| People | Locations | Statistics |
|---|---|---|
| Naji, M. |
| |
| Motta, Antonella |
| |
| Aletan, Dirar |
| |
| Mohamed, Tarek |
| |
| Ertürk, Emre |
| |
| Taccardi, Nicola |
| |
| Kononenko, Denys |
| |
| Petrov, R. H. | Madrid |
|
| Alshaaer, Mazen | Brussels |
|
| Bih, L. |
| |
| Casati, R. |
| |
| Muller, Hermance |
| |
| Kočí, Jan | Prague |
|
| Šuljagić, Marija |
| |
| Kalteremidou, Kalliopi-Artemi | Brussels |
|
| Azam, Siraj |
| |
| Ospanova, Alyiya |
| |
| Blanpain, Bart |
| |
| Ali, M. A. |
| |
| Popa, V. |
| |
| Rančić, M. |
| |
| Ollier, Nadège |
| |
| Azevedo, Nuno Monteiro |
| |
| Landes, Michael |
| |
| Rignanese, Gian-Marco |
|
Li, Li
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (24/24 displayed)
- 2023Large-area epitaxial growth of InAs nanowires and thin films on hexagonal boron nitride by metal organic chemical vapor depositioncitations
- 2023First-Ply Failure Analysis of Helicoidal/Bouligand Bio-Inspired Laminated Composite Platescitations
- 2022Tuning the crystal structure and optical properties of selective area grown InGaAs nanowirescitations
- 2022Effective Passivation of InGaAs Nanowires for Telecommunication Wavelength Optoelectronicscitations
- 2021Tuning the crystal structure and optical properties of selective area grown InGaAs nanowires
- 2021Multivariate genomic analysis and optimal contributions selection predicts high genetic gains in cooking time, iron, zinc, and grain yield in common beans in East Africacitations
- 2021Passivation of InP solar cells using large area hexagonal-BN layerscitations
- 2019Damage analysis of a perfect broadband absorber by a femtosecond lasercitations
- 2018Tungsten Refractory Plasmonic Material for High Fluence Bowtie Nano-antenna
- 2018Impurity Gettering by Diffusion-doped Polysilicon Passivating Contacts for Silicon Solar Cellscitations
- 2017Imaging of doped iron pnictides across a structural phase transition
- 2017Void evolution and porosity under arsenic ion irradiation in GaAs1-xSbx alloyscitations
- 2016Cluster analysis of acoustic emission signals for 2D and 3D woven carbon fiber/epoxy compositescitations
- 2016Shear-Coupled Grain Growth and Texture Development in a Nanocrystalline Ni-Fe Alloy during Cold Rollingcitations
- 2015Identification of the damage in woven composites based on acoustic emission cluster analysis
- 2014Encapsulated <scp>PDMS</scp> Microspheres with Reactive Handlescitations
- 2013On the mechanical effects of a nanocrystallisation treatment for ZrO2 oxide films growing on a zirconium alloycitations
- 2013Reversible loss of bernal stacking during the deformation of few-layer graphene in nanocompositescitations
- 2012Experimental and numerical study of the effects of a nanocrystallisation treatment on high-temperature oxidation of a zirconium alloycitations
- 2011Work softening in nanocrystalline materials induced by dislocation annihilationcitations
- 2011Ultrafiltration by gyroid nanoporous polymer membranescitations
- 2010Hydrophilic nanoporous materials
- 2008Plastic behavior of a nickel-based alloy under monotonic-tension and low-cycle-fatigue loadingcitations
- 2007Anion selectivity in zwitterionic amide-funtionalised metal salt extractantscitations
Places of action
| Organizations | Location | People |
|---|
article
Multivariate genomic analysis and optimal contributions selection predicts high genetic gains in cooking time, iron, zinc, and grain yield in common beans in East Africa
Abstract
<p>Common bean (Phaseolus vulgaris L.) is important in African diets for protein, iron (Fe), and zinc (Zn), but traditional cultivars have long cooking time (CKT), which increases the time, energy, and health costs of cooking. Genomic selection was used to predict genomic estimated breeding values (GEBV) for grain yield (GY), CKT, Fe, and Zn in an African bean panel of 358 genotypes in a two-stage analysis. In Stage 1, best linear unbiased estimates (BLUE) for each trait were obtained from 898 genotypes across 33 field trials in East Africa. In Stage 2, BLUE in a training population of 141 genotypes were used in a multivariate genomic analysis with genome-wide single nucleotide polymorphism data from the African bean panel. Moderate to high genomic heritability was found for GY (0.45 ± 0.10), CKT (0.50 ± 0.15), Fe (0.57 ± 0.12), and Zn (0.61 ± 0.13). There were significant favorable genetic correlations between Fe and Zn (0.91 ± 0.06), GY and Fe (0.66 ± 0.17), GY and Zn (0.44 ± 0.19), CKT and Fe (−0.57 ± 0.21), and CKT and Zn (−0.67 ± 0.20). Optimal contributions selection (OCS), based on economic index of weighted GEBV for each trait, was used to design crossing within four market groups relevant to East Africa. Progeny were predicted by OCS to increase in mean GY by 12.4%, decrease in mean CKT by 9.3%, and increase in mean Fe and Zn content by 6.9 and 4.6%, respectively, with low achieved coancestry of 0.032. Genomic selection with OCS will accelerate breeding of high-yielding, biofortified, and rapid cooking African common bean cultivars.</p>