Comparison of parametric and non-parametric methods for selecting stable and adapted durum wheat genotypes in variable environments

cg.contactr.mohammadi@areo.iren_US
cg.contributor.centerInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.contributor.centerAgricultural Research, Education and Extension Organization, Dryland Agricultural Research Institute - AREEO-DARIen_US
cg.contributor.funderInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.contributor.projectCommunication and Documentation Information Services (CODIS)en_US
cg.contributor.project-lead-instituteInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.coverage.countryIRen_US
cg.coverage.regionSouthern Asiaen_US
cg.creator.idAmri, Ahmed: 0000-0003-0997-0276en_US
cg.date.embargo-end-dateTimelessen_US
cg.identifier.doihttps://dx.doi.org/10.1007/s10681-007-9600-6en_US
cg.isijournalISI Journalen_US
cg.issn0014-2336en_US
cg.journalEuphyticaen_US
cg.subject.agrovocadaptabilityen_US
cg.subject.agrovocdurum (triticum durum)en_US
cg.volume159en_US
dc.contributorAmri, Ahmeden_US
dc.creatorMohammadi, Rezaen_US
dc.date.accessioned2020-11-25T23:48:00Z
dc.date.available2020-11-25T23:48:00Z
dc.description.abstractTwenty parametric and non-parametric measures derived from grain yield of 15 advanced durum genotypes evaluated across 12 variable environments during the 2004-2006 growing seasons were used to assess performance stability and adaptability of the genotypes and to study interrelationship among these measures. The combined ANOVA and the non-parametric tests of Genotype x environment interaction indicated the presence of significant crossover and non-crossover interactions, and of significant differences among genotypes. Principal component analysis based on the rank correlation matrix indicated that most non-parametric measures were significantly inter-correlated with parametric measures and therefore can be used as alternatives. The results also revealed that stability measures can be classified into three groups based on static and dynamic concepts of stability. The group related to the dynamic concept and strongly correlated with mean grain yield of stability included the parameters of TOP (proportion of environments in which a genotype ranked in the top third), superiority index (P-i) and geometric adaptability index. The second group reflecting the concept of static stability included, Wricke's ecovalence, the variance in regression deviation (S-di(2)), AMMI stability value, the Huehn's parameters [S-i((1)), S-i((2))], Tennarasua's parameter [NPi(1)], Kang's parameter ( RS) and yield reliability index (I-i) which were not correlated with mean grain yield. The third group influenced simultaneously by grain yield and stability included the measures S-i((3)), S-i((6)), NPi(2), NPi(3), environmental variance (S-xi(2)), coefficient of variability and coefficient of regression (b(i)). Based on the concept of dynamic stability, genotypes G6, G4, and G3 were found to be the most adapted to favorable environments, whereas genotypes G8, G9, and G12 were more stable and are related to the concept of static stability.en_US
dc.formatPDFen_US
dc.identifierhttps://mel.cgiar.org/dspace/limiteden_US
dc.identifier.citationReza Mohammadi, Ahmed Amri. (23/10/2007). Comparison of parametric and non-parametric methods for selecting stable and adapted durum wheat genotypes in variable environments. Euphytica, 159, pp. 419-432.en_US
dc.identifier.statusTimeless limited accessen_US
dc.identifier.urihttps://hdl.handle.net/20.500.11766/12102
dc.languageenen_US
dc.publisherSpringer (part of Springer Nature)en_US
dc.sourceEuphytica;159,(2007) Pagination 419-432en_US
dc.subjectge interactionen_US
dc.subjectdynamic and static stabilityen_US
dc.subjectparametric and non-parametric measuresen_US
dc.titleComparison of parametric and non-parametric methods for selecting stable and adapted durum wheat genotypes in variable environmentsen_US
dc.typeJournal Articleen_US
dcterms.available2007-10-23en_US
dcterms.extent419-432en_US
mel.impact-factor1.614en_US

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