Abstract Details
Activity Number:
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374
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Type:
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Contributed
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Date/Time:
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Tuesday, August 6, 2013 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Bayesian Statistical Science
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Abstract - #309565 |
Title:
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Bayesian Estimation of Precision and Genetic Gain Due To Selection in Barley Trials
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Author(s):
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Murari Singh*+ and Adnan Al- Yassin and Siraj Osman Omer Mohamed
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Companies:
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ICARDA and ICARDA and ICARDA
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Keywords:
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Bayesian analysis ;
Barley trials ;
Genetic gain ;
Efficiency of incomplete block design ;
Coefficient of variation ;
heritability
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Abstract:
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Crop varieties are generally evaluated in block designs and analyzed under the frequentist approach. The objectives of this study is to present systematically, under Bayesian framework, the methodology of analyzing data from experiments designed in randomized complete blocks and one-way incomplete blocks. We apply the standard criterion for selection of the best priors out of the chosen candidate priors. The selected priors were used to estimate various statistics such as experimental error variance, CV, predicted means of genotypes, with standard errors and confidence intervals, average standard error of differences of predicted means, genetic gain due to selection, realized gain due to selection, and ranking of genotypes for selection. Data on grain yields of barley genotypes evaluated under the two block designs at Tel Hadya during 2012 were used. Distribution of heritability and genetic gain was found to be skewed. Substantial difference between the posterior means and the frequentist estimates for these parameters. Due to the much more wider framework for statistical inference, the Bayesian approach is recommended for the routine variety trials data analysis.
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Authors who are presenting talks have a * after their name.
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