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

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.

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Author Loladze, Alexander, Rodrigues, Francelino, Petroli, Cesar, Muñoz, Carlos, Macia Naranjo, Sergio, San Vicente, Felix, Gerard, Bruno, Montesinos-López, Osval A., Crossa, Jose, Martini, Johannes
Maintainer CIMMYT Research Data & Software Repository Network
Last Updated January 20, 2025, 16:22 (UTC)
Created January 20, 2025, 16:22 (UTC)
contributor Dreher, Kate
creator Loladze, Alexander
date 2023-04-20T00:00:00
harvest_object_id 0df170de-8bbe-4121-a1b4-9064799efea7
harvest_source_id a58b0729-e941-4389-816d-5823f01c0d28
harvest_source_title CIMMYT Research Data
identifier https://hdl.handle.net/11529/10548898
language English
metadata_modified 2024-10-26T07:00:04
set_spec cimmytdatadvn