Application of Chemometric Methods

Heberger et al. [55] used principal component analysis (PCA) to reduce the amount of test solutes when calculating Flory-Huggins parameters x 2i- Subsequently, PCA became a popular technique in data analysis for pattern recognition and dimension reduction, as it can reveal several underlying components, and may also help to explain the vast majority of variance among the data [56,57]. PCA is particularly useful for classifying stationary phases [58,59], polarity [56], and interaction parameters [57]. Detailed descriptions of PCA are available in standard chemometric books and reviews [58,59]. Notably, the method should facilitate the solution of problems connected with the solute dependence of the x 2i parameter. 

Values of the Flory-Huggins X2i parameter expressing the magnitude of interactions between the polymer matrix and filler depend heavily on the type of test solute being used in IGC experiments. This causes problems when analyzing the influence of the type and amount of filler on the magnitude of these interactions however, such an analysis is clearly possible by using PCA. 

The collection of retention data for all test solutes is time-consuming, and it would be very useful to select only those test solutes that carried statistically valid information, to apply these species to IGC experiments, and then to use the retention data in calculations of X23 vvith the Zhao-Choi procedure. Today, PCA has 

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Kurt Varmuza was bom in 1942 in Vienna, Austria. He studied chemistry at the Vienna University of Technology, Austria, where he wrote his doctoral thesis on mass spectrometry and his habilitation, which was devoted to the field of chemometrics. His research activities include applications of chemometric methods for spectra-structure relationships in mass spectrometry and infrared spectroscopy, for structure-property relationships, and in computer chemistry, archaeometry (especially with the Tyrolean Iceman), chemical engineering, botany, and cosmo chemistry (mission to a comet). Since 1992, he has been working as a professor at the Vienna University of Technology, currently at the Institute of Chemical Engineering. 

Some of the most useful applications of chemometric methods involve the extraction of hidden information in large, complex databases. At first glance, such applications might not seem to be relevant for PAT, until one considers the following ... 

Because data analysis is of central interest, particularly in the application of chemometric methods in the field of environmental research, a rough list of important multivariate statistical methods is given below (Tab. 1-1). 

The characteristic peculiarities of environmental analysis discussed at the end of Section 1.4 lead to the following problems which urgently require the application of chemometric methods. 

A third and often neglected reason for the need for care fill application of chemometric methods is the problem of the type of distribution of environmental data. Most basic and advanced statistical methods are based on the assumption of normally distributed data. But in the case of environmental data, this assumption is often not valid. Figs. 1-7 and 1-8 demonstrate two different types of experimentally found empirical data distribution. Particularly for trace amounts in the environment, a log-normal distribution, as demonstrated for the frequency distribution of N02 in ambient air (Fig. 1-7), is typical. 

In summary, the application of chemometric methods may be very useftd for the solution of the following environmental problems ... 

Section 1.8 gives an overview of monographs which deal with basic and advanced statistics, and some hints are given about recommended books and journals. Important books on general aspects of chemometrics include SHARAF et al. [1986], MASSART et al. [1988], and BRERETON [1990]. Books which deal with the application of chemometric methods in environmental research are BREEN and ROBINSON [1985], DEVILLERS and KARCHER [1991], and EINAX [1995a 1995b],... 

In the majority of studies pollution load data result from many, often unknown entry paths of noxious substances and from interactions among one another and the environmental compartments. In brief, the scope of application of chemometric methods is to extract the latent information from environmental data. In this section the power of multivariate data analysis shall be demonstrated for specific and typical examples of environmental investigation. 

The main aim of this part of the book is to demonstrate the advantages of using multivariate statistical computations. The application of chemometric methods to the results of routine environmental monitoring and their relevant interpretation facilitates asserta-tions concerning the identification of effective factors in the environment and the objective assessment of pollutant loading. These factors and loading states are either not accessible or are of only very restricted accessibility in current environmental monitoring. 

The following case studies cannot and shall not give an overview of all possible applications of chemometric methods, but they may stimulate the reader into using chemo-metrics to solve environmental tasks and problems in his own working field. 

This second example demonstrates the possibility of investigating long range transport of particulate emissions by application of chemometric methods [EINAX et al., 1994]. 

The optimization of an analytical procedure used to solve a particular problem is an essential task for each analyst. The application of chemometric methods to this task is very useful and the principles and many applications have been described in the literature (see, for example, [SHARAF et al., 1986 MASSART et al., 1988]). In this section optimization of an analytical procedure is demonstrated for a particular case study in the field of routine environmental analysis [EINAX et ah, 1989]. 

APPLICATION OF CHEMOMETRIC METHODS IN DRUG PURITY DETERMINATION BY CAPILLARY ELECTROPHORESIS... 

Applications of chemometric methods in drug purity determination 97... 

The discipline of chemometrics originates in chemistry. Typical applications of chemometric methods are the development of quantitative structure activity relationships and the evaluation of analytical-chemical data. The data flood generated by modern analytical instrumentation is one reason that analytical chemists in particular develop applications of chemometric methods. Chemometric methods in analytics is the discipline that uses mathematical and statistical methods to obtain relevant information on material systems. 

Quantitative application of Raman spectroscopy generally requires pretreatment to reduce background variance and often also includes the application of chemometric methods. The success of both steps depends on a high level of both abscissa and ordinate stability and linearity. Scattering intensity and the relative intensities of Raman lines within a spectrum depend on a variety of measurement conditions laser power, laser wavelength, spectral resolution, detector properties, and arrangement of the excitation and collection optics. 

Multivariate calibration has the largest number of applications of chemometric methods in routine analysis for instance it became a widely used technique in quantitative analy.sis of complex mixtures by IR or UV detectors, especially in food chemistry and environmental analytical chemistry. A number of textbooks, tutorials, and reviews " have been published in this field, and software is offered by the instrument manufacturers. Applications of multivariate calibration is very widespread, ranging for instance from the determination of moisture in mushrooms to research for non-invasive measurement techniques of glucose in human blood. The multivariate methods mostly applied are PLS, PCR. and recently also neural networks, Typical calibration models describe the relationship between a set of x-variables (UV or IR absorbances) and one y-variable (concentration of one substance) although it is possible to derive models that simultaneously predict a set of y-variables. 

The second part of the book—Chapters 9-12— presents some selected applications of chemometrics to different topics of interest in the field of food authentication and control. Chapter 9 deals with the application of chemometric methods to the analysis of hyperspectral images, that is, of those images where a complete spectrum is recorded at each of the pixels. After a description of the peculiar characteristics of images as data, a detailed discussion on the use of exploratory data analytical tools, calibration and classification methods is presented. The aim of Chapter 10 is to present an overview of the role of chemometrics in food traceability, starting from the characterisation of soils up to the classification and authentication of the final product. The discussion is accompanied by examples taken from the different ambits where chemometrics can be used for tracing and authenticating foodstuffs. Chapter 11 introduces NMR-based metabolomics as a potentially useful tool for food quality control. After a description of the bases of the metabolomics approach, examples of its application for authentication, identification of adulterations, control of the safety of use, and processing are presented and discussed. Finally, Chapter 12 introduces the concept of interval methods in chemometrics, both for data pretreatment and data analysis. The topics... 

Abbas, O., Rebufa, C Dupuy, N., Pennanyer, A., Kister, J., and Azevedo, D.A. (2006). Application of chemometric methods to synchronous UV fluorescence spectra of petroleum oils. Fuel, 85, 2653-2661. 

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