Now showing items 1-10 of 45
Prediction of Genetic Values of Quantitative Traits in Plant Breeding Using Pedigree and Molecular Markers
The availability of dense molecular markers has made possible the use of genomic selection (GS) for plant breeding. However, the evaluation of models for GS in real plant populations is very limited. This article evaluates ...
Genomic prediction of genetic values for resistance to wheat rusts
Durable resistance to the rust diseases of wheat (Triticum aestivum L.) can be achieved by developing lines that have race-nonspecific adult plant resistance conferred by multiple minor slow-rusting genes. Genomic selection ...
Genomic prediction of breeding values when modeling genotype × environment interaction using pedigree and dense molecular markers
Genomic selection (GS) has become an important aid in plant and animal breeding. Multienvironment (multitrait) models allow borrowing of information across environments (traits), which could enhance prediction accuracy. ...
A Bayesian decision theory approach for genomic selection
(Genetics Society of America, 2018)
Plant and animal breeders are interested in selecting the best individuals from a candidate set for the next breeding cycle. In this paper, we propose a formal method under the Bayesian decision theory framework to tackle ...
Genomic prediction in maize breeding populations with genotyping-by sequencing
(Genetics Society of America, 2013)
Genotyping-by-sequencing (GBS) technologies have proven capacity for delivering large numbers of marker genotypes with potentially less ascertainment bias than standard single nucleotide polymorphism (SNP) arrays. Therefore, ...
Genomic bayesian prediction model for count data with genotype X environment interaction
(Genetics Society of America, 2016)
Genomic tools allow the study of the whole genome and are facilitating the study of genotype-environment combinations and their relationship with phenotype. However, most genomic prediction models developed so far are ...
Bayesian functional regression as an alternative statistical analysis of high-throughput phenotyping data of modern agriculture
(BioMed Central, 2018)
Background: Modern agriculture uses hyperspectral cameras with hundreds of reflectance data at discrete narrow bands measured in several environments. Recently, Montesinos-López et al. (Plant Methods 13(4):1-23, 2017a. ...
Bayesian functional regression as an alternative statistical analysis of high‑throughput phenotyping data of modern agriculture
(BioMed Central, 2018)
Background: Modern agriculture uses hyperspectral cameras with hundreds of reflectance data at discrete narrow bands measured in several environments. Recently, Montesinos-López et al. (Plant Methods 13(4):1–23, 2017a. ...
Using factor analytic models for joining environments and genotypes without crossover genotype x environment interaction
Genotype x environment interaction variability can be due to crossover interaction (COI) or to non-COI. Statistical methods for detecting and quantifying COI and for forming subsets of environments and/or genotypes with ...