Genomic-enabled prediction models using multi-environment trials to estimate the effect of genotype...
Genomic-enabled prediction models using multi-environment trials to estimate the effect of genotype × environment interaction on prediction accuracy in chickpea
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Author / Creator
Roorkiwal, Manish , Jarquin, Diego , Singh, Muneendra K. , Gaur, Pooran M. , Bharadwaj, Chellapilla , Rathore, Abhishek , Howard, Reka , Srinivasan, Samineni , Jain, Ankit , Garg, Vanika , Kale, Sandip , Chitikineni, Annapurna , Tripathi, Shailesh , Jones, Elizabeth , Robbins, Kelly R. , Crossa, Jose and Varshney, Rajeev K.
Publisher
London: Nature Publishing Group UK
Journal title
Language
English
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Publication information
Publisher
London: Nature Publishing Group UK
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Scope and Contents
Contents
Genomic selection (GS) by selecting lines prior to field phenotyping using genotyping data has the potential to enhance the rate of genetic gains. Genotype × environment (G × E) interaction inclusion in GS models can improve prediction accuracy hence aid in selection of lines across target environments. Phenotypic data on 320 chickpea breeding line...
Alternative Titles
Full title
Genomic-enabled prediction models using multi-environment trials to estimate the effect of genotype × environment interaction on prediction accuracy in chickpea
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Record Identifier
TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_6076323
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_6076323
Other Identifiers
ISSN
2045-2322
E-ISSN
2045-2322
DOI
10.1038/s41598-018-30027-2
