Research Article

Related GMR Articles

2016 Dec 19
Plant breeding; Quantitative trait loci; Quantitative Trait, Heritable; Selection, Genetic; Zea mays

A challenge faced by popcorn breeding programs is the existence of a negative correlation between the two main traits, popping expansion and yield, which hinders simultaneous gains. The objective of this study was to investigate the use of a new variable or super trait, which favors the reliable selection of superior progenies. The super trait 'expanded popcorn volume per hectare' was ... more

A.T. do Amara Junior; D. Santos; I.F.S. Gerhardt; R.N.F. Kurosawa; N.F. Moreira; M.G. Pereira; deA. Gravina; F.H. de L. Silva
2017 Sep 27
Edible Grain; Models, Genetic; Plant breeding; Quantitative Trait, Heritable; Selection, Genetic; Selective breeding; Zea mays

Selection indices commonly utilize economic weights, which become arbitrary genetic gains. In popcorn, this is even more evident due to the negative correlation between the main characteristics of economic importance - grain yield and popping expansion. As an option in the use of classical biometrics as a selection index, the optimal procedure restricted maximum likelihood/best linear unbiased ... more

C. Vittorazzi; A.T.Amaral Júnior; A.G. Guimarães; A.P. Viana; F.H.L. Silva; G.F. Pena; R.F. Daher; I.F.S. Gerhardt; G.H.F. Oliveira; M.G. Pereira
2016 Dec 02
DNA, Plant; Edible Grain; Genetic variation; Hordeum; Minerals; Plant breeding; Quantitative trait loci; Selection, Genetic

Mineral elements in barley (Hordeum vulgare) play an important physiological role in global human health. In this study, quantitative trait loci (QTLs) for concentration of nine mineral elements in barley grain and grass powder were detected in a population of 193 recombinant inbred lines of the barley cross Ziguangmangluoerling x Schooner and the parents. We observed large genetic variation ... more

Y.W. Zeng; J. Du; X.M. Yang; X.Y. Pu; L.X. Wang; J.Z. Yang; L.J. Du; T. Yang; S.M. Yang; Z.H. Sun
2016 Dec 19
Chromosome Mapping; Chromosomes, Plant; Computer simulation; Epistasis, Genetic; Inbreeding; Models, Genetic; Plant breeding; Plants; Quantitative trait loci; Sample Size; Selection, Genetic

The accuracy of quantitative trait loci (QTLs) identified using different sample sizes and marker densities was evaluated in different genetic models. Model I assumed one additive QTL; Model II assumed three additive QTLs plus one pair of epistatic QTLs; and Model III assumed two additive QTLs with opposite genetic effects plus two pairs of epistatic QTLs. Recombinant inbred lines (RILs) (50- ... more

C.F. Su; W. Wang; S.L. Gong; J.H. Zuo; S.J. Li
2016 Dec 19
Avena; Brazil; Disease resistance; Edible Grain; Fungicides, Industrial; Plant breeding; Quantitative trait loci; Selection, Genetic

The State of Rio Grande do Sul (RS) is the largest producer of oat in Brazil with the aid of consolidated breeding programs, which are constantly releasing new cultivars. The main objectives of this study were to: 1) evaluate the annual genetic progress in grain yield and hectoliter weight of the oat cultivars in RS, with and without fungicide use on aerial parts of plants; and 2) evaluate the ... more

D.N. Follmann; C. Filho; A.D. Lúcio; V.Q. de Souza; M. Caraffa; C.A. Wartha
2017 Mar 16
Eucalyptus; Genotype; Lignin; Models, Genetic; Phenotype; Plant breeding; Quantitative trait loci; Random Allocation; Selection, Genetic; Wood

Path analysis has been used for establishing selection criteria in genetic breeding programs for several crops. However, it has not been used in eucalyptus breeding programs yet. In the present study, we aimed to identify the wood technology traits that could be used as the criteria for direct and indirect selection of eucalyptus genotypes with high energy density of wood. Twenty-four ... more

A.M. Couto; P.E. Teodoro; P.F. Trugilho
2017 Mar 22
Animals; Bayes Theorem; Breeding; Genetic markers; Genomics; Genotype; Models, Genetic; Polymorphism, Single Nucleotide; Predictive Value of Tests; Quantitative trait loci; Regression Analysis; Selection, Genetic

Genomic selection (GS) is a variant of marker-assisted selection, in which genetic markers covering the whole genome predict individual genetic merits for breeding. GS increases the accuracy of breeding values (BV) prediction. Although a variety of statistical models have been proposed to estimate BV in GS, few methodologies have examined statistical challenges based on non-normal phenotypic ... more

M. Nascimento; F.F.E. Silva; M.D.V. de Resende; C.D. Cruz; A.C.C. Nascimento; J.M.S. Viana; C.F. Azevedo; L.M.A. Barroso
2017 Aug 17
Edible Grain; Genotype; Inbreeding; Models, Genetic; Plant breeding; Quantitative Trait, Heritable; Selection, Genetic; Selective breeding; Vigna

The aim of this study was to estimate the genotypic gain with simultaneous selection of production, nutrition, and culinary traits in cowpea crosses and backcrosses and to compare different selection indexes. Eleven cowpea populations were evaluated in a randomized complete block design with four replications. Fourteen traits were evaluated, and the following parameters were estimated: ... more

D.G. Oliveira; M.M. Rocha; K.J. Damasceno-Silva; F.V. Sá; L.R.L. Lima; M.D.V. Resende
2016 Dec 02
Crosses, Genetic; Genotype; Phenotype; Quantitative trait loci; Zea mays

The successful development of hybrid cultivars depends on the reliability of estimated combining ability of the parent lines. The objectives of this study were to assess the combining ability of partially inbred S families of popcorn derived from the open-pollinated variety UENF 14, via top-crosses with four testers, and to compare the testers for their ability to discriminate the S progenies ... more

V.J. de Lima; A.T. do Amara Junior; S.H. Kamphorst; G.F. Pena; J.T. Leite; K.F.M. Schmitt; C. Vittorazzi; J.E. de Almei Filho; F. Mora
2017 Mar 30
Crop Production; Edible Grain; Plant breeding; Zea mays

The objective of this study was to estimate the direct effects of explanatory variables on the grain yield of corn in the combinations formed by three types of hybrids x two harvests x nine scenarios of explanatory variables x two types of path analyses. Eleven explanatory variables were measured in 361, 373, and 416 single-, triple-, and double-cross hybrid plants from the 2008/2009 harvest, ... more

M. Toebe; C. Filho; L. Storck; A.D. Lúcio

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