Stochastic simulation to optimize rice breeding at IRRI

Genetic 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...

Descripción completa

Detalles Bibliográficos
Autores principales: Seck, Fallou, Prakash, Parthiban Thathapalli, Covarrubias-Pazaran, Giovanny, Gueye, Tala, Diédhiou, Ibrahima, Bhosale, Sankalp, Kadaru, Suresh, Bartholomé, Jerome
Formato: Journal Article
Lenguaje:Inglés
Publicado: Frontiers Media 2024
Materias:
Acceso en línea:https://hdl.handle.net/10568/168822
_version_ 1855521868574883840
author Seck, Fallou
Prakash, Parthiban Thathapalli
Covarrubias-Pazaran, Giovanny
Gueye, Tala
Diédhiou, Ibrahima
Bhosale, Sankalp
Kadaru, Suresh
Bartholomé, Jerome
author_browse Bartholomé, Jerome
Bhosale, Sankalp
Covarrubias-Pazaran, Giovanny
Diédhiou, Ibrahima
Gueye, Tala
Kadaru, Suresh
Prakash, Parthiban Thathapalli
Seck, Fallou
author_facet Seck, Fallou
Prakash, Parthiban Thathapalli
Covarrubias-Pazaran, Giovanny
Gueye, Tala
Diédhiou, Ibrahima
Bhosale, Sankalp
Kadaru, Suresh
Bartholomé, Jerome
author_sort Seck, Fallou
collection Repository of Agricultural Research Outputs (CGSpace)
description Genetic 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.
format Journal Article
id CGSpace168822
institution CGIAR Consortium
language Inglés
publishDate 2024
publishDateRange 2024
publishDateSort 2024
publisher Frontiers Media
publisherStr Frontiers Media
record_format dspace
spelling CGSpace1688222025-12-08T10:29:22Z Stochastic simulation to optimize rice breeding at IRRI Seck, Fallou Prakash, Parthiban Thathapalli Covarrubias-Pazaran, Giovanny Gueye, Tala Diédhiou, Ibrahima Bhosale, Sankalp Kadaru, Suresh Bartholomé, Jerome rice plant breeding optimization methods Genetic 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. 2024-11-01 2025-01-10T07:13:53Z 2025-01-10T07:13:53Z Journal Article https://hdl.handle.net/10568/168822 en Open Access application/pdf Frontiers Media Seck, 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: 1664-462X
spellingShingle rice
plant breeding
optimization methods
Seck, Fallou
Prakash, Parthiban Thathapalli
Covarrubias-Pazaran, Giovanny
Gueye, Tala
Diédhiou, Ibrahima
Bhosale, Sankalp
Kadaru, Suresh
Bartholomé, Jerome
Stochastic simulation to optimize rice breeding at IRRI
title Stochastic simulation to optimize rice breeding at IRRI
title_full Stochastic simulation to optimize rice breeding at IRRI
title_fullStr Stochastic simulation to optimize rice breeding at IRRI
title_full_unstemmed Stochastic simulation to optimize rice breeding at IRRI
title_short Stochastic simulation to optimize rice breeding at IRRI
title_sort stochastic simulation to optimize rice breeding at irri
topic rice
plant breeding
optimization methods
url https://hdl.handle.net/10568/168822
work_keys_str_mv AT seckfallou stochasticsimulationtooptimizericebreedingatirri
AT prakashparthibanthathapalli stochasticsimulationtooptimizericebreedingatirri
AT covarrubiaspazarangiovanny stochasticsimulationtooptimizericebreedingatirri
AT gueyetala stochasticsimulationtooptimizericebreedingatirri
AT diedhiouibrahima stochasticsimulationtooptimizericebreedingatirri
AT bhosalesankalp stochasticsimulationtooptimizericebreedingatirri
AT kadarusuresh stochasticsimulationtooptimizericebreedingatirri
AT bartholomejerome stochasticsimulationtooptimizericebreedingatirri