Genome · 2010 · 115 citations · 9 references
Environment InteractionGeneticsV × EAgricultural EconomicsGenomicsGenomic SelectionCrop ImprovementApplied GeneticsStatistical AnalysisGenotype-phenotype AssociationMolecular EcologySustainable AgricultureBiostatisticsMajor Oecd CropsPublic HealthStatisticsQuantitative GeneticsAgricultural GeneticsStatistical GeneticsMolecular BreedingAgricultural BiotechnologyGenetic VariationPlant BreedersPopulation GeneticsPlant BreedingCanola Breeding TrialsComplex Multi-environment TrialsCrop ProtectionMedicineSeed Processing
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.
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Finding groups in data: an introduction to cluster analysis
Choice Reviews Online · 1991 · 10.6K citations
Fred A. van Eeuwijk, Marcos Malosetti, Xinyou Yin et al. · Australian Journal of Agricultural Research · 2005 · 130 citations · Full text