Mixed model-based Jinks and Pooni method to predict segregating populations in wheat breeding

dc.contributor.authorMezzomo, Henrique Caletti
dc.contributor.authorCasagrande, Cleiton Renato
dc.contributor.authorSousa, Diana Jhulia Palheta de
dc.contributor.authorBorém, Aluízio
dc.contributor.authorSilva, Fabyano Fonseca e
dc.contributor.authorNardino, Maicon
dc.date.accessioned2026-10-16T20:56:22Z
dc.date.issued2021
dc.description.abstractThe improvement of superior wheat cultivars depends on the identification of promising segregating populations to derive superior lines. A lattice model (8×8) involving 56 F2 populations and eight parents was conducted in the 2020 cropping season, and grain yield per plant was evaluated for every F2 population, with further analysis of the population potential by Jinks and Pooni method via REML/BLUP. A total of 5,410 F2 plants were evaluated in this study. The results showed that the use of genetic variance associated with the individual genotypic value (BLUP) was superior compared with the use of variance and traditional phenotypic values. The F2 populations, CD 1303/BRS 254, CD 1303/Tbio Duque, CD 1303/Tbio Ponteiro, BRS 264/Tbio Aton, Tbio Ponteiro/Tbio Aton, and Tbio Sossego/CD 1303 had the highest likelihood of deriving superior lines.en
dc.identifier.citationMEZZOMO, Henrique Caletti. et al. Mixed model-based Jinks and Pooni method to predict segregating populations in wheat breeding. Revista Crop Breeding and Applied Biotechnology, Viçosa, v. 21, n. 4, p. 01-10, 2021.
dc.identifier.doihttp://dx.doi.org/10.1590/1984-70332021v21n4a52
dc.identifier.issn1984-7033
dc.identifier.urihttps://locus.ufv.br/handle/123456789/36027
dc.language.isoeng
dc.publisherCrop Breeding and Applied Biotechnology
dc.relation.ispartofseriesv. 21 ; n. 4
dc.rightsCreative Commons Attribution License
dc.subjectTriticum aestivum Len
dc.subjectQuantitative geneticsen
dc.subjectPlant selectionen
dc.titleMixed model-based Jinks and Pooni method to predict segregating populations in wheat breedingen
dc.typeArtigo

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