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Mostrando ítems 1-7 de 7
Article
Genomic-enabled prediction with classification algorithms
(Springer Nature, 2014)
Pearson’s correlation coefficient (ρ) is the most commonly reported metric of the success of prediction in genomic selection (GS). However, in real breeding ρ may not be very useful for assessing the quality of the regression ...
Article
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 ...
Article
Article
Genomic-enabled prediction in maize using kernel models with genotype x environment interaction
(Genetics Society of America, 2017)
Multi-environment trials are routinely conducted in plant breeding to select candidates for the next selection cycle. In this study, we compare the prediction accuracy of four developed genomic-enabled prediction models: ...
Article
A Bayesian decision theory approach for genomic selection
(Genetics Society of America, 2018)
Plant and animal breeders are interested in selecting the best individuals from a candidate set for the next breeding cycle. In this paper, we propose a formal method under the Bayesian decision theory framework to tackle ...
Article
Bayesian genomic prediction with genotype x environment interaction kernel models
(Genetics Society of America, 2017)
The phenomenon of genotype · environment (G · E) interaction in plant breeding decreases selection accuracy, thereby negatively affecting genetic gains. Several genomic prediction models incorporating G · E have been ...
Article
Genomic prediction in maize breeding populations with genotyping-by sequencing
(Genetics Society of America, 2013)
Genotyping-by-sequencing (GBS) technologies have proven capacity for delivering large numbers of marker genotypes with potentially less ascertainment bias than standard single nucleotide polymorphism (SNP) arrays. Therefore, ...