Predicted genetic gains by various selection methods in Eucalyptus urophylla progenies

Authors

  • Antonio Marcos Rosado Celulose Nipo-Brasileira S.A.
  • Tatiana Barbosa Rosado
  • Márcio Fernando Ribeiro Resende Júnior
  • Leonardo Lopes Bhering
  • Cosme Damião Cruz

DOI:

https://doi.org/10.1590/S1678-3921.pab2009.v44.2267

Keywords:

eucalyptus, genetic gains, forestry breeding, mixed models

Abstract

The objective of this work was to evaluate genetic parameters and to compare predicted gains using different selection methods in half-sib families of Eucalyptus urophylla. Within and between selection, combined selection and selection based on mixed model equations (REML/BLUP) were used for the traits diameter at breast height, total height and total volume with bark. The progeny test used consisted of 100 55-month-old half-sib families distributed in a 3x2-m spacing, in randomized complete block design with five replicates. The progenies showed significant genetic variability and high heritability for the studied traits, which indicates high genetic control and favorable conditions for selection. All the methods tested were efficient in eucalyptus breeding. However, the combined selection and the selection based on mixed models (BLUP) provided gains significantly larger than those obtained with within and between selections, and were more efficient in the selection of the best individuals in the population.

Author Biography

Antonio Marcos Rosado, Celulose Nipo-Brasileira S.A.

Engenheiro Florestal, mestrado e doutorado em Genética e Melhoramento pela Universidade Federal de Viçosa, atuação profissional atual como pesquisador na área de melhoramento genético florestal

Published

2010-12-23

How to Cite

Rosado, A. M., Rosado, T. B., Júnior, M. F. R. R., Bhering, L. L., & Cruz, C. D. (2010). Predicted genetic gains by various selection methods in <i>Eucalyptus urophylla</i> progenies. Pesquisa Agropecuaria Brasileira, 44(12), 1653–1659. https://doi.org/10.1590/S1678-3921.pab2009.v44.2267

Issue

Section

GENETICS