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dc.contributorKharab, A.S.en_US
dc.contributorSingh, Jogendraen_US
dc.contributorVishnu, Kumaren_US
dc.contributorSharma, Induen_US
dc.contributorVerma, Ajayen_US
dc.creatorVerma, Ramesh Pal Singhen_US
dc.date2016-03-09en_US
dc.date.accessioned2017-02-20T10:22:24Z
dc.date.available2017-02-20T10:22:24Z
dc.identifierhttp://arccjournals.com/uploads/articles/ArticleFile-D-4352-2%20(9-16)%20D-4352.pdfen_US
dc.identifierhttps://mel.cgiar.org/reporting/download/hash/JZnTXRZyen_US
dc.identifier.citationRamesh Pal Singh Verma, A. S. Kharab, Jogendra Singh, Kumar Vishnu, Indu Sharma, Ajay Verma. (9/3/2016). AMMI model to analyse GxE for dual purpose barley in multi-environment trials. Agricultural Science Digest, 36 (1), pp. 9-16.en_US
dc.identifier.urihttps://hdl.handle.net/20.500.11766/5773
dc.description.abstractThe highly significant effects of environments, genotypes and interactions were observed for forage and grain yield. The environmental effects explained the major portion of the total variance as of 82.3% and 58.8% respectively. Indicated that the environments were diverse and a major part of variation in yield resulted from environmental changes. The highly significant interaction effects partitioned into IPCA1, IPCA2 and IPCA3, IPCA4; which explained 30.4, 19.4, 14.8 & 13.2% for forage and 37.0, 17.2, 16.1 and 12.5% for harvested grain yield. AMMI stability value(ASV) identified promising genotypes G12(UPB 1035), G6(UPB 1034), G7(BH 971) and G13(RD 2857), G7 (BH 971) & G11(NDB 1570) for forage and grain respectively. AMMI distance (D) marked G3(RD 2035) G9(BH 970) & G13(RD 2857) for former while genotypes G15(RD 2856) G11(NDB 1570) & G7(BH 971) for grain yield. GSI score advocated G13(RD 2857), G11(NDB 1570) G3(RD 2035),G5(RD 2715 ) and G7(BH 971), G2(RD 2552) G14(AZAD) desirable genotypes for selection with forage and grain yield. Genotypes with IPCA-1 scores close to zero identified G4(UPB 1036), G7(BH 971), G16(NDB 1566) and G11(NDB 1570), G2(RD 2552) for forage and yield respectively would have wider adaptation to the tested environments as per AMMI graphical plots.en_US
dc.formatPDFen_US
dc.languageenen_US
dc.publisherAgricultural Research Communication Centreen_US
dc.rightsCC-BY-NC-4.0en_US
dc.sourceAgricultural Science Digest;36,(2016) Pagination 9-16en_US
dc.subjectgxe interactionen_US
dc.subjectammi modelsen_US
dc.subjectammi stability value (asv)en_US
dc.subjectd(ammi distance)en_US
dc.subjectbiplot analysisen_US
dc.subjectgenotypic selection index(gsi)en_US
dc.titleAMMI model to analyse GxE for dual purpose barley in multi-environment trialsen_US
dc.typeJournal Articleen_US
dcterms.extent9-16en_US
cg.creator.idVerma, Ramesh Pal Singh: 0000-0002-2621-2015en_US
cg.subject.agrovocBarleyen_US
cg.contributor.centerInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.contributor.centerIndian Council of Agricultural Research, Indian Institute of Wheat and Barley Research - ICAR-IIWBRen_US
cg.contributor.crpCRP on Dryland Cereals - DCen_US
cg.contributor.funderCGIAR System Organization - CGIARen_US
cg.contributor.project-lead-instituteInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.contactverma.dwr@gmail.comen_US
dc.identifier.statusOpen accessen_US
cg.issn0253-150Xen_US
cg.journalAgricultural Science Digesten_US
cg.issue1en_US
cg.volume36en_US


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