ReviewPlants (Basel, Switzerland)2024
RGB Imaging as a Tool for Remote Sensing of Characteristics of Terrestrial Plants: A Review.
Review in Plants (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
19 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A Systematic Review on the Advancements in Remote Sensing and Proximity Tools for Grapevine Disease Detection.Sensors (Basel, Switzerland) · 2024Pooled it
- Article
- Proxima Green: RGB Color Metrics for Turfgrass Phenotyping in Controlled Conditions.Sensors (Basel, Switzerland) · 2026Article
- Harnessing artificial intelligence in plant breeding: innovations in digital phenotyping and breeding methodologies.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Review
- Integrating hyperspectral reflectance and machine learning for rapid diagnosis of nutrient deficiencies in greenhouse chrysanthemum leaves.BMC plant biology · 2026Article
- Light-Induced Changes in RGB Reflectance Parameters in Wheat and Pea Leaves in the Minute Range.Plants (Basel, Switzerland) · 2026Article
- Digitalised phenotyping of pepper (Capsicum spp.) using effective RGB imaging and optimised camera positioning.Scientific reports · 2026Article
- Artificial Intelligence (AI) in Detection of Abiotic Stress in Plants: A Review.Sensors (Basel, Switzerland) · 2026Review
- Macronutrient deficiency reduces growth and influences vegetation indices of greenhouse grown ornamental and vegetable plants as measured by the TraitFinder digital phenotyping system.Frontiers in plant science · 2026Article
- AI-integrated digital breeding for crop improvement.Frontiers in plant science · 2026Review
- Light Scattering of Leaf Surface and Spongy Mesophyll and Concentration of Anthocyanin Influence Typical and Modified Photochemical Reflectance Indices.Plants (Basel, Switzerland) · 2025Article
- Prediction of soybean yellow mottle mosaic virus in soybean using hyperspectral imaging.Plant methods · 2025Article
- Optical coherence tomography for early detection of crop infection.Plant methods · 2025Article
- RGB Indices Can Be Used to Estimate NDVI, PRI, and Fv/Fm in Wheat and Pea Plants Under Soil Drought and Salinization.Plants (Basel, Switzerland) · 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
- Broadband Normalized Difference Reflectance Indices and the Normalized Red-Green Index as a Measure of Drought in Wheat and Pea Plants.Plants (Basel, Switzerland) · 2024Article
- Computer Vision-Based Fire-Ice Ion Algorithm for Rapid and Nondestructive Authentication of Ziziphi Spinosae Semen and Its Counterfeits.Foods (Basel, Switzerland) · 2024Article
- Development of Analytical Model to Describe Reflectance Spectra in Leaves with Palisade and Spongy Mesophyll.Plants (Basel, Switzerland) · 2024Article
- High-Throughput Phenotyping for Revealing Key Morpho-Physiological Traits for Drought Tolerance in Pea (Pisum sativum and Wild Relatives).Physiologia plantarumArticle
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Approaches for remote sensing can be used to estimate the influence of changes in environmental conditions on terrestrial plants, providing timely protection of their growth, development, and productivity. Different optical methods, including the informative multispectral and hyperspectral imaging of reflected light, can be used for plant remote sensing; however, multispectral and hyperspectral cameras are technically complex and have a high cost. RGB imaging based on the analysis of color images of plants is definitely simpler and more accessible, but using this tool for remote sensing plant characteristics under changeable environmental conditions requires the development of methods to increase its informativity. Our review focused on using RGB imaging for remote sensing the characteristics of terrestrial plants. In this review, we considered different color models, methods of exclusion of background in color images of plant canopies, and various color indices and their relations to characteristics of plants, using regression models, texture analysis, and machine learning for the estimation of these characteristics based on color images, and some approaches to provide transformation of simple color images to hyperspectral and multispectral images. As a whole, our review shows that RGB imaging can be an effective tool for estimating plant characteristics; however, further development of methods to analyze color images of plants is necessary.
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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.