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Download Hi-Res ImageDownload to MS-PowerPointCite This:Anal. Chem. 1997, 69, 21, 4381-4389
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Genetic Programming:  A Novel Method for the Quantitative Analysis of Pyrolysis Mass Spectral Data

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Institute of Biological Sciences, University of Wales, Aberystwyth, SY23 3DA, U.K.
Cite this: Anal. Chem. 1997, 69, 21, 4381–4389
Publication Date (Web):November 1, 1997
https://doi.org/10.1021/ac970460j
Copyright © 1997 American Chemical Society
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    Abstract

    A technique for the analysis of multivariate data by genetic programming (GP) is described, with particular reference to the quantitative analysis of orange juice adulteration data collected by pyrolysis mass spectrometry (PyMS). The dimensionality of the input space was reduced by ranking variables according to product moment correlation or mutual information with the outputs. The GP technique as described gives predictive errors equivalent to, if not better than, more widespread methods such as partial least squares and artificial neural networks but additionally can provide a means for easing the interpretation of the correlation between input and output variables. The described application demonstrates that by using the GP method for analyzing PyMS data the adulteration of orange juice with 10% sucrose solution can be quantified reliably over a 0−20% range with an RMS error in the estimate of ∼1%.

    †

     E-mail:  [email protected].

    *

    In papers with more than one author, the asterisk indicates the name of the author to whom inquiries about the paper should be addressed.

    ‡

     E-mail:  [email protected].

    §

     E-mail:  [email protected].

    ‖

     E-mail:  [email protected].

    ✗

     Abstract published in Advance ACS Abstracts, October 1, 1997.

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