Now showing items 1-10 of 19
User's guide for spatial analysis of field variety trials using ASREML
This manual describes an approach to the spatial analysis of field experiments based on the software package AS residual maximum likelihood (ASREML; Gilmour et al. 1999). It describes common sources of spatial variation ...
Data analysis in the CIMMYT applied biotechnology center: for fingerprinting and genetic diversity studies
The molecular genetic characterization of the diversity present in the CIMMYT maize and wheat germplasm collections is an ongoing process, to which many different persons have contributed. Furthermore, one of the mandates ...
User's manual for the LCDMV software (calculation software of molecular distances between varieties): for fingerprinting and genetic diversity studies
LCDMV (in English, known as the Calculation Software of Molecular Distances between Varieties) is a computer program developed in the SAS language (SAS Institute Inc., version 6.12), with the help of the modules SAS-STAT, ...
A genomic selection index applied to simulated and real data
(Genetics Society of America, 2015)
A genomic selection index (GSI) is a linear combination of genomic estimated breeding values that uses genomic markers to predict the net genetic merit and select parents from a nonphenotyped testing population. Some authors ...
Increased prediction accuracy in wheat breeding trials using a marker x environment interaction Genomic Selection model
(Genetics Society of America, 2015)
Genomic selection (GS) models use genome-wide genetic information to predict genetic values of candidates of selection. Originally, these models were developed without considering genotype · environment interaction( G·E). ...
Genomic-enabled prediction in maize using kernel models with genotype x environment interaction
(Genetics Society of America, 2017)
Multi-environment trials are routinely conducted in plant breeding to select candidates for the next selection cycle. In this study, we compare the prediction accuracy of four developed genomic-enabled prediction models: ...
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, ...
A general Bayesian estimation method of linear-bilinear models applied to plant breeding trials with genotype × environment interaction
(Springer Verlag; American Statistical Association; International Biometrics Society, 2012)
Statistical analyses of two-way tables with interaction arise in many different fields of research. This study proposes the von Mises-Fisher distribution as a prior on the set of orthogonal matrices in a linear-bilinear ...
Genomic prediction models for count data
(Springer Verlag; American Statistical Association; International Biometrics Society, 2015)
Whole genome prediction models are useful tools for breeders when selecting candidate individuals early in life for rapid genetic gains. However, most prediction models developed so far assume that the response variable ...
Genomic Bayesian functional regression models with interactions for predicting wheat grain yield using hyper‑spectral image data
(BioMed Central, 2017)
Modern agriculture uses hyperspectral cameras that provide hundreds of reflectance data at discrete narrow bands in many environments. These bands often cover the whole visible light spectrum and part of the infrared and ...