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.

Bibliographic Details

Main Authors:	Loladze, Alexander, Rodrigues, Francelino, Petroli, Cesar, Muñoz, Carlos, Macia Naranjo, Sergio, San Vicente, Felix, Gerard, Bruno, Montesinos-López, Osval A., Crossa, Jose, Martini, Johannes
Other Authors:	Dreher, Kate
Format:	Experimental data biblioteca
Language:	English
Published:	CIMMYT Research Data & Software Repository Network 2023
Subjects:	Agricultural Sciences, Maize, Agricultural research, Remote sensing, Vegetation indices, Common Rust Severity, Zea mays, Plant Breeding,
Online Access:	https://hdl.handle.net/11529/10548898
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