Main content area

Comparison of a one- and two-stage mixed model analysis of Australia’s National Variety Trial Southern Region wheat data

Gogel, Beverley, Smith, Alison, Cullis, Brian
Euphytica 2018 v.214 no.2 pp. 44
cultivars, data collection, field experimentation, statistical models, variance, variance covariance matrix, variety trials, wheat, Australia
A one-stage analysis of a series of variety trials involves a combined analysis of the individual plot data across trials. Together with prudent modelling of the genetic effects across trials, this is considered to be the gold standard analysis of multi-environment field trial data. An alternative is a two-stage approach in which the variety means from an analysis of the individual trials in stage one are combined into a weighted mixed model analysis in stage two to give the full set of predicted variety by environment effects and an estimate of their associated variance structure. The two-stage analysis will exactly reproduce the one-stage analysis if the full variance-covariance matrix of the means from stage one is known and is utilised in stage two. Typically the full matrix is not stored and a diagonal approximation is used. This introduces a compromise to the full analysis. The impacts of a diagonal approximation are greater in the presence of sophisticated models for the genetic effects. A second compromise is through a loss of information in estimating the non-genetic variance parameters using the two-stage approach. In this paper we draw a direct link between the one and two-stage analysis approaches for crop variety evaluation data in Australia. We now have the computing power to analyse large and complex multi-environment variety trial data sets using the one-stage approach without the need for a two-stage approximation. This should motivate a move away from the two-stage approach in a range of contexts.