Estimation of Genetic Parameters in Coffea canephora Var. Robusta
Received Date: Sep 05, 2017 / Accepted Date: Oct 24, 2017 / Published Date: Oct 30, 2017
The objective of this work was to assess the genetic parameters in Coffea robusta clones using mixed model. The experiments were carried out during four years, in complete block design, and one plant per plot, at Oratorio of Minas Gerais state, Brazil. The clones were evaluated for vigor, reaction to rust, reaction to Cercospora, number of ortotropicos branches, number of plegiotropics branches, plant height, diameter of stem, fruit maturity, diameter of canopy, fruit size and production of fruits. The data were analyzed using the mixed model methodology (REML/ BLUP) of Selegen software for estimation of genetic parameters in C. canephora breeding. The results showed a low genetic variability among the clones of Robusta for all the evaluated traits. On the other hand, relatively high residual coefficient of variation for most of the traits was recorded implying that these traits seem to be highly influenced by the environmental variation. However, in this study the estimates of individual heritability in the broad sense (h2g) was of low magnitude, but were significant for all traits except yield (sac/ha). The estimated repeatability for most of the traits was low indicating the irregularity of the superiority of the individuals among the measurements showing that genotype selection based on these traits is not reliable strategy. Generally, there was low interaction with year, as observed by the genotypic correlation across measurement (rgmed) for most of the characters evaluated demonstrating that selection can be performed at any of the development stages used for measurement.
Keywords: Heritability; Mixed model; Repeatability
Citation: Bikila BA, Sakiyama NS (2017) Estimation of Genetic Parameters in Coffea canephora Var. Robusta. Adv Crop Sci Tech 5: 310. Doi: 10.4172/2329-8863.1000310
Copyright: © 2017 Bikila BA, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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