Título
Replication Data for: Optimizing sparse testing for genomic prediction of plant breeding crops
Autor
Osval Antonio Montesinos-Lopez
Carolina Saint Pierre
Brandon Alejandro Mosqueda González
Alison Bentley
Yoseph Beyene
Manje Gowda
Leonardo Abdiel Crespo Herrera
Jose Crossa
Nivel de Acceso
Acceso Abierto
Descripción
Abstracto - In plant breeding, sparse testing methods have been suggested to improve the efficiency of the genomic selection methodology. The data provided in this dataset were used to evaluate four methods for allocating lines to environments for sparse testing in multi-environment trials. The analysis was conducted using a multi-trait and uni-trait framework. The accompanying article describes the results of the evaluation as well as a cost-benefit analysis to identify the benefits that can be obtained using sparse testing methods.
Editor
International Maize and Wheat Improvement Center
Fecha de publicación
2022
Tipo de recurso
Dataset
Recurso de información
Repositorio Orígen
Repositorio Institucional de Datos y Software de Investigación del CIMMYT
Descargas
0