Now showing items 1-10 of 20
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 ...
Mejoramiento de la calidad de trigo
Integrating genomic-enabled prediction and high-throughput phenotyping in breeding for climate-resilient bread wheat
Genomic selection and high-throughput phenotyping (HTP) are promising tools to accelerate breeding gains for high-yielding and climate-resilient wheat varieties. Hence, our objective was to evaluate them for predicting ...
Strategies for selecting crosses using genomic prediction in two wheat breeding programs
(Crop Science Society of America, 2017)
The single most important decision in plant breeding programs is the selection of appropriate crosses. The ideal cross would provide superior predicted progeny performance and enough diversity to maintain genetic gain. The ...
Genetic dissection of grain zinc concentration in spring wheat for mainstreaming biofortification in CIMMYT wheat breeding
(Nature Publishing Group, 2018)
Wheat is an important staple that acts as a primary source of dietary energy, protein, and essential micronutrients such as iron (Fe) and zinc (Zn) for the world?s population. Approximately two billion people suffer from ...
Breeding-assisted genomics: applying meta- GWAS for milling and baking quality in CIMMYT wheat breeding program
(Public Library of Science, 2018)
One of the biggest challenges for genetic studies on natural or unstructured populations is the unbalanced datasets where individuals are measured at different times and environments. This problem is also common in crop ...
Identification and validation of a common stem rust resistance locus in two bi-parental populations
Races belonging to Ug99 lineage of stem rust fungus Puccinia graminis f. sp. tritici (Pgt) continue to pose a threat to wheat (Triticum aestivum L.) production in various African countries. Growing resistant varieties is ...
Hybrid wheat prediction using genomic, pedigree, and environmental covariables interaction models
(Crop Science Society of America, 2019)
In this study, we used genotype × environment interactions (G×E) models for hybrid prediction, where similarity between lines was assessed by pedigree and molecular markers, and similarity between environments was accounted ...