ArticleJournal of experimental botany2015
Genome-wide association study of rice (Oryza sativa L.) leaf traits with a high-throughput leaf scorer.
Article in Journal of experimental botany, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers.
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Who cites it
51 citing papers in PubMed.
- Genome-Wide Association Analysis of Gibberellin Sensitivity for Panicle Exsertion Length in Rice and Candidate Gene Identification.Plants (Basel, Switzerland) · 2026Article
- High-Throughput Phenotyping: Status and Applications in Rice Breeding.Plants (Basel, Switzerland) · 2026Review
- Review
- Elite Alleles of EPE1 Identified via Genome-wide Association Studies Increase Panicle Elongation Length in Rice.Rice (New York, N.Y.) · 2025Article
- TPS5 and TOR signaling components are determinants ofFrontiers in plant science · 2025Article
- Integrating dynamic high-throughput phenotyping and genetic analysis to monitor growth variation in foxtail millet.Plant methods · 2024Article
- Exploring natural genetic variation in photosynthesis-related traits of barley in the field.Journal of experimental botany · 2024Article
- Genome wide association studies on seven yield-related traits of 183 rice varieties in Bangladesh.Plant direct · 2024Article
- GWAS supported by computer vision identifies large numbers of candidate regulators of in planta regeneration in Populus trichocarpa.G3 (Bethesda, Md.) · 2024Article
- Crop Leaf Phenotypic Parameter Measurement Based on the RKM-D Point Cloud Method.Sensors (Basel, Switzerland) · 2024Article
- Morphological and Genomic Differences in the Italian Populations ofPlants (Basel, Switzerland) · 2024Article
- A High-Throughput Method for Accurate Extraction of Intact Rice Panicle Traits.Plant phenomics (Washington, D.C.) · 2024Article
- An Overview of High-Throughput Crop Phenotyping: Platform, Image Analysis, Data Mining, and Data Management.Methods in molecular biology (Clifton, N.J.) · 2024Review
- Genetic architecture of leaf morphology revealed by integrated trait module inHorticulture research · 2023Article
- Multi-model genome-wide association studies of leaf anatomical traits and vein architecture in rice.Frontiers in plant science · 2023Article
- Crop/Plant Modeling Supports Plant Breeding: II. Guidance of Functional Plant Phenotyping for Trait Discovery.Plant phenomics (Washington, D.C.) · 2023Review
- Leaf Count Aided Novel Framework for Rice (Plants (Basel, Switzerland) · 2022Article
- Revitalization of small millets for nutritional and food security by advanced genetics and genomics approaches.Frontiers in genetics · 2022Review
- Dissecting the Genetic Structure of Maize Leaf Sheaths at Seedling Stage by Image-Based High-Throughput Phenotypic Acquisition and Characterization.Frontiers in plant science · 2022Article
- Advanced high-throughput plant phenotyping techniques for genome-wide association studies: A review.Journal of advanced research · 2022Review
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Leaves are the plant's solar panel and food factory, and leaf traits are always key issues to investigate in plant research. Traditional methods for leaf trait measurement are time-consuming. In this work, an engineering prototype has been established for high-throughput leaf scoring (HLS) of a large number of Oryza sativa accessions. The mean absolute per cent of errors in traditional measurements versus HLS were below 5% for leaf number, area, shape, and colour. Moreover, HLS can measure up to 30 leaves per minute. To demonstrate the usefulness of HLS in dissecting the genetic bases of leaf traits, a genome-wide association study (GWAS) was performed for 29 leaf traits related to leaf size, shape, and colour at three growth stages using HLS on a panel of 533 rice accessions. Nine associated loci contained known leaf-related genes, such as Nal1 for controlling the leaf width. In addition, a total of 73, 123, and 177 new loci were detected for traits associated with leaf size, colour, and shape, respectively. In summary, after evaluating the performance with a large number of rice accessions, the combination of GWAS and high-throughput leaf phenotyping (HLS) has proven a valuable strategy to identify the genetic loci controlling rice leaf traits.
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