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Article
Joint use of genome, pedigree, and their interaction with environment for predicting the performance of wheat lines in new environments
(Genetics Society of America, 2019)
Genome-enabled prediction plays an essential role in wheat breeding because it has the potential to increase the rate of genetic gain relative to traditional phenotypic and pedigree-based selection. Since the performance ...
Article
Genome‐based prediction of multiple wheat quality traits in multiple years
(Crop Science Society of America, 2020)
Article
A benchmarking between deep learning, support vector machine and bayesian threshold best linear unbiased prediction for predicting ordinal traits in plant breeding
(Genetics Society of America, 2019)
Genomic selection is revolutionizing plant breeding. However, still lacking are better statistical models for ordinal phenotypes to improve the accuracy of the selection of candidate genotypes. For this reason, in this ...
Article
A bayesian poisson-lognormal model for count data for multiple-trait multiple-environment genomic-enabled prediction
(Genetics Society of America, 2017)
When a plant scientist wishes to make genomic-enabled predictions of multiple traits measured in multiple individuals in multiple environments, the most common strategy for performing the analysis is to use a single trait ...
Article
A singular value decomposition Bayesian multiple-trait and multiple-environment genomic model
(Springer Nature, 2019)
Today, breeders perform genomic-assisted breeding to improve more than one trait. However, frequently there are several traits under study at one time, and the implementation of current genomic multiple-trait and ...
Article
Bayesian multitrait kernel methods improve multienvironment genome-based prediction
(Oxford University Press, 2022)
Article
An R package for multitrait and multienvironment data with the Item-based collaborative filtering algorithm
(Crop Science Society of America, 2018)
The Item-Based Collaborative Filtering for Multitrait and Multienvironment Data (IBCF.MTME) package was developed to implement the item-based collaborative filtering (IBCF) algorithm for continuous phenotypic data in the ...