Chemometric discrimination of unfractionated plant extracts analyzed by electrospray mass spectrometry

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@Article{goodacre:2003:cdupx,

• author = "Royston Goodacre and Emma V. York and James K. Heald and Ian M. Scott",
• title = "Chemometric discrimination of unfractionated plant extracts analyzed by electrospray mass spectrometry",
• journal = "Phytochemistry",
• year = "2003",
• volume = "62",
• number = "6",
• pages = "859--863",
• month = mar,
• keywords = "genetic algorithms, genetic programming, Pharbitis nil, Convolvulaceae, Japanese Morning Glory, Electrospray ionization mass spectrometry, Neural networks, Metabolic fingerprinting",
• URL = "http://www.sciencedirect.com/science/article/B6TH7-47WBXD4-7/2/91ff09f988be54824c55a1cb596f7839",
• DOI = "doi:10.1016/S0031-9422(02)00718-5",
• abstract = "Metabolic fingerprints were obtained from unfractionated Pharbitis nil leaf sap samples by direct infusion into an electrospray ionization mass spectrometer. Analyses took less than 30 s per sample and yielded complex mass spectra. Various chemometric methods, including discriminant function analysis and the machine-learning methods of artificial neural networks and genetic programming, could discriminate the metabolic fingerprints of plants subjected to different photoperiod treatments. This rapid automated analytical procedure could find use in a variety of phytochemical applications requiring high sample throughput.",
• notes = "GMax-Bio, Plant Metabolomics",

}

Genetic Programming entries for Royston Goodacre Emma V York James K Heald Ian M Scott

Citations