Literature DB >> 24203432

Software-based mass spectral enhancement to remove interferences from spectra of unknowns.

N R Herron1, J R Donnelly, G W Sovocool.   

Abstract

Gas chromatography-mass spectrometry data from the analysis of complex environmental samples were converted into ASCII text and imported into a personal computer spreadsheet. A macro was written to perform mass spectral enhancement by statistical and mathematical procedures to separate the spectra of compounds of interest from interfering mass spectral responses, such as those of broadly eluting hydrocarbons. The extracted mass spectra were compared to reference spectra, with the result that usually 80-90% of the ions common to those in the reference spectra were successfully extracted by using this method. This procedure improved mass spectral quality and the ability of the data system to perform successful library searches. The fitted quality parameters showed systematic improvements after the data were subjected to the spectral enhancement procedures. These procedures could help to identify unknowns by separating their spectra from other signals, such as those of background aliphatic hydrocarbons.

Entities:  

Year:  1996        PMID: 24203432     DOI: 10.1016/1044-0305(96)00018-9

Source DB:  PubMed          Journal:  J Am Soc Mass Spectrom        ISSN: 1044-0305            Impact factor:   3.109


  2 in total

1.  Spectral deconvolution for overlapping GC/MS components.

Authors:  B N Colby
Journal:  J Am Soc Mass Spectrom       Date:  1992-07       Impact factor: 3.109

2.  Ion abundance criteria for gas chromatographic/mass spectrometric environmental analysis.

Authors:  J R Donnelly; G W Sovocool; R K Mitchum
Journal:  J Assoc Off Anal Chem       Date:  1988 Mar-Apr
  2 in total
  3 in total

Review 1.  Unknown identification using reference mass spectra. Quality evaluation of databases.

Authors:  F W McLafferty; D A Stauffer; S Y Loh; C Wesdemiotis
Journal:  J Am Soc Mass Spectrom       Date:  1999-12       Impact factor: 3.109

Review 2.  Microbial metabolomics: replacing trial-and-error by the unbiased selection and ranking of targets.

Authors:  Mariët J van der Werf; Renger H Jellema; Thomas Hankemeier
Journal:  J Ind Microbiol Biotechnol       Date:  2005-05-14       Impact factor: 3.346

3.  Extraction of pure components from overlapped signals in gas chromatography-mass spectrometry (GC-MS).

Authors:  Vladimir A Likić
Journal:  BioData Min       Date:  2009-10-12       Impact factor: 2.522

  3 in total

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