ArticleFrontiers in plant science2022
Three-dimensional reconstruction and phenotype measurement of maize seedlings based on multi-view image sequences.
Article in Frontiers in plant science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed.
- MSDDG: Multi-scale dual-discriminator GAN for point cloud completion of plant.Plant phenomics (Washington, D.C.) · 2026Article
- Advancements in 3D Reconstruction for Plant Phenotyping: Technologies, Applications, Challenges, and Future Directions.Sensors (Basel, Switzerland) · 2026Review
- 2D-to-3D Image Reconstruction in Agriculture: A Review of Methods, Challenges, and AI-Driven Opportunities.Sensors (Basel, Switzerland) · 2026Review
- Three-dimensional phenotyping: Technological advances and applications in genomics-assisted crop breeding.Plant communications · 2026Review
- Organ-level 3D phenotyping of saffron using a low-cost dual-camera workflow.Plant methods · 2026Article
- F2DMAS: a smartphone video-based 3D phenotyping workflow for potted plants in complex backgrounds.Frontiers in plant science · 2026Article
- CLCFM3: A 3D Reconstruction Algorithm Based on Photogrammetry for High-Precision Whole Plant Sensing Using All-Around Images.Sensors (Basel, Switzerland) · 2025Article
- Accurate plant 3D reconstruction and phenotypic traits extraction via stereo imaging and multi-view point cloud alignment.Frontiers in plant science · 2025Article
- A 3D stem diameter measurement method for field maize at jointing stage: combining RLRSA-PointNet++ and structural feature fitting.Frontiers in plant science · 2025Article
- Automated measurement of field crop phenotypic traits using UAV 3D point clouds and an improved PointNet+.Frontiers in plant science · 2025Article
- A 3D reconstruction platform for complex plants using OB-NeRF.Frontiers in plant science · 2025Article
- Crop Leaf Phenotypic Parameter Measurement Based on the RKM-D Point Cloud Method.Sensors (Basel, Switzerland) · 2024Article
- An integrated method for phenotypic analysis of wheat based on multi-view image sequences: from seedling to grain filling stages.Frontiers in plant science · 2024Article
- Point Cloud Completion of Plant Leaves under Occlusion Conditions Based on Deep Learning.Plant phenomics (Washington, D.C.) · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
As an important method for crop phenotype quantification, three-dimensional (3D) reconstruction is of critical importance for exploring the phenotypic characteristics of crops. In this study, maize seedlings were subjected to 3D reconstruction based on the imaging technology, and their phenotypic characters were analyzed. In the first stage, a multi-view image sequence was acquired
Indexed as
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.