Title
Replication Data for: Multi-generation genomic prediction of maize yield using parametric and non-parametric sparse selection indices
Author
Marco Lopez-Cruz
Yoseph Beyene
Manje Gowda
Jose Crossa
Paulino Pérez-Rodríguez
Gustavo de los Campos
Access level
Open Access
Description
Abstract - Genomic prediction models may be used in plant breeding pipelines. They are often calibrated using multi-generation data and there is an open question of whether all available data or a subset of it should be used to calibrate genomic prediction models. Therefore, a study was undertaken to determine whether combining sparse selection indexes (SSIs) and kernel methods could further improve prediction accuracy when training genomic models using multi-generation data. This dataset contains the genotypic and phenotypic data from CIMMYT maize doubled haploid lines that were used to perform the analyses. The results of the analyses are presented in the accompanying article.
Publisher
International Maize and Wheat Improvement Center
Publish date
2021
Resource Type
Dataset
Information Resource
Source repository
Repositorio Institucional de Datos y Software de Investigación del CIMMYT
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