ArticlePlant methods2018
Hyperspectral imaging: a novel approach for plant root phenotyping.
Article in Plant methods, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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Who cites it
27 citing papers in PubMed.
- Advances in root phenotyping: high-throughput imaging, computational tools, and integrative approaches for crop improvement.Journal of experimental botany · 2026Review
- From signals to solutions: stress-induced leaf senescence and synthetic biology and AI approaches for crop resilience.Molecular horticulture · 2026Review
- A leaf phenomics approach for estimating belowground traits in North American licorice.American journal of botany · 2026Article
- Deep roots through time and crops: insight from five seasons at DeepRootLab.The New phytologist · 2026Article
- Light Sources in Hyperspectral Imaging Simultaneously Influence Object Detection Performance and Vase Life of Cut Roses.Plants (Basel, Switzerland) · 2026Article
- Toward an Automated System for Nondestructive Estimation of Plant Biomass.Plant direct · 2025Article
- Repeatable Imaging of Soil Processes Through a Stabilized Port: Examples of (i) Soil Contaminants and (ii) Plant Root Growth.Sensors (Basel, Switzerland) · 2025Article
- Advancing hyperspectral imaging techniques for root systems: a new pipeline for macro- and microscale image acquisition and classification.Plant methods · 2024Article
- Phenotypic quantification of root spatial distribution along circumferential direction for field paddy-wheat.PloS one · 2023Article
- Pea Breeding for Resistance to Rhizospheric Pathogens.Plants (Basel, Switzerland) · 2022Review
- MultipleXLab: A high-throughput portable live-imaging root phenotyping platform using deep learning and computer vision.Plant methods · 2022Article
- Ultra-Wideband Microwave Imaging System for Root Phenotyping.Sensors (Basel, Switzerland) · 2022Article
- Resources for image-based high-throughput phenotyping in crops and data sharing challenges.Plant physiology · 2021Article
- Selection of nitrogen responsive root architectural traits in spinach using machine learning and genetic correlations.Scientific reports · 2021Article
- Deep soil exploration vs. topsoil exploitation: distinctive rooting strategies between wheat landraces and wild relatives.Plant and soil · 2021Article
- Prediction of Sweet Corn Seed Germination Based on Hyperspectral Image Technology and Multivariate Data Regression.Sensors (Basel, Switzerland) · 2020Article
- Technical workflows for hyperspectral plant image assessment and processing on the greenhouse and laboratory scale.GigaScience · 2020Review
- Decoding Plant-Environment Interactions That Influence Crop Agronomic Traits.Plant & cell physiology · 2020Review
- High-Throughput Screening of Free Proline Content in Rice Leaf under Cadmium Stress Using Hyperspectral Imaging with Chemometrics.Sensors (Basel, Switzerland) · 2020Article
- SoilCam: A Fully Automated Minirhizotron using Multispectral Imaging for Root Activity Monitoring.Sensors (Basel, Switzerland) · 2020Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundRoot phenotyping aims to characterize root system architecture because of its functional role in resource acquisition. RGB imaging and analysis procedures measure root system traits via colour contrasts between roots and growth media or artificial backgrounds. In the case of plants grown in soil-filled rhizoboxes, where the colour contrast can be poor, it is hypothesized that root imaging based on spectral signatures improves segmentation and provides additional knowledge on physico-chemical root properties.
resultsRoot systems of
conclusionsFundamentals for root phenotyping using hyperspectral imaging have been established by means of an image processing pipeline for automated segmentation of soil-grown plant roots at a high spatial resolution and for the exploration of spectral signatures encoding physico-chemical root zone properties.
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Registered trials
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