DOI
https://doi.org/10.25772/9AT8-XE67
Defense Date
2012
Document Type
Dissertation
Degree Name
Doctor of Philosophy
Department
Chemistry
First Advisor
Sarah C. Rutan
Abstract
This research project sought to explore, compare and develop chemometric methods with the goal of resolving chromatographically overlapped peaks though the use of spectral information gained from the four-way data sets associated with comprehensive two-dimensional liquid chromatography with diode array detection (LC ´ LC-DAD). A chemometric method combining iterative key set factor analysis (IKSFA) and multivariate curve resolution-alternating least squares (MCR-ALS) was developed. In the section of urine data analyzed, over 50 peaks were found, with 18 visually observable and 32 additional compounds found only after application of the chemometric method. Upon successful chemometric resolution of chromatographically overlapped peaks, accurate and precise quantification was then necessary. Of the compared methods for quantification, the manual baseline method was determined to offer the best precisions. Of the 50 found peaks from the urine analysis, 34 were successfully quantified using the manual baseline method with percent relative standard deviations ranging from 0.09 to 16. The accuracy of quantification was then investigated by the analysis of wastewater treatment plant effluent (WWTPE) samples. The chemometrically determined concentration of the unknown phenytoin sample was found to not exhibit a significant difference from the result obtained by the LC-MS/MS reference method, and the precision of the IKSFA-ALS method was better than that of the precision of the LC-MS/MS analysis. Chromatographic factors (data complexity, large dynamic range, retention time shifting, chromatographic and spectral peak overlap and background removal, were all found to affect the quantification results. The last part of this work focused on rapid screening methods that were capable of locating peaks between samples that exhibited significant differences in concentration. The aim here was to reduce the amount of data required to be resolved and quantified to only those peaks that were of interest. This would then reduce the time required to analyze large, complex samples by eliminating the need to first quantify all peaks in a given sample for many different samples. Both the similarity index (SI) method and the Fisher ratio (FR) method were found to fulfill this requirement in a rapid means of screening fifteen wine samples.
Rights
© The Author
Is Part Of
VCU University Archives
Is Part Of
VCU Theses and Dissertations
Date of Submission
December 2012