Hybrid Breeding for MLN Resistance: Heterosis, Combining Ability, and Hybrid Prediction.

combining ability genomic prediction heterosis maize lethal necrosis resistance

Journal

Plants (Basel, Switzerland)
ISSN: 2223-7747
Titre abrégé: Plants (Basel)
Pays: Switzerland
ID NLM: 101596181

Informations de publication

Date de publication:
08 Apr 2020
Historique:
received: 20 02 2020
revised: 24 03 2020
accepted: 25 03 2020
entrez: 12 4 2020
pubmed: 12 4 2020
medline: 12 4 2020
Statut: epublish

Résumé

Prior knowledge on heterosis and quantitative genetic parameters on maize lethal necrosis (MLN) can help the breeders to develop numerous resistant or tolerant hybrids with optimum resources. Our objectives were to (1) estimate the quantitative genetic parameters for MLN disease severity, (2) investigate the efficiency of the prediction of hybrid performance based on parental

Identifiants

pubmed: 32276322
pii: plants9040468
doi: 10.3390/plants9040468
pmc: PMC7238107
pii:
doi:

Types de publication

Journal Article

Langues

eng

Subventions

Organisme : Bill and Melinda Gates Foundation
ID : OPP1134248

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Auteurs

Christine Nyaga (C)

Department of Agricultural Science and Technology, Kenyatta University, Nairobi 43844-00100, Kenya.
International Maize and Wheat Improvement Centre (CIMMYT), World Agroforestry Centre (ICRAF), United Nations Avenue, Gigiri, Nairobi 1041-00621, Kenya.

Manje Gowda (M)

International Maize and Wheat Improvement Centre (CIMMYT), World Agroforestry Centre (ICRAF), United Nations Avenue, Gigiri, Nairobi 1041-00621, Kenya.

Yoseph Beyene (Y)

International Maize and Wheat Improvement Centre (CIMMYT), World Agroforestry Centre (ICRAF), United Nations Avenue, Gigiri, Nairobi 1041-00621, Kenya.

Wilson T Murithi (WT)

Department of Agricultural Science and Technology, Kenyatta University, Nairobi 43844-00100, Kenya.

Juan Burgueno (J)

Biometrics and Statistics Unit, International Maize and Wheat Improvement Center (CIMMYT), CarreteraMexico-Veracruz Km. 45, El Batán, Texcoco Estado de Mexico 56237, Mexico.

Fernando Toledo (F)

Biometrics and Statistics Unit, International Maize and Wheat Improvement Center (CIMMYT), CarreteraMexico-Veracruz Km. 45, El Batán, Texcoco Estado de Mexico 56237, Mexico.

Dan Makumbi (D)

International Maize and Wheat Improvement Centre (CIMMYT), World Agroforestry Centre (ICRAF), United Nations Avenue, Gigiri, Nairobi 1041-00621, Kenya.

Michael S Olsen (MS)

International Maize and Wheat Improvement Centre (CIMMYT), World Agroforestry Centre (ICRAF), United Nations Avenue, Gigiri, Nairobi 1041-00621, Kenya.

Biswanath Das (B)

International Maize and Wheat Improvement Centre (CIMMYT), World Agroforestry Centre (ICRAF), United Nations Avenue, Gigiri, Nairobi 1041-00621, Kenya.

Suresh L M (S)

International Maize and Wheat Improvement Centre (CIMMYT), World Agroforestry Centre (ICRAF), United Nations Avenue, Gigiri, Nairobi 1041-00621, Kenya.

Jumbo M Bright (JM)

International Maize and Wheat Improvement Centre (CIMMYT), World Agroforestry Centre (ICRAF), United Nations Avenue, Gigiri, Nairobi 1041-00621, Kenya.

Boddupalli M Prasanna (BM)

International Maize and Wheat Improvement Centre (CIMMYT), World Agroforestry Centre (ICRAF), United Nations Avenue, Gigiri, Nairobi 1041-00621, Kenya.

Classifications MeSH