Professor Frank Vogt of the University of Tennessee Knoxville is supported by the Chemical Measurement and Imaging (CMI) Program in the Division of Chemistry to develop chemometric methods for the qualitative and quantitative analysis of complex chemical and biological samples. The specific objective is to develop "Bayesian Information Fusion," a novel chemometric concept which merges different types of information from complementary sources for sample classification. To further enhance the accuracy of the classification and the quantification, a novel "Plausibility Analysis" software will be developed and incorporated. As a proof-of-principle, these novel chemometric methodologies will be applied to FTIR spectroscopic data obtained from microalgae samples with the goal to utilize them as environmental bioprobes. The analysis of complex chemical and biological samples is extremely challenging because of the large number of analytes present and their wide range of concentrations, and chemometric data analysis is increasingly becoming an invaluable analytical chemistry tool for improved classification and quantification of such samples. The project results will be integrated in classroom material by means of the cyber-enabled and interactive software package "Virtual Chemometrics Laboratory."
