Artificial neural networks for adaptability and stability evaluation in alfalfa genotypes

The purpose of this work was to evaluate a methodology of adaptability and phenotypic stability of alfalfa genotypes basedon the training of an artificial neural network considering the methodology of Eberhart and Russell. Data from an experiment on drymatter production of 92 alfalfa genotypes (Medicago sativa L.) were used. The experimental design constituted of randomized blocks,with two repetitions. The genotypes were submitted to 20 cuttings, in the growing season of November 2004 to June 2006. Each cuttingwas considered an environment. The artificial neural network was able to satisfactorily classify the genotypes. In addition, the analysispresented high agreement rates, compared with the results obtained by the methodology of Eberhart and Russell.