Cargando…
Early prediction of biomass in hybrid rye based on hyperspectral data surpasses genomic predictability in less-related breeding material
KEY MESSAGE: Hyperspectral data is a promising complement to genomic data to predict biomass under scenarios of low genetic relatedness. Sufficient environmental connectivity between data used for model training and validation is required. ABSTRACT: The demand for sustainable sources of biomass is i...
Autores principales: | Galán, Rodrigo José, Bernal-Vasquez, Angela-Maria, Jebsen, Christian, Piepho, Hans-Peter, Thorwarth, Patrick, Steffan, Philipp, Gordillo, Andres, Miedaner, Thomas |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8081675/ https://www.ncbi.nlm.nih.gov/pubmed/33630103 http://dx.doi.org/10.1007/s00122-021-03779-1 |
Ejemplares similares
-
Integration of genotypic, hyperspectral, and phenotypic data to improve biomass yield prediction in hybrid rye
por: Galán, Rodrigo José, et al.
Publicado: (2020) -
Genomic prediction in early selection stages using multi-year data in a hybrid rye breeding program
por: Bernal-Vasquez, Angela-Maria, et al.
Publicado: (2017) -
Studying Stem Rust and Leaf Rust Resistances of Self-Fertile Rye Breeding Populations
por: Gruner, Paul, et al.
Publicado: (2022) -
The accuracy of prediction of genomic selection in elite hybrid rye populations surpasses the accuracy of marker-assisted selection and is equally augmented by multiple field evaluation locations and test years
por: Wang, Yu, et al.
Publicado: (2014) -
Model training across multiple breeding cycles significantly improves genomic prediction accuracy in rye (Secale cereale L.)
por: Auinger, Hans-Jürgen, et al.
Publicado: (2016)