Claim · model-written summary
Each QTL explained 5.3% to 25.6% of the phenotypic variation of EPP.
Zea maysNot reportedMaterialGeneCompoundOrgan / stageInteractorInteractor roleSecond interactorSecond interactor roleTreatmentComparatorSettingDirectionQualifier
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“Maize(Zea mays L.)”
e3“could explain 5.3% to 25.6% phenotypic variation of EPP”
Title
QTL Analysis of Yield Components in Maize under Different Environments
Lan Jin; Xin Li; Gao Shu; et al. 2005
Other claims from this paper (13)
- Observation 47 QTL were identified for five yield-related traits, located on nine chromosomes but not chromosome 10.
- Observation 10 QTL were detected for ears per plant (EPP).
- Observation 13 QTL were detected for row number per ear (RN).
- Observation 9 QTL were detected for kernel number per row (KR).
- Observation 10 QTL were detected for 100-kernel weight (KW).
- Observation 5 QTL were detected for grain yield per plant (GY).
- Observation Each QTL explained (4.5%) to 23.2% of the phenotypic variation of row number per ear (RN).
- Observation Each QTL explained 5.4% to 13.7% of the phenotypic variation of kernel number per row (KR).
- Observation Each QTL explained 4.9% to 13.3% of the phenotypic variation of 100-kernel weight (KW).
- Observation Each QTL explained 6.1% to 35.8% of the phenotypic variation of grain yield per plant (GY).
- Observation Most QTL were detected in a single environment, indicating significant QTL-by-environment interactions.
- Observation Several regions with clustered QTL for multiple yield components may provide the genetic loci of a universal yield QTL.
- Observation QTL relevant to phenotypically correlated yield components can be identified in the same or adjacent chromosome regions.