Genetic divergence toward the selection of promising bean progenitors via mixed multivariate models

Abstract

The genetic variability present in the bean (Phaseolus vulgaris L.) germplasm that is currently used as an agricultural crop has been shown to be stable in production and is acceptable for human sustenance. Accordingly, to maintain as much of the available variability as possible, this study aimed to examine the genetic divergence in the bean using multivariate analysis to identify the sources of genetic variability and enable breeders to recognize genetic combinations that have a greater chances of success before crossings are performed. This study was conducted in a randomized block design with three replications in the agricultural year 2015. The agronomic traits evaluated were the stem diameter (DIAM) in millimeters, plant height (PH) in centimeters, number of seedsper plant (NS), protein percentage (PROT), height of the first pod (HFP) in centimeters, pod number (PN), grain mass per plant (GM) in g plant-1, grain yield (GY) in kg ha-1, and straw yield (SY) in kg ha-1. To enable selection of the most divergent genotypes, twenty different genotypes were analyzed via clustering according to the average linkage criterion (UPGMA) using a matrix of the mean standardized Euclidean distances and principal component analysis based on the values predicted via a multivariate mixed model. The results obtained in this study revealed a high degree of genetic divergence and allowed the progenies to be allocated into different groups, as well as recommended crossings for future bean breeding programs.