ArticlePlant methods2021
Open source 3D phenotyping of chickpea plant architecture across plant development.
Article in Plant methods, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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10 citing papers in PubMed.
- Improving 3D reconstruction quality for root phenotyping: assessing the impact of camera calibration and imaging parameters.Plant methods · 2026Article
- When Does Directional Reflectance Matter? Evaluating BRDF Effects in Plant Canopy Light Simulations.Plants (Basel, Switzerland) · 2026Article
- A vision language model for generating XML-based organ-level plant architecture representations of cowpea from simulated images.Frontiers in artificial intelligence · 2026Article
- Deep learning for three-dimensional (3D) plant phenomics.Plant phenomics (Washington, D.C.) · 2025Review
- Next-generation translational genomics for developing future crops.Functional & integrative genomics · 2025Review
- CLCFM3: A 3D Reconstruction Algorithm Based on Photogrammetry for High-Precision Whole Plant Sensing Using All-Around Images.Sensors (Basel, Switzerland) · 2025Article
- A method for phenotyping lettuce volume and structure from 3D images.Plant methods · 2025Article
- A developed system to extract specific responses of increment length in rice shoots under gradient changes in nitrogen concentration regimes.Plant biotechnology (Tokyo, Japan) · 2023Article
- Earbox, an open tool for high-throughput measurement of the spatial organization of maize ears and inference of novel traits.Plant methods · 2022Article
- Review
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Authors and funding
3 authors.
Funding
Abstract
backgroundBeing able to accurately assess the 3D architecture of plant canopies can allow us to better estimate plant productivity and improve our understanding of underlying plant processes. This is especially true if we can monitor these traits across plant development. Photogrammetry techniques, such as structure from motion, have been shown to provide accurate 3D reconstructions of monocot crop species such as wheat and rice, yet there has been little success reconstructing crop species with smaller leaves and more complex branching architectures, such as chickpea.
resultsIn this work, we developed a low-cost 3D scanner and used an open-source data processing pipeline to assess the 3D structure of individual chickpea plants. The imaging system we developed consists of a user programmable turntable and three cameras that automatically captures 120 images of each plant and offloads these to a computer for processing. The capture process takes 5-10 min for each plant and the majority of the reconstruction process on a Windows PC is automated. Plant height and total plant surface area were validated against "ground truth" measurements, producing R
conclusionsOur results show that it is possible to use low-cost photogrammetry techniques to accurately reconstruct individual chickpea plants, a crop with a complex architecture consisting of many small leaves and a highly branching structure. We hope that our use of open-source software and low-cost hardware will encourage others to use this promising technique for more architecturally complex species.
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