Cargando…
Multi-Trait Genomic Prediction Models Enhance the Predictive Ability of Grain Trace Elements in Rice
Multi-trait (MT) genomic prediction models enable breeders to save phenotyping resources and increase the prediction accuracy of unobserved target traits by exploiting available information from non-target or auxiliary traits. Our study evaluated different MT models using 250 rice accessions from As...
Autores principales: | Muvunyi, Blaise Pascal, Zou, Wenli, Zhan, Junhui, He, Sang, Ye, Guoyou |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9257107/ https://www.ncbi.nlm.nih.gov/pubmed/35812754 http://dx.doi.org/10.3389/fgene.2022.883853 |
Ejemplares similares
-
Validation of Genes Affecting Rice Grain Zinc Content Through Candidate Gene-Based Association Analysis
por: Liu, Jindong, et al.
Publicado: (2021) -
Molecular mapping of QTLs for grain dimension traits in Basmati rice
por: Malik, Ankit, et al.
Publicado: (2022) -
Association mapping for yield and grain quality traits in rice (Oryza sativa L.)
por: de Oliveira Borba, Tereza Cristina, et al.
Publicado: (2010) -
Genomic Prediction of Yield Traits in Single-Cross Hybrid Rice (Oryza sativa L.)
por: Labroo, Marlee R., et al.
Publicado: (2021) -
Inquiring the inter-relationships amongst grain-filling, grain-yield, and grain-quality of Japonica rice at high latitudes of China
por: Farooq, Muhammad Shahbaz, et al.
Publicado: (2022)