ArticleFrontiers in plant science2021
Plant Variety Selection Using Interaction Classes Derived From Factor Analytic Linear Mixed Models: Models With Independent Variety Effects.
Article in Frontiers in plant science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
- Optimizing multi-trait selection for profitability in Illinois wheat using a factor analytic mixed model and an economic selection index.The plant genome · 2026Article
- A haplotype-based approach to explore genotype-by-environment interactions for barley yield.The plant genome · 2026Article
- From family trials to genomic mate allocation: statistical and genomic strategies to accelerate sugarcane genetic improvement.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Review
- Envirotyping-driven strategies to enhance soybean adaptation across Southern Africa.Scientific reports · 2026Article
- Genetic analysis of biomass yield and related traits for hybrid cultivar development in the leafy vegetable Gynandropsis gynandra (L.) Briq.BMC plant biology · 2026Article
- Towards a sweetpotato genomic-enabled breeding: optimizing two-stage analysis of multi-environment augmented trials.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Article
- Exploring standing genetic variation for barley leaf rust resistance in Australian breeding panel.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Article
- High-resolution soybean trial data supporting the expansion of agriculture in Africa.Scientific data · 2025Article
- Enhancing enviromics based predictions in common bean multi-environment trials.Scientific reports · 2025Article
- Prediction of Australian wheat genotype by environment interactions and mega-environments.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Article
- A large-scale multi-environment study dissecting adult-plant resistance haplotypes for stripe rust resistance in Australian wheat breeding populations.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Article
- Incorporating gene expression and environment for genomic prediction in wheat.Frontiers in plant science · 2025Article
- Optimizing soybean variety selection for the Pan-African Trial network using factor analytic models and envirotyping.Frontiers in plant science · 2025Article
- Factor analytic selection tools and environmental feature-integration enable holistic decision-making in Eucalyptus breeding.Scientific reports · 2024Article
- Envirotyping within a multi-environment trial allowed identifying genetic determinants of winter oilseed rape yield stability.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024Article
- A comprehensive multivariate approach for GxE interaction analysis in early maturing rice varieties.Frontiers in plant science · 2024Article
- Image-based phenomic prediction can provide valuable decision support in wheat breeding.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2023Article
- Partitioning the forms of genotype-by-environment interaction in the reaction norm analysis of stability.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2023Article
- Extending the breeder's equation to take aim at the target population of environments.Frontiers in plant science · 2023Article
- Nested association mapping-based GWAS for grain yield and related traits in wheat grown under diverse Australian environments.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2022Article
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Abstract
A major challenge in the analysis of plant breeding multi-environment datasets is the provision of meaningful and concise information for variety selection in the presence of variety by environment interaction (VEI). This is addressed in the current paper by fitting a factor analytic linear mixed model (FALMM) then using the fundamental factor analytic parameters to define groups of environments in the dataset within which there is minimal crossover VEI, but between which there may be substantial crossover VEI. These groups are consequently called interaction classes (iClasses). Given that the environments within an iClass exhibit minimal crossover VEI, it is then valid to obtain predictions of overall variety performance (across environments) for each iClass. These predictions can then be used not only to select the best varieties within each iClass but also to match varieties in terms of their patterns of VEI across iClasses. The latter is aided with the use of a new graphical tool called an iClass Interaction Plot. The ideas are introduced in this paper within the framework of FALMMs in which the genetic effects for different varieties are assumed independent. The application to FALMMs which include information on genetic relatedness is the subject of a subsequent paper.
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