Chemometrics in analytical chemistry
Keywords:analytical chemistry, chemometrics, principal component analysis, classification, characterization
AbstractChemometrics is a scientific discipline closely connected with statistics and mathematics. It has an important role in analytical chemistry. Modern analytical methods provide opportunity to collect large amounts of data for various samples. For handling analytical results different chemometric methods are employed, such as basic statistical methods for the determination of mean and median values, standard deviations, minimal and maximal values of measured parameters and their mutual correlation coefficients, the principal component analysis (PCA), cluster analysis (CA), and linear discriminant analysis (LDA). The objectives of chemometrics in analytical chemistry are focused on characterization and chemometrical classification of different samples. The quality of environmental samples such as water, sediment, soil, air samples etc. can be determined according to measured physical and chemical parameters, which represent the individual samples. Chemometric methods give information regarding measured parameters about similarity between sampling locations, sources of pollution, seasonal behavior and time trends. Monitoring of general pollution of environmental samples and following measuring parameters which are above permitted level given by legislation can be used for searching of pollution source and for planning prevention measures from pollution. Food samples can also be characterized by chemometrical methods. Chemometrics can be used for fast and efficient determination of food sample categories, such as edible oils, wines, fruits and fruit juices etc. Classification can also be performed according to the origin, source or season. From all these facts it is evident that the aim of chemometrics in analytical chemistry is high and extensive.
How to Cite
Brodnjak Vončina , D. (2021). Chemometrics in analytical chemistry. Nova Biotechnologica Et Chimica, 9(2), 211-216. https://doi.org/10.36547/nbc.1280
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