74][75][76] could explain the changes in oxidation rates. We and others have used several techniques to measure the proton activity or the effective ''pH" in this environment.…”

Preliminary Investigation on the Characterization of Durum Wheat Flours Coming from Some Areas of South Italy by Means of 1H High-Resolution Magic Angle Spinning Nuclear Magnetic Resonance

“…An example of the application of this type of statistical analysis can be found for olive oil (Dunlop et al, 1995), wine (Armanino et al, 1990), and mineral waters (Caselli et al, 1998).…”

Methodology of a combined approach: analytical techniques to identify the technology and raw materials used in thin-walled pottery from Herculaneum and Pompeii

“…The compositional data (Table 3) were processed with PCA, with the main aim of identifying groups of objects distinguishable on the basis of their compositional features. [53][54][55][56][57] It is interesting to underline that S was present in a nonnegligible amount in almost all ceramic bodies and the quantities of Mn were very different for the samples of the two groups lower than the LOD for almost all samples in group B and about 800 ppm for the samples in group A. Thus, even though Mn can be a strongly discriminating parameter for the sample investigated, it was not possible to include it in the statistical treatment.…”