ArticleSensors (Basel, Switzerland)2018
Automatic Non-Destructive Growth Measurement of Leafy Vegetables Based on Kinect.
Article in Sensors (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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Who cites it
29 citing papers in PubMed.
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- Plant stem and leaf segmentation and phenotypic parameter extraction using neural radiance fields and lightweight point cloud segmentation networks.Frontiers in plant science · 2025Article
- Accurate plant 3D reconstruction and phenotypic traits extraction via stereo imaging and multi-view point cloud alignment.Frontiers in plant science · 2025Article
- Crop Leaf Phenotypic Parameter Measurement Based on the RKM-D Point Cloud Method.Sensors (Basel, Switzerland) · 2024Article
- Fast reconstruction method of three-dimension model based on dual RGB-D cameras for peanut plant.Plant methods · 2023Article
- Phenotyping of Silique Morphology in Oilseed Rape Using Skeletonization with Hierarchical Segmentation.Plant phenomics (Washington, D.C.) · 2023Article
- Point Cloud Completion of Plant Leaves under Occlusion Conditions Based on Deep Learning.Plant phenomics (Washington, D.C.) · 2023Article
- Dynamic detection of three-dimensional crop phenotypes based on a consumer-grade RGB-D camera.Frontiers in plant science · 2023Article
- Plant trait measurement in 3D for growth monitoring.Plant methods · 2022Article
- Growth parameter acquisition and geometric point cloud completion of lettuce.Frontiers in plant science · 2022Article
- Banana Pseudostem Width Detection Based on Kinect V2 Depth Sensor.Computational intelligence and neuroscience · 2022Article
- TMSCNet: A three-stage multi-branch self-correcting trait estimation network for RGB and depth images of lettuce.Frontiers in plant science · 2022Article
- Non-destructive Plant Biomass Monitoring With High Spatio-Temporal ResolutionFrontiers in plant science · 2022Article
- Plant Leaf Detection and Counting in a Greenhouse during Day and Nighttime Using a Raspberry Pi NoIR Camera.Sensors (Basel, Switzerland) · 2021Article
- Three-Dimensional Reconstruction Method of Rapeseed Plants in the Whole Growth Period Using RGB-D Camera.Sensors (Basel, Switzerland) · 2021Article
- Article
- Optimization of 3D Point Clouds of Oilseed Rape Plants Based on Time-of-Flight Cameras.Sensors (Basel, Switzerland) · 2021Article
- Non-Destructive Measurement of Three-Dimensional Plants Based on Point Cloud.Plants (Basel, Switzerland) · 2020Article
- Path Tracking Control of Field Information-Collecting Robot Based on Improved Convolutional Neural Network Algorithm.Sensors (Basel, Switzerland) · 2020Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Non-destructive plant growth measurement is essential for plant growth and health research. As a 3D sensor, Kinect v2 has huge potentials in agriculture applications, benefited from its low price and strong robustness. The paper proposes a Kinect-based automatic system for non-destructive growth measurement of leafy vegetables. The system used a turntable to acquire multi-view point clouds of the measured plant. Then a series of suitable algorithms were applied to obtain a fine 3D reconstruction for the plant, while measuring the key growth parameters including relative/absolute height, total/projected leaf area and volume. In experiment, 63 pots of lettuce in different growth stages were measured. The result shows that the Kinect-measured height and projected area have fine linear relationship with reference measurements. While the measured total area and volume both follow power law distributions with reference data. All these data have shown good fitting goodness (
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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.