ArticlePlant methods2017
A "Do-It-Yourself" phenotyping system: measuring growth and morphology throughout the diel cycle in rosette shaped plants.
Article in Plant methods, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed, 54 citations in OpenAlex.
- SAGA1 and SAGA2 promote starch formation around proto-pyrenoids in Arabidopsis chloroplasts.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Flexible wearable sensors for crop monitoring: a review.Frontiers in plant science · 2024Review
- Affordable Phenotyping at the Edge for High-Throughput Detection of Hypersensitive Reaction Involving Cotyledon Loss.Plant phenomics (Washington, D.C.) · 2024Article
- High cyclic electron transfer via the PGR5 pathway in the absence of photosynthetic control.Plant physiology · 2023Article
- PhenoWell®-A novel screening system for soil-grown plants.Plant-environment interactions (Hoboken, N.J.) · 2023Article
- Pitfalls and potential of high-throughput plant phenotyping platforms.Frontiers in plant science · 2023Article
- A method of cotton root segmentation based on edge devices.Frontiers in plant science · 2023Article
- Development of a plant conveyance system using an AGV and a self-designed plant-handling device: A case study of DIY plant phenotyping.Breeding science · 2022Article
- Image analysis for the automatic phenotyping of Orobanche cumana tubercles on sunflower roots.Plant methods · 2021Article
- Condensation of Rubisco into a proto-pyrenoid in higher plant chloroplasts.Nature communications · 2020Article
- Decoding Plant-Environment Interactions That Influence Crop Agronomic Traits.Plant & cell physiology · 2020Review
- An embedded system for the automated generation of labeled plant images to enable machine learning applications in agriculture.PloS one · 2020Article
- Skewed distribution of leaf color RGB model and application of skewed parameters in leaf color description model.Plant methods · 2020Article
- Doing More With Less: A Multitask Deep Learning Approach in Plant Phenotyping.Frontiers in plant science · 2020Article
- CRISPR-Cas9-Mediated Mutagenesis of the Rubisco Small Subunit Family inFrontiers in genome editing · 2020Article
- The pyrenoidal linker protein EPYC1 phase separates with hybrid Arabidopsis-Chlamydomonas Rubisco through interactions with the algal Rubisco small subunit.Journal of experimental botany · 2019Article
- Leaf economics and slow-fast adaptation across the geographic range of Arabidopsis thaliana.Scientific reports · 2019Article
- A photometric stereo-based 3D imaging system using computer vision and deep learning for tracking plant growth.GigaScience · 2019Article
- Review: New sensors and data-driven approaches-A path to next generation phenomics.Plant science : an international journal of experimental plant biology · 2019Review
- A low-cost and open-source platform for automated imaging.Plant methods · 2019Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundImprovements in high-throughput phenotyping technologies are rapidly expanding the scope and capacity of plant biology studies to measure growth traits. Nevertheless, the costs of commercial phenotyping equipment and infrastructure remain prohibitively expensive for wide-scale uptake, while academic solutions can require significant local expertise. Here we present a low-cost methodology for plant biologists to build their own phenotyping system for quantifying growth rates and phenotypic characteristics of
resultsWe constructed an image capture system consisting of a near infra-red (NIR, 940 nm) LED panel with a mounted Raspberry Pi NoIR camera and developed a MatLab-based software module (iDIEL Plant) to characterise rosette expansion. Our software was able to accurately segment and characterise multiple rosettes within an image, regardless of plant arrangement or genotype, and batch process image sets. To further validate our system, wild-type Arabidopsis plants (Col-0) and two mutant lines with reduced Rubisco contents, pale leaves and slow growth phenotypes (
conclusionOur methodology offers a straightforward solution for setting up automated, scalable and low-cost phenotyping facilities in a wide range of lab environments that could greatly increase the processing power and scalability of Arabidopsis soil growth experiments.
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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.