ArticlePlant phenomics (Washington, D.C.)2019
Easy MPE: Extraction of Quality Microplot Images for UAV-Based High-Throughput Field Phenotyping.
Article in Plant phenomics (Washington, D.C.), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Aerial imagery and Segment Anything Model for architectural trait phenotyping to support genetic analysis in peanut breeding.Plant phenomics (Washington, D.C.) · 2025Article
- Expeditionplus: The application of a gridded system in the integration of multidimensional environmental factors.Plant diversity · 2025Article
- SHP Buddy: a QGIS plugin for generating shapefiles to support remote sensing in plant breeding and agronomic experiments.Plant methods · 2025Article
- Prediction accuracy and repeatability of UAV based biomass estimation in wheat variety trials as affected by variable type, modelling strategy and sampling location.Plant methods · 2024Article
- High-Throughput Yield Prediction of Diallele Crossed Sugar Beet in a Breeding Field Using UAV-Derived Growth Dynamics.Plant phenomics (Washington, D.C.) · 2024Article
- IHUP: An Integrated High-Throughput Universal Phenotyping Software Platform to Accelerate Unmanned-Aerial-Vehicle-Based Field Plant Phenotypic Data Extraction and Analysis.Plant phenomics (Washington, D.C.) · 2024Article
- PREPs: An Open-Source Software for High-Throughput Field Plant Phenotyping.Plant phenomics (Washington, D.C.) · 2024Article
- High-precision plant height measurement by drone with RTK-GNSS and single camera for real-time processing.Scientific reports · 2023Article
- Effect of varying UAV height on the precise estimation of potato crop growth.Frontiers in plant science · 2023Article
- AirMeasurer: open-source software to quantify static and dynamic traits derived from multiseason aerial phenotyping to empower genetic mapping studies in rice.The New phytologist · 2022Article
- High-throughput field crop phenotyping: current status and challenges.Breeding science · 2022Article
- Validation of UAV-based alfalfa biomass predictability using photogrammetry with fully automatic plot segmentation.Scientific reports · 2021Article
- UAS-Based Plant Phenotyping for Research and Breeding Applications.Plant phenomics (Washington, D.C.) · 2021Review
- Automatic Microplot Localization Using UAV Images and a Hierarchical Image-Based Optimization Method.Plant phenomics (Washington, D.C.) · 2021Article
- Canopy Roughness: A New Phenotypic Trait to Estimate Aboveground Biomass from Unmanned Aerial System.Plant phenomics (Washington, D.C.) · 2020Article
- Semi-Automated Field Plot Segmentation From UAS Imagery for Experimental Agriculture.Frontiers in plant science · 2020Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Microplot extraction (PE) is a necessary image processing step in unmanned aerial vehicle- (UAV-) based research on breeding fields. At present, it is manually using ArcGIS, QGIS, or other GIS-based software, but achieving the desired accuracy is time-consuming. We therefore developed an intuitive, easy-to-use semiautomatic program for MPE called Easy MPE to enable researchers and others to access reliable plot data UAV images of whole fields under variable field conditions. The program uses four major steps: (1) binary segmentation, (2) microplot extraction, (3) production of ∗.shp files to enable further file manipulation, and (4) projection of individual microplots generated from the orthomosaic back onto the raw aerial UAV images to preserve the image quality. Crop rows were successfully identified in all trial fields. The performance of the proposed method was evaluated by calculating the intersection-over-union (IOU) ratio between microplots determined manually and by Easy MPE: the average IOU (±SD) of all trials was 91% (±3).
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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.