ArticlePlants (Basel, Switzerland)2023
Design and Development of a Low-Cost UGV 3D Phenotyping Platform with Integrated LiDAR and Electric Slide Rail.
Article in Plants (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed.
- Omics-driven plant breeding through phenomics-enviromics crosstalk.Nature communications · 2026Review
- Quantification of lettuce leaf DUS test traits and phenotypic fingerprint construction for variety identification.Plant phenomics (Washington, D.C.) · 2026Article
- Research progress on rapid detection technology of soybean phenotypic indicators under saline-alkali stress.Planta · 2026Review
- Rhizosphere Microbiome Engineering for Climate-Smart Agriculture: From Synthetic Consortia to Precision Decision Support.Microorganisms · 2026Review
- OpenEar: an ultra-affordable, high-throughput, and accurate maize ear phenotyping system.Plant methods · 2026Article
- Precise 3D geometric phenotyping and phenotype interaction network construction of maize kernels.Frontiers in plant science · 2025Article
- FF-Net: Feature-Fusion-Based Network for Semantic Segmentation of 3D Plant Point Cloud.Plants (Basel, Switzerland) · 2023Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Unmanned ground vehicles (UGV) have attracted much attention in crop phenotype monitoring due to their lightweight and flexibility. This paper describes a new UGV equipped with an electric slide rail and point cloud high-throughput acquisition and phenotype extraction system. The designed UGV is equipped with an autopilot system, a small electric slide rail, and Light Detection and Ranging (LiDAR) to achieve high-throughput, high-precision automatic crop point cloud acquisition and map building. The phenotype analysis system realized single plant segmentation and pipeline extraction of plant height and maximum crown width of the crop point cloud using the Random sampling consistency (RANSAC), Euclidean clustering, and k-means clustering algorithm. This phenotyping system was used to collect point cloud data and extract plant height and maximum crown width for 54 greenhouse-potted lettuce plants. The results showed that the correlation coefficient (R2) between the collected data and manual measurements were 0.97996 and 0.90975, respectively, while the root mean square error (RMSE) was 1.51 cm and 4.99 cm, respectively. At less than a tenth of the cost of the PlantEye F500, UGV achieves phenotypic data acquisition with less error and detects morphological trait differences between lettuce types. Thus, it could be suitable for actual 3D phenotypic measurements of greenhouse crops.
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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.