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Replication Data for: A Bayesian Linear Phenotypic Selection Index to Predict the Net Genetic Merit

CIMMYT Research Data & Software Repository Network Dataverse OAI Archive

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Title Replication Data for: A Bayesian Linear Phenotypic Selection Index to Predict the Net Genetic Merit
 
Identifier https://hdl.handle.net/11529/10548567
 
Creator Cerón-Rojas, J. Jesus
Perez-Elizalde, Sergio
Crossa, Jose
Martini, Johannes Wolfgang Robert
 
Publisher CIMMYT Research Data & Software Repository Network
 
Description In breeding, the plant net genetic merit may be predicted through the linear phenotypic selection index (LPSI). This paper associated with this dataset proposes a Bayesian LPSI (BLPSI). The supplemental files provided in this dataset include data that were used to compare the two indices as well as figures showing the results from these comparisons. The analysis revealed that the BLPSI is a good option when carrying out phenotypic selections in breeding programs.
 
Subject Agricultural Sciences
Zea mays
Agricultural research
Maize
 
Language English
 
Date 2021
 
Contributor Dreher, Kate
United States Agency for International Development (USAID)
Bill and Melinda Gates Foundation (BMGF)
Foreign, Commonwealth and Development Office (FCDO)
Biometrics and Statistics Unit (BSU)
Genetic Resources Program (GRP)
Global Maize Program (GMP)
CGIAR Research Program on Maize (MAIZE)
CGIAR Research Program on Wheat (WHEAT)
Foundation for Research Levy on Agricultural Products (FFL)
Agricultural Agreement Research Fund (JA)
CGIAR
 
Type Phenotypic data
Genotypic data
Experimental data