Abstract: A metabonomic method of selecting one or more non-human primate subjects for inclusion in a study is disclosed. The method generally involves spectroscopically profiling a sample of bodily fluid acquired from a subject proposed to be included in the study. The subject is accepted or rejected as a member of the proposed study based on a chemometric analysis of the similarities and differences between the subjects' samples, which provides a homogeneous subject pool for the study. The method can be applied to any type of subject, for example, non-human primates.

Abstract: Methods are provided that apply neural network technology to recognize small metabolic changes in microorganisms, plants or animals to detect changes induced by pesticide (herbicide, insecticide, fungicide) treatment, genetic modification, environmental stress, and other external or internal factors that have influence on metabolite concentrations. The method implements recognition of nuclear magnetic resonance spectra, mass spectra, and/or chromatograms of crude plant extracts and association of such spectra or chromatograms with the treatment of tissue before harvest. The spectra and chromatograms have information of all the metabolites above a concentration threshold contained in the plant tissue extract. The method applies mathematical models to the very complex plant tissue extract and allows the detection of treatments with bioregulators such as pesticides, or genetic modifications such as gene insertions or deletions.