ArticlePlant methods2017
Leaf-GP: an open and automated software application for measuring growth phenotypes for arabidopsis and wheat.
Article in Plant methods, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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Who cites it
26 citing papers in PubMed.
- ELMERF: A deep-learning-assisted hydroponic RGB phenotyping framework for rice seedling salt-stress evaluation and genetic mapping.Plant phenomics (Washington, D.C.) · 2026Article
- Enhancement of neem growth and wood quality via humic acid and seaweed extract application under treated wastewater irrigation in arid environments.Scientific reports · 2026Article
- PTV2-Fr: a point cloud segmentation network for phenotypic trait extraction and gibberellin effect analysis in sorghum seedlings.Frontiers in plant science · 2026Article
- Rapid acquisition of ionomic and morphological data from plant seeds through fast X-ray fluorescence microscopy and computer vision.Plant phenomics (Washington, D.C.) · 2025Article
- Zero-shot instance segmentation for plant phenotyping in vertical farming with foundation models and VC-NMS.Frontiers in plant science · 2025Article
- New-generation rice seed germination assessment: high efficiency and flexibility via SeedRuler web-based platform.Frontiers in plant science · 2025Article
- ScAnalyzer: an image processing tool to monitor plant disease symptoms and pathogen spread in Arabidopsis thaliana leaves.Plant methods · 2024Article
- AraDQ: an automated digital phenotyping software for quantifying disease symptoms of flood-inoculated Arabidopsis seedlings.Plant methods · 2024Article
- Auto-LIA: The Automated Vision-Based Leaf Inclination Angle Measurement System Improves Monitoring of Plant Physiology.Plant phenomics (Washington, D.C.) · 2024Article
- High-Throughput Field Plant Phenotyping: A Self-Supervised Sequential CNN Method to Segment Overlapping Plants.Plant phenomics (Washington, D.C.) · 2023Article
- A low-cost and open-source solution to automate imaging and analysis of cyst nematode infection assays for Arabidopsis thaliana.Plant methods · 2022Article
- Phosphorylation of the FACT histone chaperone subunit SPT16 affects chromatin at RNA polymerase II transcriptional start sites in Arabidopsis.Nucleic acids research · 2022Article
- Large-scale field phenotyping using backpack LiDAR and CropQuant-3D to measure structural variation in wheat.Plant physiology · 2021Article
- Review
- MFCIS: an automatic leaf-based identification pipeline for plant cultivars using deep learning and persistent homology.Horticulture research · 2021Article
- Maize-IAS: a maize image analysis software using deep learning for high-throughput plant phenotyping.Plant methods · 2021Article
- KAT4IA:Plant phenomics (Washington, D.C.) · 2021Article
- Roles of DNA Methylation in Cold Priming in Tartary Buckwheat.Frontiers in plant science · 2020Article
- A photometric stereo-based 3D imaging system using computer vision and deep learning for tracking plant growth.GigaScience · 2019Article
- CropSight: a scalable and open-source information management system for distributed plant phenotyping and IoT-based crop management.GigaScience · 2019Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
backgroundPlants demonstrate dynamic growth phenotypes that are determined by genetic and environmental factors. Phenotypic analysis of growth features over time is a key approach to understand how plants interact with environmental change as well as respond to different treatments. Although the importance of measuring dynamic growth traits is widely recognised, available open software tools are limited in terms of batch image processing, multiple traits analyses, software usability and cross-referencing results between experiments, making automated phenotypic analysis problematic.
resultsHere, we present Leaf-GP (Growth Phenotypes), an easy-to-use and open software application that can be executed on different computing platforms. To facilitate diverse scientific communities, we provide three software versions, including a graphic user interface (GUI) for personal computer (PC) users, a command-line interface for high-performance computer (HPC) users, and a well-commented interactive
conclusionsLeaf-GP is a sophisticated software application that provides three approaches to quantify growth phenotypes from large image series. We demonstrate its usefulness and high accuracy based on two biological applications: (1) the quantification of growth traits for
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