Content area
Full text
Theor Appl Genet (2015) 128:5572 DOI 10.1007/s00122-014-2412-x
ORIGINAL PAPER
Factor analytic mixed models for the provision of grower information from national crop variety testing programs
Alison B. Smith Aanandini Ganesalingam Haydn Kuchel Brian R. Cullis
Abstract
Key message Factor analytic mixed models for national crop variety testing programs have the potential to improve industry productivity through appropriate modelling and reporting to growers of variety by environment interaction.
Abstract Crop variety testing programs are conducted in many countries world-wide. Within each program, data are combined across locations and seasons, and analysed in order to provide information to assist growers in choosing the best varieties for their conditions. Despite major advances in the statistical analysis of multi-environment trial data, such methodology has not been adopted within national variety testing programs. The most commonly used approach involves a variance component model that includes variety and environment main effects, and variety by environment (V E) interaction effects. The variety predictions obtained from such an analysis, and subsequently reported to growers, are typically on a long-term regional basis. In Australia, the variance component model has been found to be inadequate in terms of modelling
Communicated by Jose Crossa.
A. B. Smith (*) B. R. Cullis
National Institute for Applied Statistics Research Australia, University of Wollongong, Wollongong, Australiae-mail: [email protected]
A. Ganesalingam
University of Western Australia, Perth, Australia
H. Kuchel
Australian Grain Technologies, Roseworthy, Australia
B. R. Cullis
Computational Informatics, CSIRO, Canberra, Australia
Received: 16 May 2014 / Accepted: 3 October 2014 / Published online: 19 October 2014 The Author(s) 2014. This article is published with open access at Springerlink.com
V E interaction, and the reporting of information at a regional level often masks important local V E interaction. In contrast, the factor analytic mixed model approach that is widely used in Australian plant breeding programs, has regularly been found to provide a parsimonious and informative model for V E effects, and accurate predictions. In this paper we develop an approach for the analysis of crop variety evaluation data that is based on a factor analytic mixed model. The information obtained from such an analysis may well be superior, but will only enhance industry productivity if mechanisms exist for successful technology transfer. With this in mind, we offer a suggested reporting format...