Characterizing odorous emissions using new software for identifying peaks in chemometric models of gas chromatography-mass spectrometry datasets

The task of identifying individual compounds within complex gas chromatography - mass spectrometry (GC-MS) chromatograms is made more difficult by interferences between peaks with similar mass spectra eluting at the same time, typically against a background of chemical and electronic noise. Although chemometric techniques like parallel factor analysis and multivariate curve resolution can help to purify spectra and improve correlations with reference compounds, file incompatibilities between GC-MS acquisition software and modeling software prevent the modeled spectra from being easily compared to spectra in reference libraries. In this paper we present an enhancement to OpenChrom, an open-source software for chromatography and mass spectrometry, which implements the automated cross-matching of modeled spectra to NIST08 and NIST11 mass spectral databases. The benefits of this approach are demonstrated using a complex environmental dataset consisting of non-methane volatile organic compound emissions sampled on an Australian poultry farm.