ArticleFrontiers in plant science2022
Deep learning-based phenotyping for genome wide association studies of sudden death syndrome in soybean.
Article in Frontiers in plant science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Integrative genomics and zero-shot deep learning-based phenotyping reveal the genetic architecture of seed traits in mungbean (Vigna radiata L.).The plant genome · 2026Article
- Association Mapping of Seedling Resistance toPlants (Basel, Switzerland) · 2026Article
- Genome-wide association study of post-harvest physiological deterioration in cassava (Frontiers in plant science · 2026Article
- Gradient responsive regularization: a deep learning framework for codon frequency based classification of evolutionarily conserved genes.BMC genomic data · 2025Article
- Genomic and phenomic prediction for soybean seed yield, protein, and oil.The plant genome · 2025Article
- Soybean genomics research community strategic plan: A vision for 2024-2028.The plant genome · 2024Article
- Multi-sensor and multi-temporal high-throughput phenotyping for monitoring and early detection of water-limiting stress in soybean.Plant phenome journal · 2024Article
- Genome-Wide Association Study and Marker Development forInternational journal of molecular sciences · 2024Article
- Genetic Analysis of Soybean Flower Size Phenotypes Based on Computer Vision and Genome-Wide Association Studies.International journal of molecular sciences · 2024Article
- Persistent monitoring of insect-pests on sticky traps through hierarchical transfer learning and slicing-aided hyper inference.Frontiers in plant science · 2024Article
- BreedingFrontiers in plant science · 2024Review
- "Canopy fingerprints" for characterizing three-dimensional point cloud data of soybean canopies.Frontiers in plant science · 2023Article
- Transvaginal natural orifice endoscopic surgery for ovarian cystectomy: a more suitable surgical approach for the day-care procedure.Frontiers in medicine · 2023Article
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Using a reliable and accurate method to phenotype disease incidence and severity is essential to unravel the complex genetic architecture of disease resistance in plants, and to develop disease resistant cultivars. Genome-wide association studies (GWAS) involve phenotyping large numbers of accessions, and have been used for a myriad of traits. In field studies, genetic accessions are phenotyped across multiple environments and replications, which takes a significant amount of labor and resources. Deep Learning (DL) techniques can be effective for analyzing image-based tasks; thus DL methods are becoming more routine for phenotyping traits to save time and effort. This research aims to conduct GWAS on sudden death syndrome (SDS) of soybean [
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