ArticleFrontiers in plant science2020
Genomic Prediction of Agronomic Traits in Common Bean (
Article in Frontiers in plant science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers, 1 of them a synthesis that pooled it.
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Who cites it
49 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Combination of meta-analysis of QTL and GWAS to uncover the genetic architecture of seed yield and seed yield components in common bean.The plant genome · 2023Pooled it
- Beyond Nitrogen Fixation: Multifunctional Roles of Common Bean in Organic Agroecosystems and Ecosystem-Oriented Breeding Strategies.Plants (Basel, Switzerland) · 2026Review
- Prioritization of deleterious mutations informs genomic prediction and increases the rate of gain in common bean (Phaseolus vulgaris L.), a simulation study.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Article
- Image-based high-throughput phenotyping enables genetic analyses of pod morphological traits in mungbean (Vigna radiata (L.) R. Wilczek).G3 (Bethesda, Md.) · 2026Article
- FIP 1.0 soybean data: Insights on soybean growth from eight years of high-throughput image field phenotyping.Scientific data · 2026Article
- Advancing anthracnose resistance in dry beans through the transition from traditional to computational breeding efforts.Frontiers in plant science · 2026Review
- Pod Dehiscence in Soybean: Genome Wide Association Study and Genomic Prediction.Plants (Basel, Switzerland) · 2025Article
- Genomic Prediction of Adaptation in Common Bean (International journal of molecular sciences · 2025Article
- Genetic architecture of ideotype-related traits in middle American beans through single trait, multi-trait and epistatic genome-wide analyses.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Article
- Environment ensemble models for genomic prediction in common bean (Phaseolus vulgaris L.).The plant genome · 2025Article
- Genome-wide association mapping for early maturity in kintoki bean (Breeding science · 2025Article
- GWAS-assisted and multitrait genomic prediction for improvement of seed yield and canning quality traits in a black bean breeding panel.G3 (Bethesda, Md.) · 2025Article
- Improving genomic prediction of vitamin C content in spinach using GWAS-derived markers.BMC genomics · 2025Article
- Genomic Predicted cross performance: a tool for optimizing parental combinations in breeding programs.Database : the journal of biological databases and curation · 2025Article
- The role of pangenomics in orphan crop improvement.Nature communications · 2025Review
- Breeding vegetables for whitefly resistance: past, present, and future in the AI era.Frontiers in plant science · 2025Review
- Consumer traits of common beans: a global and regional perspective on seed coat darkening, cooking time, protein, and mineral content.Frontiers in nutrition · 2025Review
- Comparative Effects of Water Scarcity on the Growth and Development of Two Common Bean (Plants (Basel, Switzerland) · 2024Article
- Simulations of multiple breeding strategy scenarios in common bean for assessing genomic selection accuracy and model updating.The plant genome · 2024Article
- Linking photosynthesis and yield reveals a strategy to improve light use efficiency in a climbing bean breeding population.Journal of experimental botany · 2024Article
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9 authors.
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No grant is acknowledged in the PubMed record.
Abstract
In plant and animal breeding, genomic prediction models are established to select new lines based on genomic data, without the need for laborious phenotyping. Prediction models can be trained on recent or historic phenotypic data and increasingly available genotypic data. This enables the adoption of genomic selection also in under-used legume crops such as common bean. Beans are an important staple food in the tropics and mainly grown by smallholders under limiting environmental conditions such as drought or low soil fertility. Therefore, genotype-by-environment interactions (G × E) are an important consideration when developing new bean varieties. However, G × E are often not considered in genomic prediction models nor are these models implemented in current bean breeding programs. Here we show the prediction abilities of four agronomic traits in common bean under various environmental stresses based on twelve field trials. The dataset includes 481 elite breeding lines characterized by 5,820 SNP markers. Prediction abilities over all twelve trials ranged between 0.6 and 0.8 for yield and days to maturity, respectively, predicting new lines into new seasons. In all four evaluated traits, the prediction abilities reached about 50-80% of the maximum accuracies given by phenotypic correlations and heritability. Predictions under drought and low phosphorus stress were up to 10 and 20% improved when G × E were included in the model, respectively. Our results demonstrate the potential of genomic selection to increase the genetic gain in common bean breeding. Prediction abilities improved when more phenotypic data was available and G × E could be accounted for. Furthermore, the developed models allowed us to predict genotypic performance under different environmental stresses. This will be a key factor in the development of common bean varieties adapted to future challenging conditions.
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