Show simple item record

dc.contributor.authorBakare, M.A.
dc.contributor.authorKayondo, S.I.
dc.contributor.authorKulakow, P.
dc.contributor.authorRabbi, I.Y.
dc.contributor.authorJannink, J.L.
dc.date.accessioned2024-03-14T08:06:23Z
dc.date.available2024-03-14T08:06:23Z
dc.date.issued2024
dc.identifier.citationBakare, M.A., Kayondo, S.I., Kulakow, P., Rabbi, I.Y. & Jannink, J.L. (2024). Evaluating breeding for broad versus narrow adaptation for cassava in Nigeria using stochastic simulation. Crop Science, 1-14.
dc.identifier.issn0011-183X
dc.identifier.urihttps://hdl.handle.net/20.500.12478/8437
dc.description.abstractThe cassava (Manihot esculenta Crantz) breeding program at the International Institute of Tropical Agriculture (IITA) has adopted genomic selection to accelerate genetic gain. The program continues to develop varieties broadly adapted across Nigeria’s diverse agroclimatic zones. However, genotype by- environment interaction (GEI) presents a challenge for this purpose. To decide whether broad adaptation breeding is a good strategy, we evaluated broad versus narrow adaptation strategies using stochastic simulation, assessing genetic gain, genetic variance, heritability, and selection accuracy at 0 versus realistic levels of GEI variance. To parameterize the models, we analyzed historical data from four phenotypic evaluation stages of the IITA breeding program to estimate genetic and error variances, and genetic correlations across environments. Based on these observed parameters, the genomic-enabled breeding programs exhibited higher genetic gain than the conventional program for both GEI variances. At realistic GEI variance, the narrow adaptation program showed higher genetic gain than the broad adaptation program. Across all programs, the genetic variance declined over time, though the genomic-enabled programs showed higher initial variance due to the selection of parents at earlier stages. At realistic GEI variance, an increase in genetic variance was observed in the narrow adaptation program due to its conversion of GEI between mega-environments into main genetic variance within mega-environments. This higher genetic variance led to higher heritabilities and selection accuracies. This study highlights the potential of genomic selection in accelerating genetic gain and suggests that dividing the IITA cassava breeding program to target more than one mega-environment should be considered.
dc.description.sponsorshipForeign, Commonwealth and Development Office, United Kingdom
dc.description.sponsorshipBill & Melinda Gates Foundation
dc.format.extent1-14
dc.language.isoen
dc.subjectCassava
dc.subjectBreeding
dc.subjectGenomics
dc.subjectGenotypes
dc.titleEvaluating breeding for broad versus narrow adaptation for cassava in Nigeria using stochastic simulation
dc.typeJournal Article
cg.contributor.crpRoots, Tubers and Bananas
cg.contributor.affiliationCornell University
cg.contributor.affiliationInternational Institute of Tropical Agriculture
cg.coverage.regionAfrica
cg.coverage.regionWest Africa
cg.coverage.countryNigeria
cg.coverage.hubHeadquarters and Western Africa Hub
cg.researchthemeBiotech and Plant Breeding
cg.identifier.bibtexciteidBAKARE:2024
cg.isijournalISI Journal
cg.authorship.typesCGIAR and advanced research institute
cg.iitasubjectAgronomy
cg.iitasubjectCassava
cg.iitasubjectFood Security
cg.iitasubjectGenetic Improvement
cg.iitasubjectPlant Breeding
cg.iitasubjectPlant Production
cg.journalCrop Science
cg.notesOpen Access Article
cg.accessibilitystatusOpen Access
cg.reviewstatusPeer Review
cg.usagerightslicenseCreative Commons Attribution 4.0 (CC BY 0.0)
cg.targetaudienceScientists
cg.identifier.doihttps://doi.org/10.1002/csc2.21170
cg.iitaauthor.identifierMoshood Agba Bakare: 0000-0003-1910-8233
cg.iitaauthor.identifierKayondo Siraj Ismail: 0000-0002-3212-5727
cg.iitaauthor.identifierPeter Kulakow: 0000-0002-7574-2645
cg.iitaauthor.identifierIsmail Rabbi: 0000-0001-9966-2941
cg.futureupdate.requiredNo


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record