Chemometric tools definition

Key words in the definition are optimal and material systems . These express the fact that chemical analysis is related to a problem and not to a sample and that economical aspects of chemical analysis prevail. The result of chemometric research is chemometric software, which enable a large scale implementation and application of chemometric tools in practical chemical analysis. 

In the field of electrochemical sensors for liquids, there is the recent approach known as electronic tongue, which is inspired on the sense of taste. A widely accepted definition of electronic tongue (Holmberg et al. 2004) entails an analytical instrument comprising an array of non-specific, poorly selective, chemical sensors with crosssensitivity to different compounds in a solution, and an appropriate chemometric tool for data processing. 

Despite the broad definition of chemometrics, the most important part of it is the application of multivariate data analysis to chemistry-relevant data. Chemistry deals with compounds, their properties, and their transformations into other compounds. Major tasks of chemists are the analysis of complex mixtures, the synthesis of compounds with desired properties, and the construction and operation of chemical technological plants. However, chemical/physical systems of practical interest are often very complicated and cannot be described sufficiently by theory. Actually, a typical chemometrics approach is not based on first principles—that means scientific laws and mles of nature—but is data driven. Multivariate statistical data analysis is a powerful tool for analyzing and structuring data sets that have been obtained from such systems, and for making empirical mathematical models that are for instance capable to predict the values of important properties not directly measurable (Figure 1.1). 

Some basic concepts and definitions of statistics, chemometrics, algebra, graph theory, similarity/diversity, which are fundamental tools in the development and application of molecular descriptors, are also presented in the Handbook in some detail. More attention has been paid to information content, multivariate correlation, model complexity, variable selection, and parameters for model quality estimation, as these are the characteristic components of modern QSAR/QSPR modelling. 

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