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Development of models to predict genotype by environment interactions, in unobserved environments, using environmental covariates, a crop model and genomic selection. Application to a large winter wheat dataset. Genotype by environment interaction (G*E) is one of the key issues when analyzing phenotypes. The use of environment data to model G*E has long(More)
In this article, we propose several new approaches for post processing a large ensemble of conjunctive rules for supervised, semi-supervised and unsupervised learning problems. We show with various examples that for high dimensional regression problems the models constructed by post processing the rules with partial least squares regression have(More)
Population structure must be evaluated before optimization of the training set population. Maximizing the phenotypic variance captured by the training set is important for optimal performance. The optimization of the training set (TRS) in genomic selection has received much interest in both animal and plant breeding, because it is critical to the accuracy(More)
In plant and animal breeding studies a distinction is made between the genetic value (additive plus epistatic genetic effects) and the breeding value (additive genetic effects) of an individual since it is expected that some of the epistatic genetic effects will be lost due to recombination. In this article, we argue that the breeder can take advantage of(More)
This study examines genomic prediction within 8416 Mexican landrace accessions and 2403 Iranian landrace accessions stored in gene banks. The Mexican and Iranian collections were evaluated in separate field trials, including an optimum environment for several traits, and in two separate environments (drought, D and heat, H) for the highly heritable traits,(More)
In this article, we propose an approach to breeding which focuses on mating instead of truncation selection, our method uses genome-wide marker information in a similar fashion to genomic selection so we refer it to as genomic mating. Using concepts of estimated breeding values, risk (usefulness) and inbreeding, an efficient mating approach is formulated(More)
In statistical genetics an important task involves building predictive models for the genotype-phenotype relationships and thus attribute a proportion of the total pheno-typic variance to the variation in genotypes. Numerous models have been proposed to incorporate additive genetic effects into models for prediction or association. However, there is a(More)
In this article, we imagine a breeding scenario with a population of individuals that have been genotyped but not phenotyped. We derived a computationally efficient statistic that uses this genetic information to measure the reliability of genomic estimated breeding values (GEBV) for a given set of individuals (test set) based on a training set of(More)