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Article
Extending the marker x environment interaction model for genomic-enabled prediction and genome-wide association analysis in durum wheat
(Crop Science Society of America (CSSA), 2016)
The marker ´ environment interaction (M´E) genomic model can be used to generate predictions for untested individuals and identify genomic regions in which effects are stable across environments and others that show ...
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
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 ...
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
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 ...
Article
An R Package for Bayesian analysis of multi-environment and multi-trait multi-environment data for genome-based prediction
(Genetics Society of America, 2019)
Evidence that genomic selection (GS) is a technology that is revolutionizing plant breeding continues to grow. However, it is very well documented that its success strongly depends on statistical models, which are used by ...
Article
Partial least squares enhances genomic prediction of new environments
(Frontiers, 2022)
Article
Application of multi-trait Bayesian decision theory for parental genomic selection
(Genetics Society of America, 2021)
Article
Bayesian multitrait kernel methods improve multienvironment genome-based prediction
(Oxford University Press, 2022)
Article
Maximum a posteriori Threshold Genomic Prediction model for ordinal traits
(Genetics Society of America, 2020)