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Article
An R Package for Bayesian analysis of multi-environment and multi-trait multi-environment data for genome-based prediction
(Genetics Society of America, 2019)
Evidence that genomic selection (GS) is a technology that is revolutionizing plant breeding continues to grow. However, it is very well documented that its success strongly depends on statistical models, which are used by ...
Article
New deep learning genomic-based prediction model for multiple traits with binary, ordinal, and continuous phenotypes
(Genetics Society of America, 2019)
Multiple-trait experiments with mixed phenotypes (binary, ordinal and continuous) are not rare in animal and plant breeding programs. However, there is a lack of statistical models that can exploit the correlation between ...
Article
A benchmarking between deep learning, support vector machine and bayesian threshold best linear unbiased prediction for predicting ordinal traits in plant breeding
(Genetics Society of America, 2019)
Genomic selection is revolutionizing plant breeding. However, still lacking are better statistical models for ordinal phenotypes to improve the accuracy of the selection of candidate genotypes. For this reason, in this ...
Article
Genome-wide association study to identify genomic regions influencing spontaneous fertility in maize haploids
(Springer, 2019)
Efficient production and use of doubled haploid lines can greatly accelerate genetic gains in maize breeding programs. One of the critical steps in standard doubled haploid line production is doubling the haploid genome ...
Article
Genome-wide association mapping and genomic prediction analyses reveal the genetic architecture of grain yield and flowering time under drought and heat stress conditions in maize
(Blackwell Verlag, 2019)
Drought stress (DS) is a major constraint to maize yield production. Heat stress (HS) alone and in combination with DS are likely to become the increasing constraints. Association mapping and genomic prediction (GP) analyses ...