Automated methods for the location of the boundaries of chromatographic peaks

Several simple techniques are presented for the identification of the boundaries of chromatographic peaks. These methods provide a significant reduction in the time needed to perform the rapid, automatic calculation of the central peak moments and to evaluate the quality of a separation while improving the accuracy of the measurements of column efficiencies. It was found that the identification of the peak boundaries as functions of the peak widths and the examination of the slope of the signal to noise versus time plot are viable alternatives to a manual determination.

Investigation of selected baseline removal techniques as candidates for automated implementation

Observed spectra normally contain spurious features along with those of interest and it is common practice to employ one of several available algorithms to remove the unwanted components. Low frequency spurious components are often referred to as 'baseline', 'background', and/or 'background noise'. Here we examine a cross-section of non-instrumental methods designed to remove background features from spectra; the particular methods considered here represent approaches with different theoretical underpinnings. We compare and evaluate their relative performance based on synthetic data sets designed to exemplify vibrational spectroscopic signals in realistic contexts and thereby assess their suitability for computer automation. Each method is presented in a modular format with a concise review of the underlying theory, along with a comparison and discussion of their strengths, weaknesses, and amenability to automation, in order to facilitate the selection of methods best suited to particular applications.