ReviewPlant phenomics (Washington, D.C.)2024
The State of the Art in Root System Architecture Image Analysis Using Artificial Intelligence: A Review.
Review in Plant phenomics (Washington, D.C.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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
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Who cites it
18 citing papers in PubMed.
- Application of deep learning in crop research: From genomics to phenomics.The plant genome · 2026Review
- Physiological and morphological drivers of early-spring vigor in warm-climate crops under suboptimal temperatures.Scientific reports · 2026Article
- A systematic comparison of transformers and ConvNets for root segmentation across nine datasets.Plant methods · 2026Article
- Early Plant Development as a Systems-Level Trait: Integrating Omics, Artificial Intelligence, and Emerging Biotechnologies.Plants (Basel, Switzerland) · 2026Review
- Dual-guided asymmetric MP-former for rice root instance segmentation.Plant phenomics (Washington, D.C.) · 2026Article
- Fungal Frontiers in (Bio)sensing.Biosensors · 2026Review
- Root growth and function in New Zealand pasture systems: a perspective on research needs, methods, and system integration.Frontiers in plant science · 2026Article
- CSAG-DETR: a lightweight detector for accurate weed detection in sugar beet fields under complex field conditions.Frontiers in plant science · 2026Article
- Root system architecture and drought adaptation: emerging tools and genetic insights.Frontiers in plant science · 2026Review
- Research neglect of root system architecture in root and tuber crops important for Sub-Saharan African Food Security.PloS one · 2026Article
- Auxin-rhizomicrobiome interactions as a driver of climate-resilient root architecture: a conceptual framework for sustainable agriculture.Frontiers in plant science · 2026Review
- Genetic dissection of the root system architecture QTLome and its relationship with early shoot development, breeding and adaptation in durum wheat.The plant genome · 2025Article
- Characterizing Root Morphology, Water and Nitrogen Uptake of Fibrous-Root and Taproot Crops Under Transparent Soil.Plants (Basel, Switzerland) · 2025Article
- Unearthing the hidden organ: vital role of the root in drought tolerance of plants.Plant molecular biology · 2025Review
- Climate-Resilient Crops: Integrating AI, Multi-Omics, and Advanced Phenotyping to Address Global Agricultural and Societal Challenges.Plants (Basel, Switzerland) · 2025Review
- Improved U-Shaped Convolutional Neural Network with Convolutional Block Attention Module and Feature Fusion for Automated Segmentation of Fine Roots in Field Rhizotron Imagery.Sensors (Basel, Switzerland) · 2025Article
- Rootrainertrons: a novel root phenotyping method used to identify genotypic variation in lettuce rooting.Plant methods · 2025Article
- Artificial intelligence: the human response to approach the complexity of big data in biology.GigaScience · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Roots are essential for acquiring water and nutrients to sustain and support plant growth and anchorage. However, they have been studied less than the aboveground traits in phenotyping and plant breeding until recent decades. In modern times, root properties such as morphology and root system architecture (RSA) have been recognized as increasingly important traits for creating more and higher quality food in the "Second Green Revolution". To address the paucity in RSA and other root research, new technologies are being investigated to fill the increasing demand to improve plants via root traits and overcome currently stagnated genetic progress in stable yields. Artificial intelligence (AI) is now a cutting-edge technology proving to be highly successful in many applications, such as crop science and genetic research to improve crop traits. A burgeoning field in crop science is the application of AI to high-resolution imagery in analyses that aim to answer questions related to crops and to better and more speedily breed desired plant traits such as RSA into new cultivars. This review is a synopsis concerning the origins, applications, challenges, and future directions of RSA research regarding image analyses using AI.
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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.