ArticleFrontiers in plant science2018
Novel Digital Features Discriminate Between Drought Resistant and Drought Sensitive Rice Under Controlled and Field Conditions.
Article in Frontiers in plant science, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
- High-Throughput Phenotyping: Status and Applications in Rice Breeding.Plants (Basel, Switzerland) · 2026Review
- A hybrid method for water stress evaluation of rice with the radiative transfer model and multidimensional imaging.Plant phenomics (Washington, D.C.) · 2025Article
- Exploring physiological and molecular dynamics of drought stress responses in plants: challenges and future directions.Frontiers in plant science · 2025Review
- Crop/Plant Modeling Supports Plant Breeding: II. Guidance of Functional Plant Phenotyping for Trait Discovery.Plant phenomics (Washington, D.C.) · 2023Review
- Leaf Count Aided Novel Framework for Rice (Plants (Basel, Switzerland) · 2022Article
- Inter-tissue and inter-organ signaling in drought stress response and phenotyping of drought tolerance.The Plant journal : for cell and molecular biology · 2022Review
- Multi-locus genome-wide association studies reveal genomic regions and putative candidate genes associated with leaf spot diseases in African groundnut (Frontiers in plant science · 2022Article
- Leaf rolling in bread wheat (Frontiers in plant science · 2022Article
- Changes in Vertical Phenotypic Traits of Rice (Frontiers in plant science · 2022Article
- Computer Vision and Machine Learning Analysis of Commercial Rice Grains: A Potential Digital Approach for Consumer Perception Studies.Sensors (Basel, Switzerland) · 2021Article
- Omics for the Improvement of Abiotic, Biotic, and Agronomic Traits in Major Cereal Crops: Applications, Challenges, and Prospects.Plants (Basel, Switzerland) · 2021Review
- Crop breeding for a changing climate: integrating phenomics and genomics with bioinformatics.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2021Review
- Exploiting High-Throughput Indoor Phenotyping to Characterize the Founders of a StructuredFrontiers in plant science · 2021Article
- Drought Tolerant Near Isogenic Lines of Pusa 44 Pyramided WithFrontiers in plant science · 2021Article
- Species-independent analytical tools for next-generation agriculture.Nature plants · 2020Review
- QTL detection and putative candidate gene prediction for leaf rolling under moisture stress condition in wheat.Scientific reports · 2020Article
- Article
- High-Throughput Plant Phenotyping Platform (HT3P) as a Novel Tool for Estimating Agronomic Traits From the Lab to the Field.Frontiers in bioengineering and biotechnology · 2020Review
- Image-Based Assessment of Drought Response in Grapevines.Frontiers in plant science · 2020Article
- Non-Invasive Sensing of Nitrogen in Plant Using Digital Images and Machine Learning forSensors (Basel, Switzerland) · 2019Article
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14 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Dynamic quantification of drought response is a key issue both for variety selection and for functional genetic study of rice drought resistance. Traditional assessment of drought resistance traits, such as stay-green and leaf-rolling, has utilized manual measurements, that are often subjective, error-prone, poorly quantified and time consuming. To relieve this phenotyping bottleneck, we demonstrate a feasible, robust and non-destructive method that dynamically quantifies response to drought, under both controlled and field conditions. Firstly, RGB images of individual rice plants at different growth points were analyzed to derive 4 features that were influenced by imposition of drought. These include a feature related to the ability to stay green, which we termed greenness plant area ratio (GPAR) and 3 shape descriptors [total plant area/bounding rectangle area ratio (TBR), perimeter area ratio (PAR) and total plant area/convex hull area ratio (TCR)]. Experiments showed that these 4 features were capable of discriminating reliably between drought resistant and drought sensitive accessions, and dynamically quantifying the drought response under controlled conditions across time (at either daily or half hourly time intervals). We compared the 3 shape descriptors and concluded that PAR was more robust and sensitive to leaf-rolling than the other shape descriptors. In addition, PAR and GPAR proved to be effective in quantification of drought response in the field. Moreover, the values obtained in field experiments using the collection of rice varieties were correlated with those derived from pot-based experiments. The general applicability of the algorithms is demonstrated by their ability to probe archival
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