Mostrando ítems 1-10 de 51
Use of genomic estimated breeding values results in rapid genetic gains for drought tolerance in maize
More than 80% of the 19 million ha of maize (Zea mays L.) in tropical Asia is rainfed and prone to drought. The breeding methods for improving drought tolerance (DT), including genomic selection (GS), are geared to ...
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: ...
A genomic selection index applied to simulated and real data
(Genetics Society of America, 2015)
A genomic selection index (GSI) is a linear combination of genomic estimated breeding values that uses genomic markers to predict the net genetic merit and select parents from a nonphenotyped testing population. Some ...
Genome-enabled prediction of genetic values using radial basis function neural networks
The availability of high density panels of molecular markers has prompted the adoption of genomic selection (GS) methods in animal and plant breeding. In GS, parametric, semi-parametric and non-parametric regressions models ...
Performance and grain yield stability of maize populations developed using marker-assisted recurrent selection and pedigree selection procedures
A marker-assisted recurrent selection (MARS) program was undertaken in sub-Saharan Africa to improve grain yield under drought-stress in 10 biparental tropical maize populations. The objectives of the present study were ...
Factors affecting the accuracy of genotype imputation in populations from several maize breeding programs
Genomic selection and association mapping offer great potential to increase rates of genetic progress in plants. The prediction of genomic breeding values usually requires that missing genotypes be imputed because a ...
Effectiveness of Genomic Prediction of Maize Hybrid Performance in Different Breeding Populations and Environments
Genomic prediction is expected to considerably increase genetic gains by increasing selection intensity and accelerating the breeding cycle. In this study, marker effects estimated in 255 diverse maize (Zea mays L.) hybrids ...
QTL mapping in three tropical maize populations reveals a set of constitutive and adaptive genomic regions for drought tolerance
Despite numerous published reports of quantitative trait loci (QTL) for drought-related traits, practical applications of such QTL in maize improvement are scarce. Identifying QTL of sizeable effects that express more or ...
Genomic prediction in CIMMYT maize and wheat breeding programs
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 ...