ArticlePlant methods2015
Automated phenotyping of plant shoots using imaging methods for analysis of plant stress responses - a review.
Article in Plant methods, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 101 papers.
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Who cites it
101 citing papers in PubMed.
- Integrated phenotyping reveals coordinated physiological responses to cold, freezing, and recovery inAoB PLANTS · 2026Article
- Effect of Silicon on Early Root and Shoot Phenotypes of Rice in Hydroponic and Soil Systems.Plants (Basel, Switzerland) · 2026Article
- Perceptual graph kernels for image-derived plant trait interaction analysis in precision agriculture.Frontiers in plant science · 2026Article
- Genetic and molecular breeding perspectives on developing abiotic stress tolerant pea (Frontiers in plant science · 2026Review
- Post-transcriptional regulation of light-stress responses and predictive modeling in vegetableFrontiers in plant science · 2026Review
- Integrative insights into abiotic stress tolerance in finger millet (Frontiers in plant science · 2026Review
- Microclimate-Controlled Smart Growth Cabinets for High-Throughput Plant Phenotyping.Sensors (Basel, Switzerland) · 2025Article
- Intra-Varietal Variability for Abiotic Stress Tolerance Traits in the Grapevine Variety Arinto.Plants (Basel, Switzerland) · 2025Article
- A panomics-driven framework for the improvement of major food legume crops: advances, challenges, and future prospects.Horticulture research · 2025Article
- MADI: A multispectral automated dynamic imager to monitor plant health.Plant phenomics (Washington, D.C.) · 2025Article
- Two-fold red excess (TREx): a simple and novel digital color index that enables non-invasive real-time monitoring of green-leaved as well as anthocyanin-rich crops.Plant methods · 2025Article
- Harnessing controlled-environment systems for enhanced production of medicinal plants.Journal of experimental botany · 2025Review
- Prediction of harvest-related traits in barley using high-throughput phenotyping data and machine learning.Frontiers in plant science · 2025Article
- Assessing nutritional pigment content of green and red leafy vegetables by image analysis: Catching the "red herring" of plant digital color processing via machine learning.Biology methods & protocols · 2025Article
- Integrating dynamic high-throughput phenotyping and genetic analysis to monitor growth variation in foxtail millet.Plant methods · 2024Article
- Continuous Growth Monitoring and Prediction with 1D Convolutional Neural Network Using Generated Data with Vision Transformer.Plants (Basel, Switzerland) · 2024Article
- AraDQ: an automated digital phenotyping software for quantifying disease symptoms of flood-inoculated Arabidopsis seedlings.Plant methods · 2024Article
- Accurate classification of wheat freeze injury severity from the color information in digital canopy images.PloS one · 2024Article
- Affordable Phenotyping at the Edge for High-Throughput Detection of Hypersensitive Reaction Involving Cotyledon Loss.Plant phenomics (Washington, D.C.) · 2024Article
- Monitoring of drought stress and transpiration rate using proximal thermal and hyperspectral imaging in an indoor automated plant phenotyping platform.Plant methods · 2023Article
41 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Current methods of in-house plant phenotyping are providing a powerful new tool for plant biology studies. The self-constructed and commercial platforms established in the last few years, employ non-destructive methods and measurements on a large and high-throughput scale. The platforms offer to certain extent, automated measurements, using either simple single sensor analysis, or advanced integrative simultaneous analysis by multiple sensors. However, due to the complexity of the approaches used, it is not always clear what such forms of plant phenotyping can offer the potential end-user, i.e. plant biologist. This review focuses on imaging methods used in the phenotyping of plant shoots including a brief survey of the sensors used. To open up this topic to a broader audience, we provide here a simple introduction to the principles of automated non-destructive analysis, namely RGB, chlorophyll fluorescence, thermal and hyperspectral imaging. We further on present an overview on how and to which extent, the automated integrative in-house phenotyping platforms have been used recently to study the responses of plants to various changing environments.
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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.