Claim · model-written summary
In limited conditions CV2 sampling is the most appropriate for genomic predictions with multi-environment models.
Not reportedMaterialGeneCompoundOrgan / stageInteractorInteractor roleSecond interactorSecond interactor roleTreatmentComparatorSettingDirectionValueQualifier
Verbatim
t0“tomate”
e0“In limited conditions, CV2 sampling is the most appropriate to make genomic predictions with multi-environment models”
Title
Ange Fouabi HAL (Le Centre pour la Communication Scientifique Directe) 2020
Other claims from this paper (5)
- Method / resource Multi-environment models had better prediction accuracy than the single environment model.
- Method / resource The GxE model had prediction accuracy as high as G+E and better than G+E depending on the environment or training population composition.
- Method / resource Both multi-environment models had higher prediction accuracy than the single environment model when accessions were tested in at least one environment (CV2) rather than in none (CV1).
- Association Prediction accuracy was strongly correlated with trait heritability and increased when the environments were correlated with each other.
- Intervention effect Integrating environmental co-factors in the GxE model improved prediction accuracy.