Chemometric discrimination of unfractionated plant extracts analyzed by electrospray mass spectrometry.
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.
Goodacre
Royston
R
Institute of Biological Sciences, University of Wales Aberystwyth, Ceredigion SY23 3DA, UK.
York
Emma V
EV
Heald
James K
JK
Scott
Ian M
IM
D001185:Artificial Intelligence; D016002:Discriminant Analysis; D027741:Ipomoea / Q000737:chemistry; D016571:Neural Networks, Computer; D017440:Photoperiod; D010936:Plant Extracts / Q000737:chemistry*; D018515:Plant Leaves / Q000737:chemistry; D021241:Spectrometry, Mass, Electrospray Ionization
D010936:Plant Extracts