Selective Data Reduction in Gas Chromatography/Infrared Spectrometry

As gas chromatography/infrared spectrometry (GC/IR) becomes routinely avaliable, methods must be deve-loped to deal with the large amount of data produced. We demonstrate computer methods that quickly search through a large data file, locating those spectra that display a spectral feature of interest. Based on a modified library search routine, these selective data reduction methods retrieve all or nearly all of the compounds of in-terest, while rejecting the vast majority of unrelated compounds. To overcome the shifting problem of IR spec-tra, a search method of moving the average pattern was designed. In this moving pattern search, the average pattern of a particular functional group was not held stationary, but was allowed to be moved a little bit right and left