Stochastic simulation to optimize rice breeding at IRRI

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cg.authorship.typesCGIAR and developing country instituteen_US
cg.contributor.affiliationInternational Center for Tropical Agricultureen_US
cg.contributor.affiliationInternational Rice Research Instituteen_US
cg.contributor.affiliationÉcole Nationale Supérieure Agronomiqueen_US
cg.contributor.donorInternational Center for Tropical Agricultureen_US
cg.contributor.donorInternational Rice Research Instituteen_US
cg.contributor.donorÉcole Nationale Supérieure d'Agricultureen_US
cg.contributor.donorCGIAR Trust Funden_US
cg.contributor.initiativeAccelerated Breedingen_US
cg.creator.identifierParthiban Thathapalli Prakash: 0000-0002-4539-140Xen_US
cg.creator.identifierGIOVANNY COVARRUBIAS-PAZARAN: 0000-0002-7194-3837en_US
cg.creator.identifierIbrahima DIEDHIOU: 0000-0002-2065-4381en_US
cg.creator.identifierJérôme Bartholomé: 0000-0002-0855-3828en_US
cg.identifier.doihttps://doi.org/10.3389/fpls.2024.1488814en_US
cg.isijournalISI Journalen_US
cg.issn1664-462Xen_US
cg.journalFrontiers in Plant Scienceen_US
cg.reviewStatusPeer Reviewen_US
cg.subject.actionAreaGenetic Innovationen_US
cg.subject.alliancebiovciatPLANT BREEDINGen_US
cg.subject.alliancebiovciatRICEen_US
cg.subject.impactAreaEnvironmental health and biodiversityen_US
cg.subject.sdgSDG 2 - Zero hungeren_US
cg.subject.sdgSDG 13 - Climate actionen_US
cg.volume15en_US
dc.contributor.authorSeck, Fallouen_US
dc.contributor.authorPrakash, Parthiban Thathapallien_US
dc.contributor.authorCovarrubias-Pazaran, Giovannyen_US
dc.contributor.authorGueye, Talaen_US
dc.contributor.authorDiédhiou, Ibrahimaen_US
dc.contributor.authorBhosale, Sankalpen_US
dc.contributor.authorKadaru, Sureshen_US
dc.contributor.authorBartholomé, Jeromeen_US
dc.date.accessioned2025-01-10T07:13:53Zen_US
dc.date.available2025-01-10T07:13:53Zen_US
dc.identifier.urihttps://hdl.handle.net/10568/168822en_US
dc.titleStochastic simulation to optimize rice breeding at IRRIen_US
dcterms.abstractGenetic improvement in rice increased yield potential and improved varieties for farmers over the last decades. However, the demand for rice is growing while its cultivation faces challenges posed by climate change. To address these challenges, rice breeding programs need to adopt efficient breeding strategies to provide a steady increase in the rate of genetic gain for major traits. The International Rice Research Institute (IRRI) breeding program has evolved over time to implement faster and more efficient breeding techniques such as rapid generation advance (RGA) and genomic selection (GS). Simulation experiments support data-driven optimization of the breeding program toward the desired rate of genetic gain for key traits.en_US
dcterms.accessRightsOpen Accessen_US
dcterms.available2024-11-01en_US
dcterms.bibliographicCitationSeck, F.; Prakash, P.T.; Covarrubias-Pazaran, G.; Gueye, T.; Diédhiou, I.; Bhosale, S.; Kadaru, S.; Bartholomé, J.. (2024) Stochastic simulation to optimize rice breeding at IRRI. Frontiers in Plant Science 15: 1488814. ISSN: 1664-462Xen_US
dcterms.extent1488814en_US
dcterms.issued2024-11-01en_US
dcterms.languageenen_US
dcterms.licenseCC-BY-4.0en_US
dcterms.publisherFrontiers Mediaen_US
dcterms.subjectriceen_US
dcterms.subjectplant breedingen_US
dcterms.subjectoptimization methodsen_US
dcterms.typeJournal Articleen_US

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Alliance Research Lever 6: Crops for Nutrition and Health
CGIAR Initiative on Accelerated Breeding
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