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Replication Data for: Use of Remote Sensing for Genome-Wide Association Studies and Genomic Prediction

CIMMYT Research Data & Software Repository Network Dataverse OAI Archive

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Title Replication Data for: Use of Remote Sensing for Genome-Wide Association Studies and Genomic Prediction
 
Identifier https://hdl.handle.net/11529/10548898
 
Creator Loladze, Alexander
Rodrigues, Francelino
Petroli, Cesar
Muñoz, Carlos
Macia Naranjo, Sergio
San Vicente, Felix
Gerard, Bruno
Montesinos-López, Osval A.
Crossa, Jose
Martini, Johannes
 
Publisher CIMMYT Research Data & Software Repository Network
 
Description Disease resistance improvement efforts in plant breeding can help to reduce the negative impact of biotic stresses on crop production.Disease resistance can be assessed through a labor-intensive process of assigning visual scores
(VS) of susceptibility (or resistance) by specially trained staff. Remote sensing (RS) tools can also be used to measure traits such as vegetation indices that can also be used to assess plant responses to diseases. This dataset contains phenotypic and genotypic data from a two-year evaluation trial of three newly
developed biparental populations of maize doubled haploid lines (DH). Data from VS and RS methods for assessing common rust resistance were used in genome wide association study (GWAS) as well as genomic prediction (GP) analyses. A report on the comparison of the results of these analyses is provided in the accompanying article.
 
Subject Agricultural Sciences
Maize
Agricultural research
Remote sensing
Vegetation indices
Common Rust Severity
Zea mays
Plant Breeding
 
Language English
 
Date 2023
 
Contributor Dreher, Kate
CGIAR
CGIAR Research Program on Maize (MAIZE)
Global Maize Program (GMP)
Sustainable Intensification Program (SIP)
Biometrics and Statistics Unit (BSU)
Genetic Resources Program (GRP)
Bill and Melinda Gates Foundation (BMGF)
 
Type Experimental data
Genotypic data
Phenotypic data