Multivariate analytical images

Multivariate analytical images may be processed additionally by chemo-metrical procedures, e.g., by exploratory data analysis, regression, classifica-tion> and principal component analysis (Geladi et al. [1992b]). 

When the peak of interest is strong and is not overlapped by other spectral features, data analyses are straightforward and individual wavelength-specific images can be constructed (18), In most cases, the sample complexity and, therefore, that of the spectrum, requires a more rigorous approach to data analyses which is facilitated by multivariate analytical techniques, e.g., cluster analysis, hierarchical analysis and the like that yield high quality detailed images which can reveal anatomical features of interest (18, 19). 

Analytical Problem Solving Selection of Analytical Methods Multivariate Image Analysis Quality Assurance in Analytical Chemistry Quantitative Spectroscopic Calibration... 

Geladi P, Grahn H, Multivariate Image Analysis, in Encyclopedia of Analytical Chemistry, Meyers R (ed.), John Wiley Sons, Ltd, Chichester, 2000, pp. 13540-13562. 

Process analyzer measurements, e.g., spectra or chemical images, typically require a mathematical transformation, e.g., multivariate data analysis, to correlate the process analytical data to a more relevant critical product attribute for design space definition. For brevity, throughout this section the measurement system that yields process analytical data is noted as a PAT method and the subsequent mathematical transformation is described as a model. To forego a debate regarding what constitutes a process analyzer, i.e., temperature sensor versus a Raman fiber optic probe, herein focuses on process analyzers that yield multivariate data. 

Botelho, B. G., L. P. de Assis, and M. M. Sena. 2014. Development and analytical validation of a simple multivariate calibration method using digital scanner images for Sunset Yellow determination in soft beverages. Food Chem. 159 175-180. 

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