Chemometric tools

relationships between measured process parameters and desired product attributes are not directly measurable, but must rather be inferred from measurements that are made. This is the case with several spectroscopic measurements including that of octane number or polymer viscosity by NIR. When this is the case, these latent properties can be related to the spectroscopic measurement by using chemometric tools such as PLS and PCA. The property of interest can be inferred through a defined mathematical relation.39 Latent variables allow a multidimensional data set to be reduced to a data set of fewer variables which describe the majority of the variance related to the property of interest. This data compression using the most relevant data also removes the irrelevant or noisy data from the model used to measure properties. Latent variables are used to extract features from data, and can result in better accuracy of measurement and a reduced measurement time.4 

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The aim of this work is the optimization of distillation process using H SO for fluoride separation and potentiometric determination in anhydrite samples by means of chemometric tools. 

Baroni M, Costantino G, Cruciani G, Riganelli D, Valigi R, Clementi S. Generating optimal linear PLS estimations (GOLPE) an advanced chemometric tool for handling 3D-QSAR problems. Quant Struct-Act Relat 1993 12 9-20. 

A homogeneity index or significance coefficienf has been proposed to describe area or spatial homogeneity characteristics of solids based on data evaluation using chemometrical tools, such as analysis of variance, regression models, statistics of stochastic processes (time series analysis) and multivariate data analysis (Singer and... 

A number of chemometric tools have been employed for these classifications, including partial least squares - hierarchical cluster analysis (PLS-HCA) for Viagra tablets [98] and antimalarial artesunate tablets [99]. de Peinder et al. used partial least squares discriminant analysis (PLS-DA) models to distinguish genuine from counterfeit Lipitor tablets even when the real API was present [100]. The counterfeit samples also were found to have poorer API distribution than the genuine ones based on spectra collected in a cross pattern on the tablet. 

Second, the emphasis on empirical modeling leads to chemometrics being a highly interfacial discipline, in that specific tools are often developed with specihc applications already in mind. For example, specific chemometric tools have been developed to align retention time axes in chromatograms [20] and to preprocess diffuse reflectance data [21]. In contrast, other disciplines, such as statistics, are associated with well-defined stand-alone tools (ANOVA, f-test, etc.) that can be applied to a wide array of different applications. One consequence of this interfacial property of chemometrics is that one must often sift through a very large toolbox of application-specific tools in order to find one that suits a particular application. 

Chemometrics tools can be used for a wide variety of tasks, including experimental design, exploratory data analysis, and the development of predictive models. In the context of analytical chemistry, however, chemometrics has been shown to be most effective for two general functions ... 

Information extraction Chemometrics tools are used to unlock hidden information already present in information-rich multivariate analytical instruments... 

In addition, specific letters are nsed to denote specific qnantities that are common for the chemometrics tools discnssed in this chapter ... 

With the foundations of chemometrics as a background, this section provides some detailed discussion of several specific chemometric tools. A truly complete discussion of all chemometric methods would require at least a book s worth of material. As a result, this discussion will focus on the tools that have been found... 

It was mentioned earlier that PCA is a useful method for compressing the information contained in a large number of x variables into a smaller number of orthogonal principal components that explain most of the variance in the x data. This particular compression method was considered to be one of the foundations of chemometrics, because many commonly used chemometric tools are also focused on explaining variance and dealing with colinearity. However, there are other compression methods that operate quite differently than PCA, and these can be useful as both compression methods and preprocessing methods. 

The highly empirical nature of chemometric tools can lead to customer suspicion regarding the efficacy of chemometric models and... 

Regardless of your problem, and the specific chemometric tools that you choose to implement, there are three guiding principles that should always be kept in mind. 

The first results from the use of PLS were reported by Dunn fit al (6) who estimated the composition of PCB contaminated waste oil in terms of Aroclor mixtures. Stalling gt al (13), who reported on the characterization of PCB mixtures and the use of three-dimensional plots derived from principal components, demonstrated that the fractional composition of TCDD and other PCDD residues were related to their geographical origins. These two reports (6,13) described the application of an advanced chemometric tool in residue studies and illustrated the... 

There are numerous reviews of chemometric tools, from the basic overview [ 159] to comprehensive literature reviews [160]. 

Baroni, M., Constantino, G., Cruciani, G., Riganelli, D., Valigli, R. and Clementi, S. (1993) Generating optimal linear pis estimations (GOLPE) An advanced chemometric tool for handling 3D-QSAR problems. Quantitative Stmcture-Activity Relationships, 12, 9-20. 

Although the chemometric tools discussed in this book into both of these categories, most of the emphasis is on implicit modeling. Valid explicit models are notnmunon in practice and, therefore, implicit models are often necessary to anfee the data and/or construct predictive models. 

Not rarely, analytical signals are composed of hundreds or thousands of variables. Many of them are uniquely or predominantly associated with noise, while contiguous informative variables are often very intercorre-lated, so that they carry redundant information. For these reasons, chemometric tools to perform the selection of a limited number of informative predictors and to realize data compression are enormously profitable. 

In each case, chemometrics plays an essential role in data processing, which corresponds to the brain elaboration of exteroceptive stimuli in mammalian sensory processes. A clever employment of chemometric tools is thus essential for obtaining reliable and valuable results. 

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. 

The aim of this chapter is, therefore, to introduce briefly the most common quantitative atomic techniques based on both optical and mass spectrometric detection. The main emphasis will be given to conceptual explanations in order to stress the advantages and disadvantages of each technique, the increase in the complexity of the data they generate and how this can be addressed. References to chemometric tools presented in the following chapters will be given. 

Cuny, M., Vigneau, E., Le Gall, G., Colquhoun, I., Lees, M., and Rutledge, D. N. (2008). Fruit juice authentication by FI NMR spectroscopy in combination with different chemometrics tools. Anal. Bioanal. Chem. 390,419-427. 

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