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The present work appeals to a classification approach based on a network of artificial neurons of type Self-Organizing map SOM. This algorithm has been used to better discriminate individuals (measuring points) by highlighting nonlinear relationships unobtainable with classic methods of ordination. Thus, from an unsupervised learning of an artificial neural network, this algorithm searches iteratively for similarities among the observed data and represents them on a map output (Kohonen map). Indoi:10.6084/m9.figshare.3470237.v1 fatcat:62phes7lhff4hknhdmsubqlnn4