ArticleFrontiers in plant science2014
Image-based phenotyping of plant disease symptoms.
Article in Frontiers in plant science, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 90 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
90 citing papers in PubMed, 1 synthesis or guideline pooled it, 309 citations in OpenAlex.
- Pooled it
- Genetic dissection of southern corn leaf blight resistance in sweet corn through genome-wide association studies and genomic selection.The plant genome · 2026Article
- Explainable hybrid multi-branch CNN-ViT-GNN framework for robust hibiscus leaf disease classification.Scientific reports · 2026Article
- Integrative Longitudinal Study of 'Microorganisms · 2026Article
- Article
- A non-destructive plant screening method for improving sample uniformity in horticultural crops based on a hydrogen peroxide fluorescent probe.Frontiers in plant science · 2026Article
- Development of a Comprehensive Lesion Severity Classification Model for Largemouth Bass (International journal of molecular sciences · 2025Article
- Recent advances in characterization and diagnosis of stone fruit tree viruses.Physiology and molecular biology of plants : an international journal of functional plant biology · 2025Review
- Foliar disease resistance phenomics of fungal pathogens: image-based approaches for mapping quantitative resistance in cereal germplasm.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Review
- Energy-Efficient Wireless Multimedia Sensor Nodes for Plant Proximal Monitoring.Sensors (Basel, Switzerland) · 2024Article
- Exploring Imaging Techniques for Detecting Tomato Spotted Wilt Virus (TSWV) Infection in Pepper (Plants (Basel, Switzerland) · 2024Article
- Integrating genomics, phenomics, and deep learning improves the predictive ability for Fusarium head blight-related traits in winter wheat.The plant genome · 2024Article
- Hyperspectral imaging for quantifying Magnaporthe oryzae sporulation on rice genotypes.Plant methods · 2024Article
- QTL analysis on a lemon population provides novel insights on the genetic regulation of the tolerance to the two-spotted spider mite attack.BMC plant biology · 2024Article
- ScAnalyzer: an image processing tool to monitor plant disease symptoms and pathogen spread in Arabidopsis thaliana leaves.Plant methods · 2024Article
- AraDQ: an automated digital phenotyping software for quantifying disease symptoms of flood-inoculated Arabidopsis seedlings.Plant methods · 2024Article
- Natural variation in the pattern-triggered immunity response in plants: Investigations, implications and applications.Molecular plant pathology · 2024Review
- A machine learning system to identify progress level of dry rot disease in potato tuber based on digital thermal image processing.Scientific reports · 2024Article
- High-Resolution Disease Phenotyping Reveals Distinct Resistance Mechanisms of Tomato Crop Wild Relatives againstPlant phenomics (Washington, D.C.) · 2024Article
- Broad-spectrum resistance to fungal foliar diseases in wheat: recent efforts and achievements.Frontiers in plant science · 2024Review
30 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Plant diseases cause significant reductions in agricultural productivity worldwide. Disease symptoms have deleterious effects on the growth and development of crop plants, limiting yields and making agricultural products unfit for consumption. For many plant-pathogen systems, we lack knowledge of the physiological mechanisms that link pathogen infection and the production of disease symptoms in the host. A variety of quantitative high-throughput image-based methods for phenotyping plant growth and development are currently being developed. These methods range from detailed analysis of a single plant over time to broad assessment of the crop canopy for thousands of plants in a field and employ a wide variety of imaging technologies. Application of these methods to the study of plant disease offers the ability to study quantitatively how host physiology is altered by pathogen infection. These approaches have the potential to provide insight into the physiological mechanisms underlying disease symptom development. Furthermore, imaging techniques that detect the electromagnetic spectrum outside of visible light allow us to quantify disease symptoms that are not visible by eye, increasing the range of symptoms we can observe and potentially allowing for earlier and more thorough symptom detection. In this review, we summarize current progress in plant disease phenotyping and suggest future directions that will accelerate the development of resistant crop varieties.
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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.