Genetic diversity among cassava genotypes (Manihot esculenta crantz) collected in the south-central mesoregion of the state of Mato Grosso-Brazil
DOI:
https://doi.org/10.14393/BJ-v37n0a2021-54068Palavras-chave:
Agronomic Descriptors, Genetic Dissimilarity, Genetic Improvement.Resumo
The aim of this research was to evaluate the genetic divergence between 164 genotypes of Manihot esculenta from the South-Central mesoregion of the State of Mato Grosso. The genotypes are from projects conducted by the Laboratory of Genetic Resources & Biotechnology of the University of the State of Mato Grosso, Cáceres-Mato Grosso (UNEMAT), and the Brazilian Public Agricultural Research Corporation - Agrosilvopastoral (EMBRAPA). The agronomic descriptors evaluated were plant height, height of first branching, branching levels, weight of the aerial part of the plant, total weight of the plant, number of roots per plant, average weight of roots per plant, yield of commercial roots, yield of non-commercial roots, number of rotten roots per plant and harvest index. For the analysis of genetic divergence, multivariate analysis based on the standardized Euclidean mean distance was employed, later performing the Hierarchical UPGMA and Tocher Optimization agglomerative methods. The degree of preservation of the genetic distances in the dendrogram was verified using the Cophenetic Correlation Coefficient. The Singh criterion was used to quantify the relative contribution of characteristics to genetic divergence. The genotypes presented genetic dissimilarity for the evaluated characteristics and based on the results of the dissimilarity matrix and groupings, it is recommended the crossings between the genotypes allocated in group II with the genotype allocated in group V, for the development of segregated populations with high genetic variability.
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Copyright (c) 2021 Bruno Wagner Zago , Marco Antonio Aparecido Barelli, Valvenarg Pereira da Silva, Rafhael Felipin-Azevedo, Carla Lima Corrêa , Leonarda Grillo Neves , Eulalia Soler Sobreira Hoogerheide
Este trabalho está licenciado sob uma licença Creative Commons Attribution 4.0 International License.
