Abstract

Multiple–environmental trials are routinely conducted by crop improvement programs for developing desired genotypes. Over a long run, these programs gather information on genotypic performance and variability. Bayesian approach can be used to utilize prior information to identify genotypes for high and stable yield. A set of 18 sorghum genotypes were evaluated in randomized complete block designs (RCBD) with four replications during three seasons, 2009-2012 at diverse locations, North-Gedarif and South-Gedarif, in Sudan. Data on grain yield was analyzed. The aim of this paper was to estimate stability indices such as regression coefficient, coefficient of variation (CV %) and coefficient of determination (R2) using a Bayesian approach. R2WinBUGS and R packages have been used. The results of these different stability indices agreements and suggesting that this approach produces reliable estimates of the stability of crop variety. In general, Bayesian compared to frequentist approach gave higher precision in terms of standard error of genotypes means, regression coefficient and coefficient of determination. Moreover, Bayesian has a broader inference-base to allow an integration of prior information about the current data and is recommended for use following the steps illustrated with the example datasets.

Keywords

Stability Analysis, Genotypes by Environment Interaction (GEI), Bayesian Approach, R2WINBUG.

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May 1st, 10:00 AM

BAYESIAN ESTIMATION OF STABILITY INDICES OF SORGHUM VARIETY TRIALS

Multiple–environmental trials are routinely conducted by crop improvement programs for developing desired genotypes. Over a long run, these programs gather information on genotypic performance and variability. Bayesian approach can be used to utilize prior information to identify genotypes for high and stable yield. A set of 18 sorghum genotypes were evaluated in randomized complete block designs (RCBD) with four replications during three seasons, 2009-2012 at diverse locations, North-Gedarif and South-Gedarif, in Sudan. Data on grain yield was analyzed. The aim of this paper was to estimate stability indices such as regression coefficient, coefficient of variation (CV %) and coefficient of determination (R2) using a Bayesian approach. R2WinBUGS and R packages have been used. The results of these different stability indices agreements and suggesting that this approach produces reliable estimates of the stability of crop variety. In general, Bayesian compared to frequentist approach gave higher precision in terms of standard error of genotypes means, regression coefficient and coefficient of determination. Moreover, Bayesian has a broader inference-base to allow an integration of prior information about the current data and is recommended for use following the steps illustrated with the example datasets.