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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
Effect of leaf rust on grain yield and yield traits of durum wheats with race-specific and slow-rusting resistance to leaf rust
(American Phytopathological Society (APS), 2006)
Leaf rust, caused by Puccinia triticina, is an important disease of durum wheat (Triticum turgidum) in many countries. We compared the effectiveness of different types of resistance in International Maize and Wheat Improvement ...
Article
Genomic prediction of genetic values for resistance to wheat rusts
(Crop Science Society of America, 2012)
Durable resistance to the rust diseases of wheat (Triticum aestivum L.) can be achieved by developing lines that have race-nonspecific adult plant resistance conferred by multiple minor slow-rusting genes. Genomic selection ...
Article
Multi-trait and multi-environment QTL analyses for resistance to wheat diseases
(Public Library of Science, 2012)
Background: Stripe rust, leaf rust, tan spot, and Karnal bunt are economically significant diseases impacting wheat production. The objectives of this study were to identify quantitative trait loci for resistance to these ...
Book
Partner survey for the CGIAR Research Program WHEAT: national and international priorities and engagement
(CGIAR, 2014)
This document analyzes 92 responses to a 2012 survey sent by the CGIAR Research Program WHEAT to its more than 200 partners regarding their institutional priorities, engagement and activities under WHEAT strategic initiatives, ...
Article
Comparison between linear and non-parametric regression models for genome-enabled prediction in wheat
(Genetics Society of America, 2012)
In genome-enabled prediction, parametric, semi-parametric, and non-parametric regression models have been used. This study assessed the predictive ability of linear and non-linear models using dense molecular markers. The ...