Title
Replication Data for: Optimizing sparse testing for genomic prediction of plant breeding crops
Author
Osval Antonio Montesinos-Lopez
Carolina Saint Pierre
Brandon Alejandro Mosqueda González
Alison Bentley
Yoseph Beyene
Manje Gowda
Leonardo Abdiel Crespo Herrera
Jose Crossa
Access level
Open Access
Description
Abstract - 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.
Publisher
International Maize and Wheat Improvement Center
Publish date
2022
Resource Type
Dataset
Information Resource
Source repository
Repositorio Institucional de Datos y Software de Investigación del CIMMYT
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