The detection of caffeine in a variety of beverages using Curie-point pyrolysis mass spectrometry and genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3949

@Article{goodacre:1999:dcvbcppmsGP,
  author =       "Royston Goodacre and Richard J. Gilbert",
  title =        "The detection of caffeine in a variety of beverages
                 using Curie-point pyrolysis mass spectrometry and
                 genetic programming",
  journal =      "The Analyst",
  year =         "1999",
  volume =       "124",
  number =       "7",
  pages =        "1069--1074",
  keywords =     "genetic algorithms, genetic programming",
  URL =          "http://pubs.rsc.org/en/content/articlelanding/1999/an/a901062i",
  DOI =          "doi:10.1039/A901062I",
  size =         "6 pages",
  abstract =     "Freeze dried coffee, filter coffee, tea and cola were
                 analysed by Curie-point pyrolysis mass spectrometry
                 (PyMS). Cluster analysis showed, perhaps not
                 surprisingly, that the discrimination between coffee,
                 tea and cola was very easy. However, cluster analysis
                 also indicated that there was a secondary difference
                 between these beverages which could be attributed to
                 whether they were caffeine- containing or
                 decaffeinated. Artificial neural networks (ANNs) could
                 be trained, with the pyrolysis mass spectra from some
                 of the freeze dried coffees, to classify correctly the
                 caffeine status of the unseen spectra of freeze dried
                 coffee, filter coffee, tea and cola in an independent
                 test set. However, the information in terms of which
                 masses in the mass spectrum are important was not
                 available, which is why ANNs are often perceived as a
                 'black box' approach to modelling spectra. By contrast,
                 genetic programs (GPs) could also be used to classify
                 correctly the caffeine status of the beverages, but
                 which evolved function trees (or mathematical rules)
                 enabling the deconvolution of the spectra and which
                 highlighted that m/z 67, 109 and 165 were the most
                 significant massed for this classification. Moreover,
                 the chemical structure of these mass ions could be
                 assigned to the reproducible pyrolytic degradation
                 products from caffeine.",
}

Genetic Programming entries for Royston Goodacre Richard J Gilbert

Citations