ArticleFrontiers in plant science2019
Genomic Selection in Rubber Tree Breeding: A Comparison of Models and Methods for Managing G×E Interactions.
Article in Frontiers in plant science, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- The haplotype-resolved telomere-to-telomere genome and OMICS analyses reveal genetic responses to tapping in rubber tree.Nature communications · 2025Article
- Article
- Genomic selection for genotype performance and environmental stability in Coffea canephora.G3 (Bethesda, Md.) · 2023Article
- Chromosome-level wild Hevea brasiliensis genome provides new tools for genomic-assisted breeding and valuable loci to elevate rubber yield.Plant biotechnology journal · 2023Article
- A divide-and-conquer approach for genomic prediction in rubber tree using machine learning.Scientific reports · 2022Article
- Genomic selection in tropical perennial crops and plantation trees: a review.Molecular breeding : new strategies in plant improvement · 2022Review
- Exploring methods to summarize gut microbiota composition for microbiability estimation and phenotypic prediction in swine.Journal of animal science · 2022Article
- Recent insights on gene expression studies onPhysiology and molecular biology of plants : an international journal of functional plant biology · 2022Review
- Phenotypic Trait Subdivision Provides New Sight Into the Directional Improvement ofFrontiers in plant science · 2022Article
- Genomic Prediction of Complex Traits in Perennial Plants: A Case for Forest Trees.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Achievements and Challenges of Genomics-Assisted Breeding in Forest Trees: From Marker-Assisted Selection to Genome Editing.International journal of molecular sciences · 2021Review
- Genome editing in fruit, ornamental, and industrial crops.Transgenic research · 2021Review
- Unravelling Rubber Tree Growth by Integrating GWAS and Biological Network-Based Approaches.Frontiers in plant science · 2021Article
- Favorable Conditions for Genomic Evaluation to Outperform Classical Pedigree Evaluation Highlighted by a Proof-of-Concept Study in Poplar.Frontiers in plant science · 2020Article
- Modern Strategies to Assess and Breed Forest Tree Adaptation to Changing Climate.Frontiers in plant science · 2020Review
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Several genomic prediction models combining genotype × environment (G×E) interactions have recently been developed and used for genomic selection (GS) in plant breeding programs. G×E interactions reduce selection accuracy and limit genetic gains in plant breeding. Two data sets were used to compare the prediction abilities of multienvironment G×E genomic models and two kernel methods. Specifically, a linear kernel, or GB (genomic best linear unbiased predictor [GBLUP]), and a nonlinear kernel, or Gaussian kernel (GK), were used to compare the prediction accuracies (PAs) of four genomic prediction models: 1) a single-environment, main genotypic effect model (SM); 2) a multienvironment, main genotypic effect model (MM); 3) a multienvironment, single-variance G×E deviation model (MDs); and 4) a multienvironment, environment-specific variance G×E deviation model (MDe). We evaluated the utility of genomic selection (GS) for 435 individual rubber trees at two sites and genotyped the individuals
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