Chemometric characterization of environmental and food samples : doctoral dissertation = Kemometrijska karakterizacija okoljskih in prehranskih vzorcev : doktorska disertacija
Šnuderl, Katja, 1977-
Gathered data were processed with the use of following chemometric methods: statistics (description and prediction of the sample or measurement properties and populations), visualisation ...(representation and projection of the complex multidimensional data into a 2-D space), partition (assortment and definition of learning-, test- and control-samples), classification (sampleforecast to a category), modelling (quantitative foretelling of the object properties), optimisation (assortment and definition of the most appropriate conditions, variables and properties at given border requirements). The Thesis reveals different fields of research: (1) research of food products, (2) research in environmental chemistry (3) research in clinical chemistry considering oncology patients undergoing different laboratory tests, and (4) contemporary use of chemometrics, statistics and informatics. Using chemometric techniques the following tasks were performed: (a) characterisation and classification of pumpkin seed oils regarding their chemical and sensorial properties, (b) multivariate analysis of wine samples concerning classification and determination of origin and vintage of different wine sorts, (c) characterisation and classification of mineral waters with regard to their physico-chemical properties, (d) assessment of the content of pollutants monitored in the collected air samples in order to find the correlations among the concentrations of the selected chemical components in air as well as selected meteorological parameters, (e) evaluation of the correlations among the concentration of morphine and its metabolites in the serum of oncology patients aimed to find their dependency on daily drug doses, sort of drug, personal characteristics and gender of patient, type of tumour and traditional biochemical parameters. Due to its systematic approach the dissertation introduces new cognition in a practical field of categorisation and classification of larger data sets in different analytical areas. Using multivariate chemometric methods the following original scientific contributions were achieved: - Determination of quality of the selected pumpkin seed oils using measured UV-Vis, NIR in FTIR spectra at different wavelengths and performed sensorial data analysis (evaluation with regard to taste, odour and colour). - Composition of classification models of wine samples and determination of their authenticity with regard to different criteria (vintage, producer, and sort of wine) connected to sensorial evaluation of wine samples (evaluation with regard to taste, colour and bouquet). - Classification, chemometric characterisation and comparison of 50 different mineral water samples (37 from Slovenia and 13 from other European countries) with regard to their physical parameters and ion contents. - Elucidation of correlations between concentrations of morphine and its metabolites in blood serum taken from oncology patients under treatment. Determination of dependency of the above mentioned concentrations upon administered drug (daily doses, sort of medicament), patients' personal characteristics and gender, tumour location and measured biochemical parameters. - Composition of mathematical models and graphical review of the correlations among the air pollutants and meteorological conditions valid at the time of sampling. In the Thesis the use of the following multivariate methods of data analysis is described: correlation analysis, analysis of variance (ANOVA), cluster analysis (CA), principal component analysis (PCA), canonical correlation analysis (CCA), linear discriminant analysis (LDA) and logistic regression (LR). These chemometric methods were performed with use of different software packages like TeachMe, Statgraphics Plus, Systat, SAS, MSExcel, and other.
Type of material - dissertation
; adult, serious
Publication and manufacture - Maribor : [K. Šnuderl], 2009
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