BLUP for phenotypic selection in plant breeding and variety testing
 H. P. Piepho,
 J. Möhring,
 A. E. Melchinger,
 A. Büchse
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Best linear unbiased prediction (BLUP) is a standard method for estimating random effects of a mixed model. This method was originally developed in animal breeding for estimation of breeding values and is now widely used in many areas of research. It does not, however, seem to have gained the same popularity in plant breeding and variety testing as it has in animal breeding. In plants, application of mixed models with random genetic effects has up until recently been mainly restricted to the estimation of genetic and nongenetic components of variance, whereas estimation of genotypic values is mostly based on a model with fixed effects. This paper reviews recent developments in the application of BLUP in plant breeding and variety testing. These include the use of pedigree information to model and exploit genetic correlation among relatives and the use of flexible variance–covariance structures for genotypebyenvironment interaction. We demonstrate that BLUP has good predictive accuracy compared to other procedures. While pedigree information is often included via the socalled numerator relationship matrix \(({\user2{A}})\) , we stress that it is frequently straightforward to exploit the same information by a simple mixed model without explicit reference to the \({\user2{A}}\) matrix.
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 Title
 BLUP for phenotypic selection in plant breeding and variety testing
 Journal

Euphytica
Volume 161, Issue 12 , pp 209228
 Cover Date
 20080501
 DOI
 10.1007/s1068100794498
 Print ISSN
 00142336
 Online ISSN
 15735060
 Publisher
 Springer Netherlands
 Additional Links
 Topics
 Keywords

 Mixed model
 Breeding value
 Pedigree
 Genetic effect
 Genotypic value
 Industry Sectors
 Authors

 H. P. Piepho ^{(1)}
 J. Möhring ^{(1)}
 A. E. Melchinger ^{(1)}
 A. Büchse ^{(1)}
 Author Affiliations

 1. Bioinformatics Unit, University of Hohenheim, Fruwirthstrasse 23, 70599, Stuttgart, Germany