Cluster Analysis in the study of agronomic traits for corn

Abstract

Studies based on genetic data are important for the knowledge of the genetic variability of the populations, besides providing parameters for parent choice. In the studies to analyze how far genetically one genotype is from another are used multivariate statistical methods, allowing to unify multiple information of a set of characters. Thus, the present work aims used corn agronomic traits in the application of the fuzzy c-means clustering algorithm, in order to assist in the characterization of the groups obtained, observing through the degree of relationship of the individual with the group, which type of individual joins a certain group. Three clusters with specific characteristics were identified and the individuals of the first cluster presented superior agronomic performance when compared with the individuals of the other cluster.