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Presentation
Handbook
User's guide for spatial analysis of field variety trials using ASREML
(CIMMYT, 2000)
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 ...
Article
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. ...
Article
Correction to: bayesian functional regression as an alternative statistical analysis of high-throughput phenotyping data of modern agriculture
(BioMed Central, 2018)
Unfortunately, in the original version [1] of this article, a funder note was missed out in the acknowledgement. Te corrected acknowledgement is given below: Acknowledgements Te authors thank all the feld and lab assistants ...
Article
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: ...
Article
Genomic prediction of breeding values when modeling genotype × environment interaction using pedigree and dense molecular markers
(Crop Science Society of America (CSSA), 2012)
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. ...
Article
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 ...
Article
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, ...
Article
A reaction norm model for genomic selection using high-dimensional genomic and environmental data
(Springer, 2013)
In most agricultural crops the effects of genes on traits are modulated by environmental conditions, leading to genetic by environmental interaction (G × E). Modern genotyping technologies allow characterizing genomes in ...
Article
Multivariate bayesian analysis of on-farm trials with multiple-trait and multiple-environment data
(American Society of Agronomy, 2019)