AMMI and GGE Biplot Analyses for Mega-Environment Identification and Selection of Some High-Yielding Oat (Avena sativa L.) Genotypes for Multiple Environments

cg.contactkibreabyosefe@gmail.comen_US
cg.contributor.centerInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.contributor.centerInternational Crops Research Institute for the Semi-Arid Tropics - ICRISATen_US
cg.contributor.centerSouthern Agricultural Research Institute - SARI, Ethiopiaen_US
cg.contributor.centerJimma University, College of Agriculture and Veterinary Medicine - JU-CAVMen_US
cg.contributor.centerSouthern Agricultural Research Institute, Areka Agricultural Research Center - SARI - Arekaen_US
cg.contributor.centerBonga Agricultural Research Center - BARCen_US
cg.contributor.centerArba Minch Agricultural Research Centeren_US
cg.contributor.crpResilient Agrifood Systems - RAFSen_US
cg.contributor.funderInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.contributor.funderBonga Agricultural Research Center - BARCen_US
cg.contributor.initiativeSustainable Animal Productivityen_US
cg.contributor.initiativeMixed Farming Systemsen_US
cg.contributor.project-lead-instituteInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.coverage.countryETen_US
cg.coverage.end-date2023-03-31en_US
cg.coverage.regionEastern Africaen_US
cg.coverage.start-date2022-06-01en_US
cg.creator.idWamatu, Jane: 0000-0003-3544-6718en_US
cg.creator.idMamta, Sharma: 0000-0001-5745-4693en_US
cg.identifier.doihttps://dx.doi.org/10.3390/plants12173064en_US
cg.isijournalISI Journalen_US
cg.issn2223-7747en_US
cg.issue17en_US
cg.journalPlantsen_US
cg.subject.actionAreaResilient Agrifood Systemsen_US
cg.subject.agrovocammien_US
cg.subject.agrovocforageen_US
cg.subject.impactAreaNutrition, health and food securityen_US
cg.subject.impactAreaEnvironmental health and biodiversityen_US
cg.subject.sdgSDG 2 - Zero hungeren_US
cg.subject.sdgSDG 12 - Responsible consumption and productionen_US
cg.volume12en_US
dc.contributorTolemariam, Tayeen_US
dc.contributorDemeke, Solomonen_US
dc.contributorGaredew, Weyessaen_US
dc.contributorTesfaye, Tessemaen_US
dc.contributorEkule, Mulukenen_US
dc.contributorGemiyu, Deribeen_US
dc.contributorBedeke, Workuen_US
dc.contributorWamatu, Janeen_US
dc.contributorMamta, Sharmaen_US
dc.creatorWodebo, Kibreaben_US
dc.date.accessioned2023-12-05T16:45:33Z
dc.date.available2023-12-05T16:45:33Z
dc.description.abstractThis paper reports an evaluation of eleven oat genotypes in four environments for two consecutive years to identify high-biomass-yielding, stable, and broadly adapted genotypes in selected parts of Ethiopia. Genotypes were planted and evaluated with a randomized complete block design, which was repeated three times. The additive main effect and multiplicative interaction analysis of variances revealed that the environment, genotype, and genotype–environment interaction had a significant (p ≤ 0.001) influence on the biomass yield in the dry matter base (t ha−1). The interaction of the first and second principal component analysis accounted for 73.43% and 14.97% of the genotype according to the environment interaction sum of squares, respectively. G6 and G5 were the most stable and widely adapted genotypes and were selected as superior genotypes. The genotype-by-environment interaction showed a 49.46% contribution to the total treatment of sum-of-squares variation, while genotype and environment effects explained 34.94% and 15.60%, respectively. The highest mean yield was obtained from G6 (12.52 kg/ha), and the lowest mean yield was obtained from G7 (8.65 kg/ha). According to the additive main effect and multiplicative interaction biplot, G6 and G5 were high-yielding genotypes, whereas G7 was a low-yielding genotype. Furthermore, according to the genotype and genotype–environment interaction biplot, G6 was the winning genotype in all environments. However, G7 was a low-yielding genotype in all environments. Finally, G6 was an ideal genotype with a higher mean yield and relatively good stability. However, G7 was a poor-yielding and unstable genotype. The genotype, environment, and genotype x environment interaction had extremely important effects on the biomass yield of oats. The findings of the graphic stability methods (additive main effect and multiplicative interaction and the genotype and genotype–environment interaction) for identifying high-yielding and stable oat genotypes were very similar.en_US
dc.formatPDFen_US
dc.identifierhttps://mel.cgiar.org/reporting/downloadmelspace/hash/15ab65ff70065173bf5cf30bb55c1ec7/v/937692e877721b0739cbd64c25168981en_US
dc.identifier.citationKibreab Wodebo, Taye Tolemariam, Solomon Demeke, Weyessa Garedew, Tessema Tesfaye, Muluken Ekule, Deribe Gemiyu, Worku Bedeke, Jane Wamatu, Sharma Mamta. (25/8/2023). AMMI and GGE Biplot Analyses for Mega-Environment Identification and Selection of Some High-Yielding Oat (Avena sativa L. ) Genotypes for Multiple Environments. Plants, 12 (17).en_US
dc.identifier.statusOpen accessen_US
dc.identifier.urihttps://hdl.handle.net/20.500.11766/68864
dc.languageenen_US
dc.publisherMultidisciplinary Digital Publishing Institute (MDPI)en_US
dc.rightsCC-BY-4.0en_US
dc.sourcePlants;12,(2023)en_US
dc.subjectggeen_US
dc.subjectgxe interactionen_US
dc.subjectbiomass yielden_US
dc.subjectoat (avena sativa l.)en_US
dc.titleAMMI and GGE Biplot Analyses for Mega-Environment Identification and Selection of Some High-Yielding Oat (Avena sativa L.) Genotypes for Multiple Environmentsen_US
dc.typeJournal Articleen_US
dcterms.available2023-08-25en_US
dcterms.issued2023-08-25en_US
mel.impact-factor4.5en_US

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