Dataset for unrevealing the application of multi-trait genotype-ideotype distance index and multi-trait index based on factor analysis and ideotype-design models in the identification of high-yielding and stable barley genotypes

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cris.virtual.author-orcid0000-0002-0102-0084
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cris.virtual.author-orcid0000-0002-8011-9487
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cris.virtualsource.author-orcid51a5a68b-106b-4e9d-bd9b-79d15d3ec0c1
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cris.virtualsource.author-orcid20597688-8be2-4b58-9e15-29f5ff8c53aa
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dc.abstract.enDissecting the genotype-by-environment interaction (GEI) effects in multi-environmental trials (METs) is a critical step in any breeding program before introducing new commercial varieties for cultivation in specific regions or across diverse environments. This dataset explores the application of two novel selection models: the multi-trait genotype-ideotype distance index (MGIDI) and the multi-trait index based on factor analysis and ideotype-design (FAI-BLUP). These models incorporate comprehensive stability parameters to identify high-yielding and stable barley genotypes across varying environmental conditions. In both models, the first three factors (FAs) with eigenvalues greater than 1 accounted for 92.3% of the total variation. The BLUP-based parameters, along with grain yield (GY) and the mean variance component (Ɵ), showed a positive selection deferential (SD) and correlated with the second factor (FA2). Notably, these models identified G3, G10, and G14 as the most stable genotypes. In conclusion, this dataset underscores the utility of comprehensive stability parameters and advanced selection models in identifying high-yielding, stable genotypes within the framework of METs.
dc.affiliationWydział Rolnictwa, Ogrodnictwa i Biotechnologii
dc.affiliation.instituteKatedra Metod Matematycznych i Statystycznych
dc.contributor.authorPour-Aboughadareh, Alireza
dc.contributor.authorJadidi, Omid
dc.contributor.authorJamshidi, Bita
dc.contributor.authorBocianowski, Jan
dc.contributor.authorNiemann, Janetta
dc.date.access2025-03-10
dc.date.accessioned2025-03-20T07:58:40Z
dc.date.available2025-03-20T07:58:40Z
dc.date.copyright2025-02-11
dc.date.issued2025
dc.description.accesstimeat_publication
dc.description.bibliographyil., bibliogr.
dc.description.financepublication_nocost
dc.description.financecost0,00
dc.description.if1,00
dc.description.points40
dc.description.reviewreview
dc.description.versionfinal_published
dc.description.volume59
dc.identifier.doi10.1016/j.dib.2025.111383
dc.identifier.issn2352-3409
dc.identifier.urihttps://sciencerep.up.poznan.pl/handle/item/2608
dc.identifier.weblinkhttps://www.sciencedirect.com/science/article/pii/S2352340925001155
dc.languageen
dc.relation.ispartofData in Brief
dc.relation.pagesart. 111383
dc.rightsCC-BY
dc.sciencecloudnosend
dc.share.typeOPEN_JOURNAL
dc.subject.enGenotype-by-environment interaction
dc.subject.enGrain yield
dc.subject.enStability parameters
dc.subject.enAMMI model
dc.subject.enBLUP model
dc.subtypeDataPaper
dc.titleDataset for unrevealing the application of multi-trait genotype-ideotype distance index and multi-trait index based on factor analysis and ideotype-design models in the identification of high-yielding and stable barley genotypes
dc.typeJournalArticle
dspace.entity.typePublication
oaire.citation.volume59