lassification using a scale of visual notes is a strategy used to select erect bean plants in order to improve bean plant architectures. Use of morphological traits associated with the phenotypic expression of bean architecture in classification procedures may enhance selection. The objective of this study was to evaluate the potential of artificial neural networks .. Read More»
Genet. Mol. Res. 16(2): gmr16029500
DOI: 10.4238/gmr16029500
Artificial neural networks have shown great potential when applied to breeding programs. In this study, we propose the use of artificial neural networks as a viable alternative to conventional prediction methods. We conduct a thorough evaluation of the efficiency of these networks with respect to the prediction of breeding values. Therefore, we considered eight simulated scenarios, and for the .. Read More»
Genet. Mol. Res. 15(1): gmr.15017676
DOI: 10.4238/gmr.15017676
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 base.. Read More»
Genet. Mol. Res. 16(1): gmr16019538
DOI: 10.4238/gmr16019538
Artificial neural networks have been used for various purposes in plant breeding, including use in the investigation of genotype x environment interactions. The aim of this study was to use artificial neural networks in the selection of common bean genotypes with high phenotypic adaptability and stability, and to verify their consistency with the Eberhart and Russel.. Read More»
Genet. Mol. Res. 15(2): gmr.15028230
DOI: 10.4238/gmr.15028230
The aim of this study was to evaluate the suitability of statistics as experimental precision degree measures for trials with cowpea (Vigna unguiculata L. Walp.) genotypes. Cowpea genotype yields were evaluated in 29 trials conducted in Brazil between 2005 and 2012. The genotypes were evaluated with a randomized block design with four replications. Ten statistics th.. Read More»
Genet. Mol. Res. 15(2): gmr.15027991
DOI: 10.4238/gmr.15027991
We propose and evaluate a novel approach for forecasting gene expression over non-observed times in longitudinal trials under a Bayesian viewpoint. One of the aims is to cluster genes that share similar expression patterns over time and then use this similarity to predict relative expression at time points of interest. Expression values of 106 genes expressed during.. Read More»
Genet. Mol. Res. 15(2): gmr.15027299
DOI: 10.4238/gmr.15027299
This study used Bayesian inference to investigate the genotype x environment interaction in common bean grown in Mato Grosso do Sul State, and it also evaluated the efficiency of using informative and minimally informative a priori distributions. Six trials were conducted in randomized blocks, and the grain yield of 13 common bean genotypes was assessed. To represen.. Read More»
Genet. Mol. Res. 15(2): gmr.15028260
DOI: 10.4238/gmr.15028260
Though the replacement of European bees by Africanized honey bees in tropical America has attracted considerable attention, little is known about the temporal changes in morphological and genetic characteristics in these bee populations. We examined the changes in the morphometric and genetic profiles of an Africanized honey bee population collected near where the o.. Read More»
Genet. Mol. Res. 8(2):
The correct classification of individuals is extremely important for the preservation of genetic variability and for maximization of yield in breeding programs using phenotypic traits and genetic markers. The Fisher and Anderson discriminant functions are commonly used multivariate statistical techniques for these situations, which allow for the allocation of an initially unknown individual to .. Read More»
Genet. Mol. Res. 14(3): 2015.August.19.24
DOI: 10.4238/2015.August.19.24
A significant contribution of molecular genetics is the direct use of DNA information to identify genetically superior individuals. With this approach, genome-wide selection (GWS) can be used for this purpose. GWS consists of analyzing a large number of single nucleotide polymorphism markers widely distributed in the genome; however, because the number of markers is.. Read More»
Genet. Mol. Res. 14(4): 2015.October.9.10
DOI: 10.4238/2015.October.9.10
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