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Grain yield stability of soybean (Glycine Max (L.) Merrill) for different stability models across diverse environments of Ethiopia

dc.contributor.authorHabtegebriel, M.H.
dc.contributor.authorAbebe, A.T.
dc.date.accessioned2026-09-02T07:40:32Z
dc.date.available2026-09-02T07:40:32Z
dc.date.issued2023-09
dc.identifier.citationHabtegebriel, M.H. & Abebe, A.T. (2023). Grain yield stability of soybean (Glycine Max (L.) Merrill) for different stability models across diverse environments of Ethiopia. Agrosystems, Geosciences & Environment, 6(3): e20396, 1-19.
dc.identifier.issn2639-6696
dc.identifier.urihttps://hdl.handle.net/20.500.12478/8686
dc.description.abstractFor grain yield stability analysis, genotype by environment interactions are crucial in properly identifying and discriminating between varieties and locations. Hence, this experiment was conducted with the objectives to evaluate the stability of soybean using additive main effects and multiplicative interaction (AMMI), multi-trait stability index (MTSI), weighted average absolute scores biplot (WAASB), Eberhart and Russell regression model, and genotype plus genotype by environment interaction (GGE) biplot analysis for grain yield of soybean genotypes and identified stable genotypes in the different soybean agroecologies of Ethiopia. Twenty-four soybean genotypes were planted at six soybean environments with RCBD in three replications in the 2015/2016 cropping season. Stability measures, namely, AMMI, AMMI stability value, and GGE biplot analysis were used to identify the high-yielding and stable genotypes across the testing environments. AMMI-1 biplot showed Pawe as the ideal environment; Bako as a favorable environment; Asosa an average environment; and the rest namely, Dimtu, Jimma, and Metu as unfavorable environments. On the other hand, AMMI-2 biplot analysis certain genotypes like Prichard, Spry, Delsoy 4710, and Croton 3.9 were identified as stable genotypes. Bako and Metu were identified as the most discriminating environments. Mega environments and the best yielding soybean genotypes on each mega environment were revealed by the GGE biplot analysis model. For other multivariate statistics used for this study, MTSI, WAASB, and regression models, stable and superior varieties for grain yield were revealed. Through the MTSI, the four genotypes, namely, Liu yue mang, SCS-1, Clarck-63k, and AFGAT, were found to be stable and superior over the rest tested genotypes. Overall, the genotypes SCS-1 and AGS-7-1 were stable across soybean growing environments and are recommended for mega environment production.
dc.format.extent1-19
dc.language.isoen
dc.subjectGrain Legumes
dc.subjectSoybeans
dc.subjectGenotypes
dc.subjectValue Chain
dc.subjectEthiopia
dc.titleGrain yield stability of soybean (Glycine Max (L.) Merrill) for different stability models across diverse environments of Ethiopia
dc.typeJournal Article
cg.contributor.crpGrain Legumes
cg.contributor.affiliationEthiopian Institutes of Agricultural Research
cg.contributor.affiliationInternational Institute of Tropical Agriculture
cg.coverage.regionAfrica
cg.coverage.regionEast Africa
cg.coverage.countryEthiopia
cg.coverage.hubHeadquarters and Western Africa Hub
cg.researchthemeBiotech and Plant Breeding
cg.identifier.bibtexciteidHABTEGEBRIEL:2023
cg.isijournalISI Journal
cg.authorship.typesCGIAR and developing country institute
cg.iitasubjectAgronomy
cg.iitasubjectFood Security
cg.iitasubjectGrain Legumes
cg.iitasubjectPlant Breeding
cg.iitasubjectPlant Production
cg.iitasubjectSoybean
cg.iitasubjectValue Chains
cg.journalAgrosystems Geosciences & Environment
cg.notesOpen Access Journal
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/agg2.20396
cg.iitaauthor.identifierAbush Tesfaye: 0000-0002-9245-360X
cg.futureupdate.requiredNo
cg.identifier.issue3: e20396
cg.identifier.volume6
cg.contributor.acknowledgementsThe authors would like to thank all persons who participated in the field research. This includes the soybean national project cooperators at Jimma, Pawe, Bako, Metu sub-centre, and Asosa agricultural research centers for managing the field trials and collecting data.


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