Some vocabulary and grammar for the analysis of multi-environment trials, as applied to the analysis of FPB and PPB trials

van Eeuwijk, F. A., Cooper, M., DeLacy, I. H., Ceccarelli, S. and Grando, S. (2001) Some vocabulary and grammar for the analysis of multi-environment trials, as applied to the analysis of FPB and PPB trials. Euphytica, 122 3: 477-490. doi:10.1023/A:1017591407285


Author van Eeuwijk, F. A.
Cooper, M.
DeLacy, I. H.
Ceccarelli, S.
Grando, S.
Title Some vocabulary and grammar for the analysis of multi-environment trials, as applied to the analysis of FPB and PPB trials
Journal name Euphytica   Check publisher's open access policy
ISSN 0014-2336
Publication date 2001
Sub-type Article (original research)
DOI 10.1023/A:1017591407285
Volume 122
Issue 3
Start page 477
End page 490
Total pages 14
Editor E. Jacobsen
Place of publication Dordrecht, The Netherlands
Publisher Kluwer Academic Publishers
Collection year 2001
Language eng
Subject C1
300203 Plant Improvement (Selection, Breeding and Genetic Engineering)
620102 Barley
Abstract For the improvement of genetic material suitable for on farm use under low-input conditions, participatory and formal plant breeding strategies are frequently presented as competing options. A common frame of reference to phrase mechanisms and purposes related to breeding strategies will facilitate clearer descriptions of similarities and differences between participatory plant breeding and formal plant breeding. In this paper an attempt is made to develop such a common framework by means of a statistically inspired language that acknowledges the importance of both on farm trials and research centre trials as sources of information for on farm genetic improvement. Key concepts are the genetic correlation between environments, and the heterogeneity of phenotypic and genetic variance over environments. Classic selection response theory is taken as the starting point for the comparison of selection trials (on farm and research centre) with respect to the expected genetic improvement in a target environment (low-input farms). The variance-covariance parameters that form the input for selection response comparisons traditionally come from a mixed model fit to multi-environment trial data. In this paper we propose a recently developed class of mixed models, namely multiplicative mixed models, also called factor-analytic models, for modelling genetic variances and covariances (correlations). Mixed multiplicative models allow genetic variances and covariances to be dependent on quantitative descriptors of the environment, and confer a high flexibility in the choice of variance-covariance structure, without requiring the estimation of a prohibitively high number of parameters. As a result detailed considerations regarding selection response comparisons are facilitated. ne statistical machinery involved is illustrated on an example data set consisting of barley trials from the International Center for Agricultural Research in the Dry Areas (ICARDA). Analysis of the example data showed that participatory plant breeding and formal plant breeding are better interpreted as providing complementary rather than competing information.
Keyword Agronomy
Plant Sciences
Horticulture
Correlated Response
Factor-analytic Model
Formal Plant Breeding
Genetic Correlation
Genetic Variance
Genotype By Environment Interaction
Heterogeneity Of Variance
Mixed Models
Multi-environment Trials
Participatory Plant Breeding
Affecting Grain-sorghum
Genotype
Variance
Selection
Patterns
Variety
Barley
Yield
Reml
Q-Index Code C1

Document type: Journal Article
Sub-type: Article (original research)
Collection: School of Agriculture and Food Sciences
 
Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 28 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 31 times in Scopus Article | Citations
Google Scholar Search Google Scholar
Created: Tue, 14 Aug 2007, 16:25:40 EST