Genetic Programming:  A Novel Method for the Quantitative Analysis of Pyrolysis Mass Spectral Data

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...

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Bibliographic Details
Published in:Analytical chemistry (Washington) 1997-11, Vol.69 (21), p.4381-4389
Main Authors: Gilbert, Richard J, Goodacre, Royston, Woodward, Andrew M, Kell, Douglas B
Format: Article
Language:English
Subjects:
Biological and medical sciences
Chemistry
Food industries
Fruit and vegetable industries
Fundamental and applied biological sciences. Psychology
Genetic engineering
Scientific imaging
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Summary: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%.
ISSN:0003-2700
1520-6882
DOI:10.1021/ac970460j