the detection method includes generating a plurality of neural network models . each model has as a training set a data set from a plurality of samples of a commodity of known origins . each sample has been analyzed for a plurality of elemental concentrations . each neural network model is presented for classification a test data set from a plurality of samples of a commodity of unknown origins . as with the training set , the samples have been analyzed for the same plurality of elemental concentrations . next a bootstrap aggregating strategy is employed to combine the results of the classifications for each sample in the test data set made by each neural network model . finally , a determination is made from the bootstrap aggregating strategy as to a final classification of each sample in the test data set . this final classification is indicative of the geographical origin of the commodity . the system includes software for generating the neural network models and a software routine for performing the bootstrap aggregating strategy .