ArticleSensors (Basel, Switzerland)2020
Performances Evaluation of a Low-Cost Platform for High-Resolution Plant Phenotyping.
Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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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
10 citing papers in PubMed.
- Improving 3D reconstruction quality for root phenotyping: assessing the impact of camera calibration and imaging parameters.Plant methods · 2026Article
- Advancements in 3D field-crop phenotyping using point clouds: a comparative review of sensor technology, target traits, and challenges under controlled and field conditions.Frontiers in plant science · 2026Review
- Implementation of an SfM-MVS-based photogrammetry approach for detailed 3D reconstruction of plants.Plant methods · 2025Article
- Phenotyping as a tool to study the impact of seed priming and arbuscular mycorrhizal fungi on tomato response to water limitation.FEMS microbiology letters · 2025Article
- Image analysis and polyphenol profiling unveil red-flesh apple phenotype complexity.Plant methods · 2024Article
- How to make sense of 3D representations for plant phenotyping: a compendium of processing and analysis techniques.Plant methods · 2023Review
- Development of a Quick-Install Rapid Phenotyping System.Sensors (Basel, Switzerland) · 2023Article
- Current Status of Biodiversity Assessment and Conservation of Wild Olive (Plants (Basel, Switzerland) · 2022Review
- Review
- Optimization of 3D Point Clouds of Oilseed Rape Plants Based on Time-of-Flight Cameras.Sensors (Basel, Switzerland) · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study aims to test the performances of a low-cost and automatic phenotyping platform, consisting of a Red-Green-Blue (RGB) commercial camera scanning objects on rotating plates and the reconstruction of main plant phenotypic traits via the structure for motion approach (SfM). The precision of this platform was tested in relation to three-dimensional (3D) models generated from images of potted maize, tomato and olive tree, acquired at a different frequency (steps of 4°, 8° and 12°) and quality (4.88, 6.52 and 9.77 µm/pixel). Plant and organs heights, angles and areas were extracted from the 3D models generated for each combination of these factors. Coefficient of determination (R
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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.