2016
DOI: 10.1111/pbr.12429
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Unravelling the inheritance, QST and reproductive phenology attributes of the tetraploid tropical grass Brachiaria ruziziensis (Germain et Evrard)

Abstract: The autotetraploid forage Congo signal grass (Brachiaria ruziziensis) is an important component in the Brachiaria breeding programme. As with other tropical forage grass species, the association between flowering and seed yield components, the mode of inheritance and the effects of population structure on phenotypic breeding are lacking. Seventeen characteristics evaluated in 59 half‐sib progeny of seven subpopulations were analysed using a mixed model methodology. According to the commonality analysis, the to… Show more

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Cited by 7 publications
(10 citation statements)
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“…hybrids selected by the Mulamba and Mock index (MMI) using the first two principal components (MMI PC ), mean genotypic value of the selected hybrids by principal components (GV.PC), mean genotypic value of selected hybrids using MMI based only in phenotypic information (GV.MM), mean genotypic value of selected hybrids by univariate analysis (GV.Uni), broad-sense heritability estimate (h 2 ), selection gain by MMI PC considering 1% of selection intensity (SG.PC), selection gain by phenotypic MMI Uni considering 1% of selection intensity (SG.MM), selection gain by univariate analysis considering 1% of selection intensity (SG.Uni), relative selection gain given by SG.CP/ and SG.Uni (rSG.PC), relative selection gain given by SG.MM and SG.Uni (rSG.MM), and general mean ( X ). and TDM, with narrow-sense heritability of 0.31 and 0.30, respectively (Simeão et al, 2017). These values of heritability are lower than observed for the same traits in this interspecific population of Urochloa spp., with FGW = 0.46 and TDM = 0.59 ( Table 2).…”
Section: Diallel Analysis and Selection Methodsmentioning
confidence: 51%
See 1 more Smart Citation
“…hybrids selected by the Mulamba and Mock index (MMI) using the first two principal components (MMI PC ), mean genotypic value of the selected hybrids by principal components (GV.PC), mean genotypic value of selected hybrids using MMI based only in phenotypic information (GV.MM), mean genotypic value of selected hybrids by univariate analysis (GV.Uni), broad-sense heritability estimate (h 2 ), selection gain by MMI PC considering 1% of selection intensity (SG.PC), selection gain by phenotypic MMI Uni considering 1% of selection intensity (SG.MM), selection gain by univariate analysis considering 1% of selection intensity (SG.Uni), relative selection gain given by SG.CP/ and SG.Uni (rSG.PC), relative selection gain given by SG.MM and SG.Uni (rSG.MM), and general mean ( X ). and TDM, with narrow-sense heritability of 0.31 and 0.30, respectively (Simeão et al, 2017). These values of heritability are lower than observed for the same traits in this interspecific population of Urochloa spp., with FGW = 0.46 and TDM = 0.59 ( Table 2).…”
Section: Diallel Analysis and Selection Methodsmentioning
confidence: 51%
“…This result is the opposite of what was observed in U. humidicola, in which there was significant difference between the sexual parents for GCA and no significant interaction (SCA) between sexual and apomictic parents for FGW and TDM (Figueiredo, 2015). and TDM, with narrow-sense heritability of 0.31 and 0.30, respectively (Simeão et al, 2017). Genotypic value (GV) of the 10 best Urochloa spp.…”
Section: Discussion Diallel Analysis and Selection Methodsmentioning
confidence: 99%
“…Wutoh et al (1968) and Souza et al (2015) also observed that greater individual seed weight can be advantageous, since it can lead to faster initial growth and better adaptation to the environment. According to Simeão, Valle, and Resende (2017), seed yield has rarely been considered a selection criterion in the early stages of breeding programs, but it is an essential attribute for a commercial forage grass genotype to be competitive in the market (Fang, Aamlid, Jørgensen, & Rognli, 2004).…”
Section: Resultsmentioning
confidence: 99%
“…For breeding programs that make use of biparental crosses, the major challenge is to precisely identify whether there are contaminating individuals to be excluded from the progeny (Martuscello et al, 2009;Ma and Amos, 2012;Santos et al, 2014;Subashini et al, 2014;Simeão et al, 2016b;Matias et al, 2019;Deo et al, 2020). In this context, no studies have proposed a unified pipeline focused on identifying the most common contaminants in biparental crossings, especially in polyploid species, and supplying such a pipeline is the main objective of this work.…”
Section: Discussionmentioning
confidence: 99%