Parameter estimation and selection efficiency under Bayesian and frequentist approaches in peach trials
نویسندگان
چکیده
Identification of stable and high-yielding genotypes is a real challenge in peach breeding, since genotype-by-environment interaction (GE) masks the performance materials. The aim this work was to evaluate effectiveness parameter estimation genotype selection solving linear mixed models (LMM) under frequentist Bayesian approaches. Fruit yield 308 were assessed different seasons replication numbers arranged completely randomized design. Under framework restricted maximum likelihood method estimate variance component genotypic prediction used. Different considering environment, GE effects according ratio test Akaike information criteria compared. In approach, mean components assumed be random variables having priori non-informative distributions with known parameters. According deviance most suitable model selected. full appropriate calculate parameters predictions, which very similar both Due imbalance data, Cullis’s heritability. It calculated at 0.80, selecting above 5% genotypes, realized gain 14.80 kg tree1 attained. Genotypic predictions showed positive correlation (r = 0.9991; P 0.0001). Since incorporates credible interval for genetic parameters, would more useful tool than approach allowed 17 genotypes.
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ژورنال
عنوان ژورنال: Euphytica
سال: 2022
ISSN: ['1573-5060', '0014-2336']
DOI: https://doi.org/10.1007/s10681-022-03063-3