Computational Methods for Gas Chromatography and Capillary Electrophoresis for Analysis of CAFO Waste

The chemical analysis of biological samples such as concentrated animal feeding operations (CAFO) waste and human breath is becoming more common as it helps create more advanced agricultural or medical processes. However, the analysis of biological samples is often noisy and hard to interpret. Several chemical analytical methods, their applications, and their associated data interpretation methods are developed in this thesis. The use of capillary electrophoresis as a method for the analysis of CAFO waste is considered via inexpensive system made from readily available components and a modified open-source contactless capacitively coupled conductivity detector design. Furthermore, the methods by which gas chromatography-mass spectrometry data is used to identify compounds is analyzed by comparing identification via mass spectrometry alone with identification in tandem with retention index matching. These methods are examined for use with the analysis of breath. Lastly, a method for the offline optimization of gas chromatography separations is presented.