Reducing Inter-replicate Variation in Fourier Transform Infrared Spectroscopy by Extended Multiplicative Signal Correction
Authors: Kohler, A.1; Böcker, U.2; Warringer, J.3; Blomberg, A.3; Omholt, S.W.4; Stark, E.5; Martens, H.6
Source: Applied Spectroscopy, Volume 63, Issue 3, Pages 68A-86A and 261-380 (March 2009) , pp. 296-305(10)
Publisher: Society for Applied Spectroscopy
- The Society publishes the internationally recognized, peer reviewed journal, Applied Spectroscopy, which is available both in print and online. Subscriptions are included with membership or can be purchased by institutional or corporate organizations. Abstracts may be viewed free of charge. Previously published as Bulletin (Society for Applied Spectroscopy)
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- In this Subject: Analytical Chemistry
- By this author: Kohler, A. ; Böcker, U. ; Warringer, J. ; Blomberg, A. ; Omholt, S.W. ; Stark, E. ; Martens, H.
Abstract:
Fourier transform infrared (FT-IR) spectroscopy is a powerful tool for characterizing biological tissues and organisms, but it is plagued by replicate variation of various sources. Here, a method for estimating and correcting unwanted replicate variation in multivariate measurement signals, based on extended multiplicative signal correction (EMSC), is presented. Systematic patterns of unwanted methodological variations are estimated from replicate spectra, modeled by a linear subspace model, and implemented into EMSC. The method is applied to FT-IR spectra of two different sets of microorganisms (different double gene knockout strains of Saccharomyces cerevisiae and different species of Listeria) and compared to other preprocessing methods used in FT-IR absorption spectroscopy of microorganisms. The EMSC replicate correction turns out to perform best among the compared methods.Keywords: EXTENDED MULTIPLICATIVE SIGNAL CORRECTION; EMSC; MODEL-BASED PREPROCESSING; FOURIER TRANSFORM INFRARED SPECTROSCOPY; FT-IR SPECTROSCOPY
Document Type: Research article
DOI: 10.1366/000370209787598906
Affiliations: 1: Nofima Mat, Centre for Biospectroscopy and Data Modelling, Osloveien 1, 1430 Ås, Norway; CIGENE - Center for Integrative Genetics, University of Life Sciences, 1432 Ås, Norway; Department of Mathematical Sciences and Technology (IMT), Norwegian University of Life Sciences, 1432 Ås, Norway 2: Nofima Mat, Centre for Biospectroscopy and Data Modelling, Osloveien 1, 1430 Ås, Norway; CIGENE - Center for Integrative Genetics, University of Life Sciences, 1432 Ås, Norway 3: Department of Cell and Molecular Biology, University of Gothenburg, 41390 Göteborg, Sweden 4: CIGENE - Center for Integrative Genetics, University of Life Sciences, 1432 Ås, Norway; Department of Animal and Aquacultural Sciences, Norwegian University of Life Sciences, 1432 Ås, Norway 5: KES Analysis, Inc, New York, New York 6: Nofima Mat, Centre for Biospectroscopy and Data Modelling, Osloveien 1, 1430 Ås, Norway; CIGENE - Center for Integrative Genetics, University of Life Sciences, 1432 Ås, Norway; Department of Mathematical Sciences and Technology (IMT), Norwegian University of Life Sciences, 1432 Ås, Norway; Faculty of Life Sciences, University of Copenhagen, Denmark

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