Mostrando ítems 1-10 de 226
Indirect selection using reference and probe genotype performance in multi-environment trials
There is a substantial challenge in identifying appropriate cultivars from databases for introduction into a breeding program. We propose an indirect selection procedure that illustrates how strategically designed ...
Harnessing genetic potential of wheat germplasm banks through impact-oriented-prebreeding for future food and nutritional security
(Nature Publishing Group, 2018)
The value of exotic wheat genetic resources for accelerating grain yield gains is largely unproven and unrealized. We used next-generation sequencing, together with multi-environment phenotyping, to study the contribution ...
Genomic-enabled prediction Kernel models with random intercepts for multi-environment trials
(Genetics Society of America, 2018)
In this study, we compared the prediction accuracy of the main genotypic effect model (MM) without G×E interactions, the multi-environment single variance G×E deviation model (MDs), and the multienvironment environment-specific ...
Genome-wide association mapping for resistance to leaf rust, stripe rust and tan spot in wheat reveals potential candidate genes
Leaf rust (LR), stripe rust (YR) and tan spot (TS) are some of the important foliar diseases in wheat (Triticum aestivum L.). To identify candidate resistance genes for these diseases in CIMMYT’s (International Maize and ...
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: ...
Genomic-enabled prediction accuracies increased by modeling genotype × environment interaction in durum wheat
(Crop Science Society of America, 2018)
Genomic prediction studies incorporating genotype × environment (G×E) interaction effects are limited in durum wheat. We tested the genomic-enabled prediction accuracy (PA) of Genomic Best Linear Unbiased Predictor (GBLUP) ...
Genomic-enabled prediction based on molecular markers and pedigree using the Bayesian linear regression package in R
The availability of dense molecular markers has made possible the use of genomic selection in plant and animal breeding. However, models for genomic selection pose several computational and statistical challenges and require ...
Gains in maize genetic improvement in Eastern and Southern Africa : I. CIMMYT hybrid breeding pipeline
Monitoring of genetic gain in crop genetic improvement programs is necessary to measure the efficiency of the program. Periodic measurement of genetic gain also allows the efficiency of new technologies incorporated into ...
Wheat yield and tillage-straw management system year interaction explained by climatic co-variables for an irrigated bed planting system in northwestern Mexico
Wheat is an important food and income source and estimated demand for wheat in the developing world is projected to increase substantially. The objectives of this study were to gain insight into (i) the effect of tillage?straw ...