Now showing items 1-10 of 41
A multivariate Poisson deep learning model for genomic prediction of count data
(Genetics Society of America, 2020)
A bayesian poisson-lognormal model for count data for multiple-trait multiple-environment genomic-enabled prediction
(Genetics Society of America, 2017)
When a plant scientist wishes to make genomic-enabled predictions of multiple traits measured in multiple individuals in multiple environments, the most common strategy for performing the analysis is to use a single trait ...
The use of unbalanced historical data for genomic selection in an international wheat breeding program
Genomic selection (GS) offers breeders the possibility of using historic data and unbalanced breeding trials to form training populations for predicting the performance of new lines. However, when using datasets that are ...
Genomic prediction in CIMMYT maize and wheat breeding programs
(Springer Nature, 2014)
Genomic selection (GS) has been implemented in animal and plant species, and is regarded as a useful tool for accelerating genetic gains. Varying levels of genomic prediction accuracy have been obtained in plants, depending ...
Genome‑wide association and genomic prediction of resistance to maize lethal necrosis disease in tropical maize germplasm
The maize lethal necrosis disease (MLND) caused by synergistic interaction of Maize chlorotic mottle virus and Sugarcane mosaic virus, and has emerged as a serious threat to maize production in eastern Africa since 2011. ...
Initiating maize pre-breeding programs using genomic selection to harness polygenic variation from landrace populations
(BioMed Central, 2016)
Background: The limited genetic diversity of elite maize germplasms raises concerns about the potential to breed for new challenges. Initiatives have been formed over the years to identify and utilize useful diversity from ...
Upstream research for accelerated genetic gain