Predicting additive and non-additive genetic effects from trials where traits are affected by interplot competition

Hunt, Colleen H., Smith, Alison B., Jordan, David R. and Cullis, Brian R. (2013) Predicting additive and non-additive genetic effects from trials where traits are affected by interplot competition. Journal of Agricultural Biological and Environmental Statistics, 18 1: 53-63. doi:10.1007/s13253-012-0117-7


Author Hunt, Colleen H.
Smith, Alison B.
Jordan, David R.
Cullis, Brian R.
Title Predicting additive and non-additive genetic effects from trials where traits are affected by interplot competition
Journal name Journal of Agricultural Biological and Environmental Statistics   Check publisher's open access policy
ISSN 1085-7117
1537-2693
Publication date 2013-03-01
Year available 2013
Sub-type Article (original research)
DOI 10.1007/s13253-012-0117-7
Open Access Status Not Open Access
Volume 18
Issue 1
Start page 53
End page 63
Total pages 11
Place of publication New York, United States
Publisher Springer New York LLC
Language eng
Abstract There are two key types of selection in a plant breeding program, namely selection of hybrids for potential commercial use and the selection of parents for use in future breeding. Oakey et al. (in Theoretical and Applied Genetics 113, 809–819, 2006) showed how both of these aims could be achieved using pedigree information in a mixed model analysis in order to partition genetic effects into additive and non-additive effects. Their approach was developed for field trial data subject to spatial variation. In this paper we extend the approach for data from trials subject to interplot competition. We show how the approach may be used to obtain predictions of pure stand additive and non-additive effects. We develop the methodology in the context of a single field trial using an example from an Australian sorghum breeding program.
Keyword Mixed models
Statistical analysis
Variogram
Spatial trends
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: School of Agriculture and Food Sciences
Queensland Alliance for Agriculture and Food Innovation
Official 2014 Collection
 
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