To build up efficient strategies in plant breeding programs, it is requested a certain level of knowledge about the genotype–by-environments interaction (GEI) effects over the crop to be improved. One efficient way to gather this information is using linear mixed models using a parsimonious structure of GEI pattern such as factor analytic (FA) structure. In th.. Read More»
Genet. Mol. Res. 17(1): gmr16039890
DOI: 10.4238/gmr16039890
The additive main effects and multiplicative interaction (AMMI) and the genotype main effects and genotype x environment interaction (GGE) models stand out among the linear-bilinear models used in genotype x environment interaction studies. Despite the advantages of their use to describe genotype x environment (AMMI) or genotype and genotype x environment (GGE) inte.. Read More»
Genet. Mol. Res. 15(2): gmr.15028612
DOI: 10.4238/gmr.15028612
The main objective of a maize breeding program is to generate hybrid combinations that are more productive than those pre-existing in the market. However, the number of parents, and consequently the number of crosses, increases so rapidly that the phenotypic evaluation of all the possible combinations becomes economically and technically infeasible. In this context, predicting the performance o.. Read More»
Genet. Mol. Res. 15(1): gmr.15017232
DOI: 10.4238/gmr.15017232
The objective of the present study was to correlate the genetic distances (GD) of single cross hybrids with yield, heterosis and specific combining ability (SCA) in the double cross hybrid synthesis. For this, 10 single cross commercial hybrids were used from different companies, and all the possible double hybrids were synthesized by a complete dialell. The hybrids were assessed in 15 location.. Read More»
Genet. Mol. Res. 7(1): vol7-1gmr403
DOI: 10.4238/vol7-1gmr403
Gray leaf spot (GLS) is a major maize disease in Brazil that significantly affects grain production. We used Bayesian inference to investigate the nature and magnitude of gene effects related to GLS resistance by evaluation of contrasting lines and segregating populations. The experiment was arranged in a randomized block design with three replications and the mean .. Read More»
Genet. Mol. Res. 11(1): http://dx.doi.org/2012.January.9.3
DOI: http://dx.doi.org/10.4238/2012.January.9.3
We aimed to identify simple sequence repeat (SSR) markers linked to quantitative trait loci (QTLs) associated with white mold resistance in a segregating population derived from a cross between common bean cultivars Jalo and Small White, in the Southern State of Minas Gerais. Parents were crossed to obtain the F2 generation of 190 plants. From these, F2:3 and F2:4 progenies were obtained for ph.. Read More»
Genet. Mol. Res. 15(3): gmr.15038724
DOI: 10.4238/gmr.15038724
We evaluated the phenotypic and genotypic stability and adaptability of hybrids using the additive main effect and multiplicative interaction (AMMI) and genotype x genotype-environment interaction (GGE) biplot models. Starting with 10 single-cross hybrids, a complete diallel was done, resulting in 45 double-cross hybrids that were appraised in 15 locations in Southe.. Read More»
Genet. Mol. Res. 8(4): vol8-4gmr658
DOI: 10.4238/vol8-4gmr658
We evaluated the potential of genetic distances estimated by microsatellite markers for the prediction of the performance of single-cross maize hybrids. We also examined the potential of molecular markers for the prediction of genotypic values and the applicability of the Monte Carlo method for a correlation of genetic distances and grain yield. Ninety S0:2 progenie.. Read More»
Genet. Mol. Res. 8(4): vol8-4gmr644
DOI: 10.4238/vol8-4gmr644
In many species, low levels of polymorphism prevent the assembly of linkage maps that are used to identify genetic markers related to the expression of quantitative trait loci (QTLs). This study compared two methods of locating QTLs in association studies that do not require a previous estimation of linkage maps. Method I (MI) was a Bayesian multiple marker regression and Method II (MII) combin.. Read More»
Genet. Mol. Res. 14(3): http://dx.doi.org/2015.September.25.13
DOI: http://dx.doi.org/10.4238/2015.September.25.13
This study aimed to analyze the robustness of mixed models for the study of genotype-environment interactions (G x E). Simulated unbalancing of real data was used to determine if the method could predict missing genotypes and select stable genotypes. Data from multi-environment trials containing 55 maize hybrids, collected during the 2005-2006 harvest season, were used in this study. Analyses w.. Read More»
Genet. Mol. Res. 14(4): 2015.November.13.10
DOI: 10.4238/2015.November.13.10
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