Analyzing variety by environment data using multiplicative mixed models and adjustments for spatial field trend

A - Papers appearing in refereed journals

Smith, A., Cullis, B. R. and Thompson, R. 2001. Analyzing variety by environment data using multiplicative mixed models and adjustments for spatial field trend. Biometrics. 57 (4), pp. 1138-1147.

AuthorsSmith, A., Cullis, B. R. and Thompson, R.
Abstract

The recommendation of new plant varieties for commercial use requires reliable and accurate predictions of the average yield of each variety across a range of target environments and knowledge of important interactions with the environment. This information is obtained from series of plant variety trials, also known as multi-environment trials (MET). Cullis, Cogel, Verbyla, and Thompson (1998) presented a spatial mixed model approach for the analysis of MET data. In this paper we extend the analysis to include multiplicative models for the variety effects in each environment. The multiplicative model corresponds to that used in the multivariate technique of factor analysis. It allows a separate genetic variance for each environment and provides a parsimonious and interpretable model for the genetic covariances between environments. The model can be regarded as a random effects analogue of AMMI (additive main effects and multiplicative interactions). We illustrate the method using a large set of MET data from a South Australian barley breeding program.

KeywordsBiology; Mathematical & Computational Biology; Statistics & Probability
Year of Publication2001
JournalBiometrics
Journal citation57 (4), pp. 1138-1147
Digital Object Identifier (DOI)doi:10.1111/j.0006-341X.2001.01138.x
PubMed ID11764254
Open accessPublished as non-open access
Funder project or code445
513
Research in statistics relevant to biological processes
Output statusPublished
Publication dates
Print01 Dec 2001
Publication process dates
Accepted01 Jun 2001
Copyright licensePublisher copyright
PublisherWiley
ISSN0006-341X

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