Robust estimation of heritability and predictive accuracy in plant breeding: evaluation using simulation and empirical data.

ABSTRACT:

Background

Genomic prediction (GP) is used in animal and plant breeding to help identify the best genotypes for selection. One of the most important measures of the effectiveness and reliability of GP in plant breeding is predictive accuracy. An accurate estimate of this measure is thus central to GP. Moreover, regression models are the models of choice for analyzing field trial data in plant breeding. However, models that use the classical likelihood typically perform poorly, often resulting in biased parameter estimates, when their underlying assumptions are violated. This typically happens when data are contaminated with outliers. These biases often translate into inaccurate estimates of heritability and predictive accuracy, compromising the performance of GP. Since phenotypic d

SUBMITTER: Lourenco VM 

PROVIDER: S-EPMC6958597 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature