ArticlePlant physiology2019
Machine Learning Approaches to Improve Three Basic Plant Phenotyping Tasks Using Three-Dimensional Point Clouds.
Article in Plant physiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- Cell-based crop phenotyping for future climates.The New phytologist · 2026Review
- Deep learning in plant phenotyping: the first ten years.Plant phenomics (Washington, D.C.) · 2025Review
- Deep learning for three-dimensional (3D) plant phenomics.Plant phenomics (Washington, D.C.) · 2025Review
- Masks-to-Skeleton: Multi-View Mask-Based Tree Skeleton Extraction with 3D Gaussian Splatting.Sensors (Basel, Switzerland) · 2025Article
- HALF: Histogram of Angles in Linked Features for 3D Point Cloud Data Segmentation of Plants for Robust Sensing.Sensors (Basel, Switzerland) · 2025Article
- Mapping of cotton bolls and branches with high-granularity through point cloud segmentation.Plant methods · 2025Article
- High-fidelity wheat plant reconstruction using 3D Gaussian splatting and neural radiance fields.GigaScience · 2025Article
- Three-dimensional branch segmentation and phenotype extraction of maize tassel based on deep learning.Plant methods · 2023Article
- How to make sense of 3D representations for plant phenotyping: a compendium of processing and analysis techniques.Plant methods · 2023Review
- Cotton plant part 3D segmentation and architectural trait extraction using point voxel convolutional neural networks.Plant methods · 2023Article
- Machine learning versus crop growth models: an ally, not a rival.AoB PLANTS · 2023Review
- DFSP: A fast and automatic distance field-based stem-leaf segmentation pipeline for point cloud of maize shoot.Frontiers in plant science · 2023Article
- Article
- A graph-based approach for simultaneous semantic and instance segmentation of plant 3D point clouds.Frontiers in plant science · 2022Article
- Open source 3D phenotyping of chickpea plant architecture across plant development.Plant methods · 2021Article
- Deep learning-based high-throughput phenotyping can drive future discoveries in plant reproductive biology.Plant reproduction · 2021Article
- Article
- Convolutional Neural Networks for Image-Based Corn Kernel Detection and Counting.Sensors (Basel, Switzerland) · 2020Article
- Skeletonization of Plant Point Cloud Data Using Stochastic Optimization Framework.Frontiers in plant science · 2020Article
- Affordable Non-Invasive Machine-Aided Phenotyping Identifies Phenotypic Variation to Soil Stress Across the Arabidopsis thaliana Life Cycle.Physiologia plantarumArticle
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Developing automated methods to efficiently process large volumes of point cloud data remains a challenge for three-dimensional (3D) plant phenotyping applications. Here, we describe the development of machine learning methods to tackle three primary challenges in plant phenotyping: lamina/stem classification, lamina counting, and stem skeletonization. For classification, we assessed and validated the accuracy of our methods on a dataset of 54 3D shoot architectures, representing multiple growth conditions and developmental time points for two Solanaceous species, tomato (
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Registered trials
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