AI-assisted Image-Based Phenotyping Reveals Genetic Architecture of Pod Traits in Mungbean (Vigna radiata L.)

No abstract is available for this paper.

• Publication year

  2025

• Venue

  bioRxiv

• Publication date

  2025-11-08

• Fields of study

  Agricultural and Food Sciences, Computer Science, Biology, Environmental Science

• Identifiers
  DOI 10.1101/2025.11.06.687031
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Pod-pose : an efficient top-down keypoint detection model for fine-grained pod phenotyping in mature soybean

  2025cited by this paper
• EnsembleEdgeFusion: advancing semantic segmentation in microvascular decompression imaging with innovative ensemble techniques

  2025cited by this paper
• Expanding genomic prediction in plant breeding: harnessing big data, machine learning, and advanced software.

  2025cited by this paper
• Differential ion transport mechanisms in arabidopsis and crops.

  2025cited by this paper
• Dissecting the genetic and phenotypic basis of salinity tolerance in mungbean: insights from multi-stage phenotyping, GWAS and genomic prediction

  2025cited by this paper
• Arabidopsis HAK5 under low K+ availability operates as PMF powered high-affinity K+ transporter

  2024cited by this paper
• Combining GWAS and comparative genomics to fine map candidate genes for days to flowering in mung bean

  2024cited by this paper
• Deciphering PDH1's role in mung bean domestication: a genomic perspective on pod dehiscence.

  2024influential reference
• High-throughput soybean pods high-quality segmentation and seed-per-pod estimation for soybean plant breeding

  2024cited by this paper
• Advancing crop improvement through GWAS and beyond in mung bean

  2024cited by this paper
• Genomic and phenomic prediction for soybean seed yield, protein, and oil

  2024cited by this paper
• Comparative Study of Single-Trait and Multi-Trait Genomic Prediction Models

  2024cited by this paper
• Leveraging genomics and phenomics to accelerate improvement in mungbean: A case study in how to go from GWAS to selection

  2023cited by this paper
• Genetic control of pod morphological traits and pod edibility in a common bean RIL population

  2023cited by this paper
• Satellite imagery for high-throughput phenotyping in breeding plots

  2023cited by this paper
• An improved Deeplabv3+ semantic segmentation algorithm with multiple loss constraints

  2022cited by this paper
• Genetic dissection of and genomic selection for seed weight, pod length, and pod width in soybean

  2022cited by this paper
• Resequencing of 558 Chinese mungbean landraces identifies genetic loci associated with key agronomic traits

  2022cited by this paper
• A Comprehensive Review of High Throughput Phenotyping and Machine Learning for Plant Stress Phenotyping

  2022cited by this paper
• Dissecting the Root Phenotypic and Genotypic Variability of the Iowa Mung Bean Diversity Panel

  2022cited by this paper
• High-Throughput Plant Phenotyping Platform (HT3P) as a Novel Tool for Estimating Agronomic Traits From the Lab to the Field

  2021cited by this paper
• Advanced high-throughput plant phenotyping techniques for genome-wide association studies: A review

  2021cited by this paper
• Exploring genetic architecture for pod-related traits in soybean using image-based phenotyping

  2021cited by this paper
• GWAS of pod morphological and color characters in common bean

  2021cited by this paper
• High-Throughput in situ Root Image Segmentation Based on the Improved DeepLabv3+ Method

  2020cited by this paper
• Global Status and Economic Importance of Mungbean

  2020cited by this paper
• SeedExtractor: An Open-Source GUI for Seed Image Analysis

  2020cited by this paper
• Genomic Prediction of Agronomic Traits in Common Bean (Phaseolus vulgaris L.) Under Environmental Stress

  2020cited by this paper
• Strategies for the utilization of the USDA mung bean germplasm collection for breeding outcomes

  2020influential reference
• Pod indehiscence in common bean is associated with the fine regulation of PvMYB26

  2020cited by this paper
• Sequenceserver: A Modern Graphical User Interface for Custom BLAST Databases

  2019influential reference
• Benchmarking Parametric and Machine Learning Models for Genomic Prediction of Complex Traits

  2019cited by this paper
• Identification of QTL controlling domestication-related traits in cowpea (Vigna unguiculata L. Walp)

  2018cited by this paper
• BLINK: a package for the next level of genome-wide association studies with both individuals and markers in the millions

  2018influential reference
• Translating High-Throughput Phenotyping into Genetic Gain

  2018cited by this paper
• Genomic Prediction of Breeding Values Using a Subset of SNPs Identified by Three Machine Learning Methods

  2018cited by this paper
• A high resolution map of the Arabidopsis thaliana developmental transcriptome based on RNA-seq profiling.

  2016cited by this paper
• Iterative Usage of Fixed and Random Effect Models for Powerful and Efficient Genome-Wide Association Studies

  2016cited by this paper
• Genomic regions, cellular components and gene regulatory basis underlying pod length variations in cowpea (V. unguiculata L. Walp)

  2016cited by this paper
• Legume information system (LegumeInfo.org): a key component of a set of federated data resources for the legume family

  2015cited by this paper
• Clumpak: a program for identifying clustering modes and packaging population structure inferences across K

  2015cited by this paper
• Genome sequence of mungbean and insights into evolution within Vigna species

  2014cited by this paper
• Molecular basis of a shattering resistance boosting global dissemination of soybean

  2014cited by this paper
• Analysis of Maize (Zea mays L.) Seedling Roots with the High-Throughput Image Analysis Tool ARIA (Automatic Root Image Analysis)

  2014cited by this paper
• A novel perspective on seed yield of broad bean (Vicia faba L.): differences resulting from pod characteristics

  2014cited by this paper
• STRUCTURE HARVESTER: a website and program for visualizing STRUCTURE output and implementing the Evanno method

  2012cited by this paper
• Scikit-learn: Machine Learning in Python

  2011influential reference
• Mixed linear model approach adapted for genome-wide association studies

  2010cited by this paper
• On the design of early generation variety trials with correlated data

  2006cited by this paper
• Detecting the number of clusters of individuals using the software structure: a simulation study

  2005cited by this paper
• Structure of linkage disequilibrium and phenotypic associations in the maize genome

  2001cited by this paper
• Improving the accuracy of PSI-BLAST protein database searches with composition-based statistics and other refinements.

  2001cited by this paper
• Inference of population structure using multilocus genotype data.

  2000influential reference
• Variances and covariances of squared linkage disequilibria in finite populations.

  1988cited by this paper

• No citing papers are available for this paper.