Estimation of Genetic Parameters in Coffea canephora Var. Robusta

Article ID

8986A

Estimation of Genetic Parameters in Coffea canephora Var. Robusta

Bayisa Asefa Bikila
Bayisa Asefa Bikila Ethiopian Institute of Agricultural Research
Ney Sussumu Sakiyama
Ney Sussumu Sakiyama
DOI

Abstract

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 cercospera, 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 (h 2 g ) 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 (r gmed ) for most of the characters evaluated demonstrating that selection can be performed at any of the development stages used for measurement.

Estimation of Genetic Parameters in Coffea canephora Var. Robusta

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 cercospera, 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 (h 2 g ) 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 (r gmed ) for most of the characters evaluated demonstrating that selection can be performed at any of the development stages used for measurement.

Bayisa Asefa Bikila
Bayisa Asefa Bikila Ethiopian Institute of Agricultural Research
Ney Sussumu Sakiyama
Ney Sussumu Sakiyama

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Bayisa Asefa Bikila. 2017. “. Global Journal of Science Frontier Research – D: Agriculture & Veterinary GJSFR-D Volume 17 (GJSFR Volume 17 Issue D5): .

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Crossref Journal DOI 10.17406/GJSFR

Print ISSN 0975-5896

e-ISSN 2249-4626

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GJSFR-D Classification: FOR Code: 070199
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Estimation of Genetic Parameters in Coffea canephora Var. Robusta

Bayisa Asefa Bikila
Bayisa Asefa Bikila Ethiopian Institute of Agricultural Research
Ney Sussumu Sakiyama
Ney Sussumu Sakiyama

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