Analysis of yield and oil from a series of canola breeding trials. Part II. Exploring variety by environment interaction using factor analysisThis article is one of a selection of papers from the conference “Exploiting Genome-wide Association in Oilseed Brassicas: a model for genetic improvement of major OECD crops for sustainable farming”.

Author:

Cullis B.R.123,Smith A.B.123,Beeck C.P.123,Cowling W.A.123

Affiliation:

1. School of Mathematics and Applied Statistics, University of Wollongong, Wollongong, NSW 2522, Australia; and Mathematics Informatics and Statistics, CSIRO, Canberra, ACT 2601, Australia.

2. Industry & Innovation NSW, Wagga Wagga Agricultural Institute, Wagga Wagga, NSW 2650, Australia; and Adjunct Assoc. Prof., School of Plant Biology, The University of Western Australia, 35 Stirling Highway, Crawley, WA 6009, Australia

3. International Centre for Plant Breeding Education and Research, School of Plant Biology and The UWA Institute of Agriculture, The University of Western Australia, 35 Stirling Highway, Crawley, WA 6009, Australia; and Canola Breeders Western Australia Pty Ltd., 15/219 Canning Highway South Perth, WA 6151, Australia.

Abstract

Exploring and exploiting variety by environment (V × E) interaction is one of the major challenges facing plant breeders. In paper I of this series, we presented an approach to modelling V × E interaction in the analysis of complex multi-environment trials using factor analytic models. In this paper, we develop a range of statistical tools which explore V × E interaction in this context. These tools include graphical displays such as heat-maps of genetic correlation matrices as well as so-called E-scaled uniplots that are a more informative alternative to the classical biplot for large plant breeding multi-environment trials. We also present a new approach to prediction for multi-environment trials that include pedigree information. This approach allows meaningful selection indices to be formed either for potential new varieties or potential parents.

Publisher

Canadian Science Publishing

Subject

Genetics,Molecular Biology,General Medicine,Biotechnology

Reference13 articles.

1. Analysis of yield and oil from a series of canola breeding trials. Part I. Fitting factor analytic mixed models with pedigree informationThis article is one of a selection of papers from the conference “Exploiting Genome-wide Association in Oilseed Brassicas: a model for genetic improvement of major OECD crops for sustainable farming”.

2. Butler, D.G., Cullis, B.R., Gilmour, A.R., and Gogel, B.J. 2009. ASReml-R reference manual, release 3. Technical report, Queensland Department of Primary Industries.

3. Cockerham, C. 1963. Statistical genetics and plant breeding. In Estimation of genetic variances. Edited by W. Hanson and H. Robinson. NAS-NRC. Washington, D.C., pp. 53–94.

4. Cooper, M., DeLacy, I., and Basford, K. 1996. Relationships among analytical methods used to analyse genotypic adaptation in multi-environment trials. In Plant adaptation and crop improvement. Edited by M. Cooper and G. Hammer. CAB International, Cambridge. pp. 193–224.

5. The biplot graphic display of matrices with application to principal component analysis

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