Claim · model-written summary
Bayesian analyses provide robust inference of genetic parameters.
- Outcome
- robust inference of genetic parameterse7
Not reportedTaxonMaterialGeneCompoundOrgan / stageInteractorInteractor roleSecond interactorSecond interactor roleTreatmentComparatorSettingDirectionValueQualifier
Verbatim
e7“Bayesian analyzes provide robust inference of genetic parameters”
Title
Antônio Carlos da Silva Júnior; Isabela de Castro Sant’Anna; Michele Jorge Silva Siqueira; et al. PLoS ONE 2022. doi:10.1371/journal.pone.0259607
Other claims from this paper (10)
- Observation Flowering heritability in environment 1 was high, with a Bayesian credibility interval of 0.039-0.80.
- Observation Flowering heritability in the second environment was high, with a Bayesian credibility interval of 0.02-0.91.
- Observation The genetic correlation between traits was significantly different from zero in environment 1, ranging from -0.80 to 0.74.
- Observation The genetic correlation between traits was significantly different from zero in environment 2, ranging from -0.82 to 0.86.
- Observation The CVg/CVe relationship for flowering was higher in the reduced model, 5.83 in environment 1.
- Observation The CVg/CVe relationship for flowering was higher in the reduced model, 13.98 in environment 2.
- Observation The relative variation index for flowering in the complete model was 4.28 in environment 1.
- Observation The relative variation index for flowering in the complete model was 4.21 in environment 2.
- Recommendation The multi-trait multi-environment Bayesian model is recommended for genetic evaluation of flood-irrigated rice genotypes.
- Method / resource The Bayesian model gave a reliable estimate of genetic parameters of flood-irrigated rice.