Record Details

New deep learning genomic prediction model for multi-traits with mixed binary, ordinal, and continuous phenotypes

CIMMYT Research Data & Software Repository Network Dataverse OAI Archive

View Archive Info
 
 
Field Value
 
Title New deep learning genomic prediction model for multi-traits with mixed binary, ordinal, and continuous phenotypes
 
Identifier https://hdl.handle.net/11529/10548140
 
Creator Montesinos-López, Osval A.
Martín-Vallejo, Javier
Crossa, Jose
Gianola, Daniel
Hernández-Suarez, Carlos Moisés
Montesinos-López, Abelardo
Juliana, Philomin
Singh, Ravi
 
Publisher CIMMYT Research Data & Software Repository Network
 
Description The seven data sets are wheat data from CIMMYT Global Wheat Breeding program. They comprise different traits, like days to heading, days to maturity, grain yield, grain color, different type of leaf and stripe rust in wheat. Also the trials were run in different environments.
 
Subject Agricultural Sciences
Agricultural research
Wheat
Days to heading
Days to maturity
Grain yield
Grain color
Genomic selection
Deep learning
Plant breeding
Multi-trait
Mixed phenotypes
 
Language English
 
Date 2018
 
Contributor Shrestha, Rosemary
Global Wheat Program (GWP)
Genetic Resources Program (GRP)
Biometrics and Statistics Unit (BSU)
CGIAR Research Program on Wheat (WHEAT)
CGIAR
 
Type Experimental data