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Hybrid wheat prediction using genomic, pedigree, and environmental covariables interaction models

Author: Basnet, B.R.
Author: Crossa, J.
Author: Dreisigacker, S.
Author: Perez-Rodriguez, P.
Author: Yann Manes
Author: Singh, R.P.
Author: Rosyara, U.
Author: Camarillo-Castillo, F.
Author: Murua, M.
Year: 2019
ISSN: 1940-3372
ISSN: ISSN: 1940-3372
URI: https://hdl.handle.net/10883/19898
Abstract: In this study, we used genotype × environment interactions (G×E) models for hybrid prediction, where similarity between lines was assessed by pedigree and molecular markers, and similarity between environments was accounted for by environmental covariables. We use five genomic and pedigree models (M1–M5) under four cross-validation (CV) schemes: prediction of hybrids when the training set (i) includes hybrids of all males and females evaluated only in some environments (T2FM), (ii) excludes all progenies from a randomly selected male (T1M), (iii) includes all progenies from 20% randomly selected females in combination with all males (T1F), and (iv) includes one randomly selected male plus 40% randomly selected females that were crossed with it (T0FM). Models were tested on a total of 1888 wheat (Triticum aestivum L.) hybrids including 18 males and 667 females in three consecutive years. For grain yield, the most complex model (M5) under T2FM had slightly higher prediction accuracy than the less complex model. For T1F, the prediction accuracy of hybrids for grain yield and other traits of the most complete model was 0.50 to 0.55. For T1M, Model M3 exhibited high prediction accuracies for flowering traits (0.71), whereas the more complex model (M5) demonstrated high accuracy for grain yield (0.5). For T0FM, the prediction accuracy for grain yield of Model M5 was 0.61. Including genomic and pedigree gave relatively high prediction accuracy even when both parents were untested. Results show that it is possible to predict unobserved hybrids when modeling genomic general combining ability (GCA) and specific combining ability (SCA) and their interactions with environments.
Format: PDF
Language: English
Publisher: Crop Science Society of America
Copyright: CIMMYT manages Intellectual Assets as International Public Goods. The user is free to download, print, store and share this work. In case you want to translate or create any other derivative work and share or distribute such translation/derivative work, please contact CIMMYT-Knowledge-Center@cgiar.org indicating the work you want to use and the kind of use you intend; CIMMYT will contact you with the sutable license for that purpose.
Type: Article
Place of Publication: Madison, U.S.
Pages: art. 180051
Issue: 1
Volume: 12
DOI: 10.3835/plantgenome2018.07.0051
Keywords: Hybrid Prediction
Keywords: Pedigree
Keywords: Molecular Markers
Agrovoc: GENOTYPE ENVIRONMENT INTERACTION
Agrovoc: WHEAT
Agrovoc: HYBRIDS
Agrovoc: COMBINING ABILITY
Agrovoc: AGRICULTURAL SCIENCES AND BIOTECHNOLOGY
Agrovoc: GENETIC MARKERS
Agrovoc: PEDIGREE LIVESTOCK
Agrovoc: TRITICUM AESTIVUM
Related Datasets: http://hdl.handle.net/11529/10548129
Related Datasets: https://dl.sciencesocieties.org/publications/tpg/supplements/12/180051-supplement1.pdf
Journal: The Plant Genome


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  • Wheat
    Wheat - breeding, phytopathology, physiology, quality, biotech

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