Genotype by environment interaction effect on yield and forage quality of native panic grasses: AMMI, GGE biplot and correlation analysis

cg.contacttessema4@gmail.comen_US
cg.contributor.centerInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.contributor.centerSouthern Agricultural Research Institute - SARI Ethiopiaen_US
cg.contributor.centerHawassa University - HU - Ethiopiaen_US
cg.contributor.centerArba Minch Agricultural Research Centeren_US
cg.contributor.centerSouthern Agricultural Research Institute, Arba Minch agriculture research center - SARI Ethiopia -AMARCen_US
cg.contributor.funderCGIAR Trust Funden_US
cg.contributor.programAcceleratorSustainable Animal and Aquatic Foodsen_US
cg.contributor.programAcceleratorSustainable Farmingen_US
cg.contributor.project-lead-instituteInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.coverage.countryETen_US
cg.coverage.end-date2025-05-12en_US
cg.coverage.regionEastern Africaen_US
cg.coverage.start-date2019-05-14en_US
cg.creator.idWamatu, Jane: 0000-0003-3544-6718en_US
cg.identifier.doihttps://doi.org/10.1007/s43621-025-02459-0en_US
cg.isijournalISI Journalen_US
cg.journalDiscover Sustainabilityen_US
cg.reviewStatusPeer Reviewen_US
cg.subject.agrovocforageen_US
cg.subject.impactAreaClimate adaptation and mitigationen_US
cg.subject.impactAreaPoverty reduction, livelihoods and jobsen_US
cg.subject.sdgSDG 8 - Decent work and economic growthen_US
cg.subject.sdgSDG 11 - Sustainable cities and communitiesen_US
cg.subject.sdgSDG 13 - Climate actionen_US
cg.volume8en_US
dc.contributorSamago, Tarekegn Yosephen_US
dc.contributorYada, Tuma Ayeleen_US
dc.contributorTeko, Otoro Olkieen_US
dc.contributorKebede Kalsa, Getineten_US
dc.contributorHibebo, Derrebe Kassaen_US
dc.contributorHeliso, Milkias Fantaen_US
dc.contributorEkule, Mulukenen_US
dc.contributorWamatu, Janeen_US
dc.creatorTesfaye, Tessemaen_US
dc.date.accessioned2026-01-26T14:33:29Z
dc.date.available2026-01-26T14:33:29Z
dc.description.abstractFeed scarcity during the dry season is common in Ethiopia. The potential of existing indigenous grasses can be harnessed and optimized for inclusion in livestock diets. The objective of this study was to evaluate the performance, stability, and genotype × environment interaction (GEI) for dry matter yield (DMY) and crude protein yield (CPY) and key parameters correlations of four panic grass: Chano (Panicum maximum Jack (PMJ), Panicum virgatum (PV), Gardula (Dichanthelium latifolium (DL), and Degungiziya (Panicum maximum) as standard check (DG(SC))) genotypes across seven diverse environments. The experiment was conducted at Argubatenao (AT), Chanomile (CM), Humbo (HM), and Lemu (LM) in the South and Central Ethiopia region during 2022 and 2023 (seven environments: AT2022, AT2023, CM2022, CM2023, HM2022, HM2023, and LM2023). Experimental field was laid out in a randomized complete block design with three replicates. Data was analyzed using Additive Main Effect and Multiplicative Interaction (AMMI) and Genotype and Genotype × Environment (GGE) biplot analyses with Pearson’s correlation analysis. DMY and CPY including additional forage quality traits of native panicum grasses, and their responses in different environments, were analyzed. The mean DMY performance of the genotypes ranged from 7.75 to 13.99 t/ha, while environmental variation was ranged from 1.37 to 15.42 t/ha. Genotype PMJ outperformed all other genotypes across all testing environments, showing a yield advantage of 21.5% over the mean DMY and 44.6% over check variety (DG). AMMI and GGE biplots provided high yielding genotype (PMJ) with wider adaptations in mega environments of AT2022, AT2023, CM2022, CM2023, and HM2022. The correlation analysis also revealed a strong positive relationship of DMY and CPY with tiller number, plant height, and leaf width, while DMY showed a negative association with IVOMD. DL demonstrated moderate stability across all environments for CP%, IVOMD, and ME. Hence, cultivation of PMJ and DL recommended across suitable environments and variety release in discriminative environments. Further research should include a larger pool of genotypes and more detailed environments to refine selection accuracy and animal testing and molecular or genomic tools could be integrated to strengthen breeding efforts.en_US
dc.identifierhttps://mel.cgiar.org/reporting/downloadmelspace/hash/ce0c106155b7772d3f6c3cb99af4c26den_US
dc.identifier.citationTessema Tesfaye, Tarekegn Yoseph Samago, Tuma Ayele Yada, Otoro Olkie Teko, Getinet Kebede Kalsa, Derrebe Kassa Hibebo, Milkias Fanta Heliso, Muluken Ekule, Jane Wamatu. (13/1/2026). Genotype by environment interaction effect on yield and forage quality of native panic grasses: AMMI, GGE biplot and correlation analysis. Discover Sustainability, 8.en_US
dc.identifier.statusOpen accessen_US
dc.identifier.urihttps://hdl.handle.net/20.500.11766/70417
dc.languageenen_US
dc.publisherSpringer (part of Springer Nature)en_US
dc.rightsCC-BY-NC-ND-4.0en_US
dc.sourceDiscover Sustainability;8,en_US
dc.subjectgrassen_US
dc.subjectnativeen_US
dc.subjectpanicumen_US
dc.titleGenotype by environment interaction effect on yield and forage quality of native panic grasses: AMMI, GGE biplot and correlation analysisen_US
dc.typeJournal Articleen_US
dcterms.available2026-01-13en_US
dcterms.hasVersionV3 - 2026-01-26en_US
dcterms.issued2026-01-13en_US
mel.impact-factor3.0en_US

Files

License bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
license.txt
Size:
1.72 KB
Format:
Item-specific license agreed upon to submission
Description: