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dc.contributorArmion, Mohammaden_US
dc.contributorZadhsan, Esmaeilen_US
dc.contributorAhmadi, Malek Masouden_US
dc.contributorAmri, Ahmeden_US
dc.creatorMohammadi, Rezaen_US
dc.date.accessioned2018-03-12T01:33:43Z
dc.date.available2018-03-12T01:33:43Z
dc.identifierhttps://www.cambridge.org/core/journals/experimental-agriculture/article/use-of-ammi-model-for-interpreting-genotype-environment-interaction-in-durum-wheat/9874315F9BE9FD64FC8BDF3630C65722en_US
dc.identifierhttps://mel.cgiar.org/reporting/download/hash/IAjOafGven_US
dc.identifier.citationReza Mohammadi, Mohammad Armion, Esmaeil Zadhsan, Malek Masoud Ahmadi, Ahmed Amri. (3/7/2017). The use of AMMI model for interpreting genotype x environment interaction in durum wheat. Experimental Agriculture, 1.en_US
dc.identifier.urihttps://hdl.handle.net/20.500.11766/8069
dc.description.abstractDurum wheat (Triticum durum) is one of the most important cereal crops in the Mediterranean region; however, its cultivation suffers from low yield due to environmental constrains. The main objectives of this study were to (i) assess genotype × environment (GE) interaction for grain yield in rainfed durum wheat and to (ii) analyse the relationships of GE interaction with genotypic/meteorological variables by the additive main effects and multiplicative interaction (AMMI) model. Grain yield and some related traits were evaluated in 25 durum wheat genotypes (landrace, breeding line, old and new varieties) in 12 rainfed environments differing in winter air temperature. The AMMI analysis of variance indicated that the environment had highest contribution (84.3% of total variation) to the variation in grain yield. The first interaction principal component axis (IPCA1) explained 77.5% of GE interaction sum of squares (SS), and its effect was 5.5 times greater than the genotype effect, indicating that the IPCA1 contributed remarkably to the total GE interaction. Large GE interaction for grain yield was detected, indicating specific adaptation of genotypes. While the postdictive success method indicated AMMI-4 as the best model, the predictive success one suggested AMMI-1. The AMMI biplot analysis confirmed a rank change interaction among the locations, indicating the presence of strong and unpredictable rank-change location-by-year interactions for locations. In contrast to landraces and old varieties, the breeding lines with high yield performance had high phenotypic plasticity under varying environmental conditions. Results indicated that the GE interaction was associated with the interaction of heading date, plant height, rainfall, air temperature and freezing days.en_US
dc.formatPDFen_US
dc.languageenen_US
dc.publisherCambridge University Press (CUP): STM Journalsen_US
dc.rightsCC-BY-NC-4.0en_US
dc.sourceExperimental Agriculture;1,(2017)en_US
dc.titleThe use of AMMI model for interpreting genotype x environment interaction in durum wheaten_US
dc.typeJournal Articleen_US
dcterms.available2017-07-03en_US
cg.creator.idAmri, Ahmed: 0000-0003-0997-0276en_US
cg.subject.agrovoctriticum durumen_US
cg.subject.agrovocdurum (triticum durum)en_US
cg.subject.agrovocWheaten_US
cg.contributor.centerInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.contributor.centerAgricultural Research, Education and Extension Organization (Agricultural Extension, Education and Research Organization) - AREEO (AEERO)en_US
cg.contributor.crpCGIAR Research Program on Wheat - WHEATen_US
cg.contributor.funderInternational Maize and Wheat Improvement Center - CIMMYTen_US
cg.contributor.projectCRP WHEAT Phase IIen_US
cg.contributor.project-lead-instituteInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.contactr.mohammadi@areo.iren_US
cg.identifier.doihttps://dx.doi.org/10.1017/S0014479717000308en_US
cg.isijournalISI Journalen_US
dc.identifier.statusOpen accessen_US
cg.issn0014-4797en_US
cg.journalExperimental Agricultureen_US
cg.volume1en_US


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