Abstract

In this work it is presented a methodology for the development of a pattern recognition system using classification methods as discriminant analysis and artificial neural networks. In this methodology, the statistical analysis is contemplated, with the purpose of retaining the observations and the important characteristics that can produce an appropriate classification, and allows, as well, to detect outliers’ observations, multicolinearity between variables, among other things. Chlorophyll a fluorescence OJIP signals measured from Pisum sativum leaves belonging to different drought stress resistance groups are correctly classified using the proposed here methodology.