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Article
Multi-environment genomic prediction of plant traits using deep learners with dense architecture
(Genetics Society of America, 2018)
Article
Bayesian multitrait kernel methods improve multienvironment genome-based prediction
(Oxford University Press, 2022)
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 genomic bayesian multi-trait and multi-environment model
(Genetics Society of America, 2016)
When information on multiple genotypes evaluated in multiple environments is recorded, a multi-environment single trait model for assessing genotype · environment interaction (G · E) is usually employed. Comprehensive ...
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, ...
Article
Canopy temperature and vegetation indices from high-throughput phenotyping improve accuracy of pedigree and genomic selection for grain yield in wheat
(Genetics Society of America, 2016)
Genomic selection can be applied prior to phenotyping, enabling shorter breeding cycles and greater rates of genetic gain relative to phenotypic selection. Traits measured using high-throughput phenotyping based on proximal ...