ArticlePlant phenomics (Washington, D.C.)2021
Using Machine Learning to Develop a Fully Automated Soybean Nodule Acquisition Pipeline (SNAP).
Article in Plant phenomics (Washington, D.C.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
18 citing papers in PubMed, 34 citations in OpenAlex.
- Leaf to Root: Harnessing leaf spectral signatures for non-destructive monitoring of soybean nodule traits.Plant phenomics (Washington, D.C.) · 2026Article
- Long-term preservation strategy for legume root nodule phenotypes coupled with a comprehensive evaluation method.BMC plant biology · 2026Article
- YOLO-based high-throughput phenotyping pipeline for soybean nodulation traits in genomic research.Frontiers in plant science · 2026Article
- Molecular Network Analysis in Model and Non-Model Legumes: Challenges in Omics Data Interpretation Across Species, with a Focus onPlants (Basel, Switzerland) · 2025Review
- Integrating Artificial Intelligence and Biotechnology to Enhance Cold Stress Resilience in Legumes.Plants (Basel, Switzerland) · 2025Review
- Research on Fine-Grained Phenotypic Analysis of Temporal Root Systems - Improved YoloV8seg Applied for Fine-Grained Analysis of In Situ Root Temporal Phenotypes.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Harnessing Multi-Omics Strategies and Bioinformatics Innovations for Advancing Soybean Improvement: A Comprehensive Review.Plants (Basel, Switzerland) · 2024Review
- Phenotyping Alfalfa (Plant phenomics (Washington, D.C.) · 2024Article
- Persistent monitoring of insect-pests on sticky traps through hierarchical transfer learning and slicing-aided hyper inference.Frontiers in plant science · 2024Article
- In Situ Root Dataset Expansion Strategy Based on an Improved CycleGAN Generator.Plant phenomics (Washington, D.C.) · 2024Article
- "Canopy fingerprints" for characterizing three-dimensional point cloud data of soybean canopies.Frontiers in plant science · 2023Article
- Self-supervised maize kernel classification and segmentation for embryo identification.Frontiers in plant science · 2023Article
- Application of Improved UNet and EnglightenGAN for Segmentation and Reconstruction of In Situ Roots.Plant phenomics (Washington, D.C.) · 2023Article
- Multi-Omics Techniques for Soybean Molecular Breeding.International journal of molecular sciences · 2022Review
- Deep learning-based phenotyping for genome wide association studies of sudden death syndrome in soybean.Frontiers in plant science · 2022Article
- Deep Multiview Image Fusion for Soybean Yield Estimation in Breeding Applications.Plant phenomics (Washington, D.C.) · 2021Article
- UAS-Based Plant Phenotyping for Research and Breeding Applications.Plant phenomics (Washington, D.C.) · 2021Review
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Nodules form on plant roots through the symbiotic relationship between soybean (
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.