ArticleFrontiers in plant science2018
High Throughput Determination of Plant Height, Ground Cover, and Above-Ground Biomass in Wheat with LiDAR.
Article in Frontiers in plant science, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 96 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
96 citing papers in PubMed.
- A Single-Operator Push-Cart Multi-Beam LiDAR Platform for Multi-Trait Field Phenotyping.Sensors (Basel, Switzerland) · 2026Article
- Bridging scales: integrated multi-omics and deep phenotyping for climate resilience in crop plants.Frontiers in plant science · 2026Review
- A wheat canopy albedo high-throughput phenotyping method and its relationship with canopy architecture and leaf properties.Frontiers in plant science · 2026Article
- Article
- Multi-Scale Remote-Sensing Phenomics Integrated with Multi-Omics: Advances in Crop Drought-Heat Stress Tolerance Mechanisms and Perspectives for Climate-Smart Agriculture.Plants (Basel, Switzerland) · 2025Review
- Soybean yield estimation and lodging discrimination based on lightweight UAV and point cloud deep learning.Plant phenomics (Washington, D.C.) · 2025Article
- Mapping of cotton bolls and branches with high-granularity through point cloud segmentation.Plant methods · 2025Article
- Advancing Crop Resilience Through High-Throughput Phenotyping for Crop Improvement in the Face of Climate Change.Plants (Basel, Switzerland) · 2025Review
- Combining UAV multisensor field phenotyping and genome-wide association studies to reveal the genetic basis of plant height in cotton (Plant phenomics (Washington, D.C.) · 2025Article
- Plant height measurement using UAV-based aerial RGB and LiDAR images in soybean.Frontiers in plant science · 2025Article
- Wheat height monitoring from GPS/BDS reflected signals using pseudorange and dual-frequency carrier phase observables.Frontiers in plant science · 2025Article
- Geometric Feature Characterization of Apple Trees from 3D LiDAR Point Cloud Data.Journal of imaging · 2024Article
- Three-Dimensional Phenotyping Pipeline of Potted Plants Based on Neural Radiation Fields and Path Segmentation.Plants (Basel, Switzerland) · 2024Article
- A Comprehensive Review of LiDAR Applications in Crop Management for Precision Agriculture.Sensors (Basel, Switzerland) · 2024Review
- Automated Phenotypic Trait Extraction for Rice Plant Using Terrestrial Laser Scanning Data.Sensors (Basel, Switzerland) · 2024Article
- Combining features selection strategy and features fusion strategy for SPAD estimation of winter wheat based on UAV multispectral imagery.Frontiers in plant science · 2024Article
- Time-Series Field Phenotyping of Soybean Growth Analysis by Combining Multimodal Deep Learning and Dynamic Modeling.Plant phenomics (Washington, D.C.) · 2024Article
- Advancements in Imaging Sensors and AI for Plant Stress Detection: A Systematic Literature Review.Plant phenomics (Washington, D.C.) · 2024Article
- Precision estimation of winter wheat crop height and above-ground biomass using unmanned aerial vehicle imagery and oblique photoghraphy point cloud data.Frontiers in plant science · 2024Article
- Cotton morphological traits tracking through spatiotemporal registration of terrestrial laser scanning time-series data.Frontiers in plant science · 2024Article
36 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Crop improvement efforts are targeting increased above-ground biomass and radiation-use efficiency as drivers for greater yield. Early ground cover and canopy height contribute to biomass production, but manual measurements of these traits, and in particular above-ground biomass, are slow and labor-intensive, more so when made at multiple developmental stages. These constraints limit the ability to capture these data in a temporal fashion, hampering insights that could be gained from multi-dimensional data. Here we demonstrate the capacity of Light Detection and Ranging (LiDAR), mounted on a lightweight, mobile, ground-based platform, for rapid multi-temporal and non-destructive estimation of canopy height, ground cover and above-ground biomass. Field validation of LiDAR measurements is presented. For canopy height, strong relationships with LiDAR (
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.