Metabolic fingerprinting of salt-stressed tomatoes

Created by W.Langdon from gp-bibliography.bib Revision:1.4192

  author =       "A. R. Smith and H. E. Johnson and M. Hall",
  title =        "Metabolic fingerprinting of salt-stressed tomatoes",
  journal =      "Bulgarian Journal of Plant Physiology",
  year =         "2003",
  volume =       "29",
  pages =        "153--163",
  note =         "Special Issue. Proceedings of the European Workshop on
                 Environmental Stress and Sustainable Agriculture, 07-12
                 Sept. 2002 Varna, Bulgaria",
  keywords =     "genetic algorithms, genetic programming, metabolic
                 fingerprinting, salt stress, tomatoes",
  ISSN =         "1310-4586",
  URL =          "",
  URL =          "",
  size =         "11 pages",
  abstract =     "Increased salinisation of agricultural land is having
                 a significant impact on agriculture, decreasing crop
                 productivity. The research presented is part of a
                 collaborative EU INCO-DC project. Data will be
                 presented on two objectives: firstly the selection and
                 screening of tomato varieties for potential salt
                 tolerance and secondly, studies on the effect of
                 salinity on fruit yield and quality.

                 Results indicated that a variety, Edkawy, displayed
                 properties of salt tolerance hence it was selected as a
                 model for metabolomic fingerprinting studies.
                 Preliminary data obtained using Pyrolysis Mass
                 Spectrometry (PyMS) and analysed by Principal Component
                 Analysis (PCA) enabled discrimination between fruit
                 according to ripeness stage, fruit ripened on- and
                 off-the-vine and fruit artificially ripened with
                 ethylene. Tomatoes grown under conditions of high and
                 low-salt concentrations were analysed using Fourier
                 Transform InfraRed spectroscopy (FTIR) with the aim of
                 identifying biochemical features linked to salinity in
                 the environment. FTIR spectra of whole tissue extracts
                 are not amenable to visual analysis so evolutionary
                 computer modelling methods were applied which were
                 capable of classifying samples on their spectral
                 characteristics. Genetic Programming (GP) models proved
                 to be successful in enabling a chemical interpretation
                 of biochemical fingerprint differences to be proposed.
                 The authors acknowledge the support of the Analytical
                 Biotechnology and Machine Learning group
  notes =        "See \cite{johnson:2003:mfsst}

                 As from 2005 journal renamed 'General and Applied Plant

Genetic Programming entries for Aileen R Smith Helen E Johnson Michael A Hall