Dissimilarity measures and hierarchical methods for the study of genetic diversity on soybean

Abstract

ABSTRACT:In analysis of the genetic diversity on soybean can be used agronomic, morphological and molecular traits, which are subjected to multivariate biometrical analysis. There are different multivariate methodologies available such as Euclidean distance, Mahalanobis distance and different hierarchical methods. However, studies that may assist in the choice of such methods are lacking. The aim of this paper was to evaluate the clustering standards of soybean genotypes using Euclidean and Mahalanobis distances, following different hierarchical methods. The experiment was conducted in "Capim Branco" farm which belongs to the Federal University of Uberlândia and were used a complete randomized block design composed of 15 soybean genotypes (nine breeding lines and six cultivars) and four replications. The agronomic traits evaluated were: number of days to flowering and to maturity, height of the plant at flowering and at maturity, height of the insertion of the first pod, number of nodes on the main stalk in flowering and at maturity, number of grains per pod, total number of pods, severity of Asian rust, number of pustules and yield. The data were submitted to multivariate analysis in GENES program. The Mahalanobis distance or the Euclidean distance obtained by agronomic traits allows the determination of soybean genetic diversity. The use of the Euclidean distance in hierarchical methods allows a greater group differentiation. The UPGMA method and the nearest neighbor method shows a greater accuracy using the Mahalanobis distance and Euclidean distance.

Combining performance and estimated genetic diversity among soybean parents and F1 populations

“…The UP-GMA hierarchical method calculates the distance between two clusters as the average distance between all pairs of items of two clusters (Oliveira et al, 2017). Methods that group the genotypes based on some similarity or dissimilarity measures aim to separate an original group observed into several subgroups, in a way to obtain intra-subgroup homogeneity and inter-subgroup heterogeneity (Rodrigues et al, 2017).…”