Analysis of genetic divergence through agronomic characters in green corn cultivars

Abstract

The genetic divergence in maize populations is important, as it allows us to identify among the existing genotypes, the best ones to be used as parents in future breeding programs as a strategy for obtaining greater gains. Therefore, the objective of this work was to estimate the genetic divergences in green corn cultivars. The tests were conducted in the 2019/20 harvest on a property in the state of Pará. The design used in the given experiment was randomized blocks (DBC) and 3 replicates. The experimental plot consisted of 4 rows of 5.0 m spaced at 0.9 m between rows, the two central rows being considered the useful area. The genetic divergence was evaluated by multivariate procedures such as the generalized Mahalanobis distance and by Tocher optimization grouping methods and Singh criterion to quantify the relative contribution of the seven characteristics. The characteristics average mass of grains per ear and number of grains in the row of the ear were the ones that most contributed to genetic divergence. The dual hybrids BR205 and BRS3046 and the triple hybrid AG8088 are potentially promising for use in future breeding programs.