| 1. |
- Murphy, Kathleen, 1972, et al.
(författare)
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Characterizing odorous emissions using new software for identifying peaks in chemometric models of gas chromatography-mass spectrometry datasets
- 2012
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Ingår i: Chemometrics and Intelligent Laboratory Systems. - : Elsevier BV. - 0169-7439 .- 1873-3239. ; 118, s. 41-50
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Tidskriftsartikel (refereegranskat)abstract
- 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. © 2012 Elsevier B.V.
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| 2. |
- Murphy, Kathleen, 1972, et al.
(författare)
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Non-methane volatile organic compounds predict odor emitted from five tunnel ventilated broiler sheds
- 2014
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Ingår i: Chemosphere. - : Elsevier BV. - 0045-6535 .- 1879-1298. ; 95, s. 423-432
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Tidskriftsartikel (refereegranskat)abstract
- Non-methane volatile organic compounds (NMVOCs) emitted from mechanically ventilated poultry sheds in similar stages (32-36d) of broiler production were measured by thermal desorption-gas chromatography/mass spectrometry (TD-GC/MS), then identified using parallel factor analysis (PARAFAC2) and the NIST11 database. Calibration models predicting odor measured by dilution olfactometry from NMVOC concentrations via orthogonal projection to latent structures (O-PLS) made good predictions (Rp2=0.83-0.87, RMSEp=137-175OU) using one to eight NMVOCs with either one or two latent variables representing odor concentration and character, respectively. Similar changes in odorant composition were observed in each sampling campaign, with samples collected early in the day more odorous and more sulfurous than samples collected later in the day. High litter moisture favored sulfur-containing odorants over alcohols, aldehydes and ketones but had little bearing on perceived odor, whereas high bird density favored alcohols, aldehydes and ketones over sulfur-containing odorants. Eight VOCs that were important predictors of odor across all sheds in order of decreasing importance were dimethyl sulfide (DMS), dimethyl trisulfide (DMTS), 2-3 butanedione, 3-methyl-butanal, 1-butanol, 3-methyl-1-butanol, acetoin, and 2-butanone. Four additional NMVOCs also influenced perceived odor although less predictably; these were n-hexane, 2-butanol, dimethyl disulfide (DMDS), and 1-octen-3-ol. All of the odorants are associated with microbial or fungal activity in the litter and manure, except n-hexane, which may originate from hexane-extracted soybean meal in the chicken feed. The organosulfides measured in this study may have arisen from the field sites as well as from the degradation of thiols captured on sorbent tubes during analysis by TD-GC/MS. © 2013 Elsevier Ltd.
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