ArticleHorticulture research2018
Application of light detection and ranging and ultrasonic sensors to high-throughput phenotyping and precision horticulture: current status and challenges.
Article in Horticulture research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 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
15 citing papers in PubMed.
- OrchardQuant-3D: combining drone and LiDAR to perform scalable 3D phenotyping for characterising key canopy and floral traits in fruit orchards.Plant biotechnology journal · 2025Article
- Next-generation translational genomics for developing future crops.Functional & integrative genomics · 2025Review
- Revealing drought tolerance strategies in pistachio clonal hybrids: role of osmotic adjustment.BMC plant biology · 2025Article
- Geometric Feature Characterization of Apple Trees from 3D LiDAR Point Cloud Data.Journal of imaging · 2024Article
- An Integrated Multi-Omics and Artificial Intelligence Framework for Advance Plant Phenotyping in Horticulture.Biology · 2023Review
- Methods and Applications of 3D Ground Crop Analysis Using LiDAR Technology: A Survey.Sensors (Basel, Switzerland) · 2023Review
- Article
- Applications of LiDAR in Agriculture and Future Research Directions.Journal of imaging · 2023Review
- Wearable Sensor: An Emerging Data Collection Tool for Plant Phenotyping.Plant phenomics (Washington, D.C.) · 2023Review
- Wind loss model for the thick canopies of orchard trees based on accurate variable spraying.Frontiers in plant science · 2022Article
- CMPC: An Innovative Lidar-Based Method to Estimate Tree Canopy Meshing-Profile Volumes for Orchard Target-Oriented Spray.Sensors (Basel, Switzerland) · 2021Article
- Applications of deep-learning approaches in horticultural research: a review.Horticulture research · 2021Review
- Opportunities and Possibilities of Developing an Advanced Precision Spraying System for Tree Fruits.Sensors (Basel, Switzerland) · 2021Review
- Phenotypic techniques and applications in fruit trees: a review.Plant methods · 2020Review
- Field-Based High-Throughput Phenotyping for Maize Plant Using 3D LiDAR Point Cloud Generated With a "Phenomobile".Frontiers in plant science · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Ultrasonic and light detection and ranging (LiDAR) sensors have been some of the most deeply investigated sensing technologies within the scope of digital horticulture. They can accurately estimate geometrical and structural parameters of the tree canopies providing input information for high-throughput phenotyping and precision horticulture. A review was conducted in order to describe how these technologies evolved and identify the main investigated topics, applications, and key points for future investigations in horticulture science. Most research efforts have been focused on the development of data acquisition systems, data processing, and high-resolution 3D modeling to derive structural tree parameters such as canopy volume and leaf area. Reported applications of such sensors for precision horticulture were restricted to real-time variable-rate solutions where ultrasonic or LiDAR sensors were tested to adjust plant protection product or fertilizer dose rates according to the tree volume variability. More studies exploring other applications in site-specific management are encouraged; some that integrates canopy sensing data with other sources of information collected at the within-grove scale (e.g., digital elevation models, soil type maps, historical yield maps, etc.). Highly accurate 3D tree models derived from LiDAR scanning demonstrate their great potential for tree phenotyping. However, the technology has not been widely adopted by researchers to evaluate the performance of new plant varieties or the outcomes from different management practices. Commercial solutions for tree scanning of whole groves, orchards, and nurseries would promote such adoption and facilitate more applied research in plant phenotyping and precision horticulture.
Identifiers
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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.