Multispectral and thermal infrared data, visual scores for severity of common rust symptoms, and genotypic single nucleotide polymorphism data of three F2-derived biparental doubled-haploid maize populations.

Corn Disease resistance Genome-wide association study Genomic prediction High-throughput phenotyping Remote sensing Resistance breeding UAV Unmanned aerial vehicles

Journal

Data in brief
ISSN: 2352-3409
Titre abrégé: Data Brief
Pays: Netherlands
ID NLM: 101654995

Informations de publication

Date de publication:
Jun 2024
Historique:
received: 08 02 2024
revised: 01 03 2024
accepted: 04 03 2024
medline: 8 4 2024
pubmed: 8 4 2024
entrez: 8 4 2024
Statut: epublish

Résumé

Three F2-derived biparental doubled haploid (DH) maize populations were generated for genetic mapping of resistance to common rust. Each of the three populations has the same susceptible parent, but a different resistance donor parent. Population 1 and 3 consist of 320 lines each, population 2 consists of 260 lines. The DH lines were evaluated for their susceptibility to common rust in two years and with two replications in each year. For phenotyping, a visual score (VS) for susceptibility was assigned. Additionally, unmanned aerial vehicle (UAV) derived multispectral and thermal infrared data was recorded and combined in different vegetation indices ("remote sensing", RS). The DH lines were genotyped with the DarTseq method, to obtain data on single nucleotide polymorphisms (SNPs). After quality control, 9051 markers remained. Missing values were "imputed" by the empirical mean of the marker scores of the respective locus. We used the data for comparison of genome-wide association studies and genomic prediction when based on different phenotyping methods, that is either VS or RS data. The data may be interesting for reuse for instance for benchmarking genomic prediction models, for phytopathological studies addressing common rust, or for specifications of vegetation indices.

Identifiants

pubmed: 38586147
doi: 10.1016/j.dib.2024.110300
pii: S2352-3409(24)00269-5
pmc: PMC10997887
doi:

Types de publication

Journal Article

Langues

eng

Pagination

110300

Informations de copyright

© 2024 The Authors.

Auteurs

Alexander Loladze (A)

International Maize and Wheat Improvement Center - CIMMYT, Mexico.

Francelino Rodrigues (F)

International Maize and Wheat Improvement Center - CIMMYT, Mexico.

Cesar D Petroli (CD)

International Maize and Wheat Improvement Center - CIMMYT, Mexico.

Carlos Muñoz-Zavala (C)

International Maize and Wheat Improvement Center - CIMMYT, Mexico.

Sergio Naranjo (S)

International Maize and Wheat Improvement Center - CIMMYT, Mexico.

Felix San Vicente (FS)

International Maize and Wheat Improvement Center - CIMMYT, Mexico.

Bruno Gerard (B)

International Maize and Wheat Improvement Center - CIMMYT, Mexico.
College of Agriculture and Environmental Sciences (CAES), University Mohammed VI Polytechnic (UM6P), Ben Guerir, Morocco.

Osval A Montesinos-Lopez (OA)

Facultad de Telemática, Universidad de Colima, Colima, Mexico.

Jose Crossa (J)

International Maize and Wheat Improvement Center - CIMMYT, Mexico.

Johannes W R Martini (JWR)

International Maize and Wheat Improvement Center - CIMMYT, Mexico.

Classifications MeSH