ArticlePlant physiology2021
Classical phenotyping and deep learning concur on genetic control of stomatal density and area in sorghum.
Article in Plant physiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
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Who cites it
28 citing papers in PubMed.
- Candidate genes with antagonistic roles in stomatal development are associated with population-wide variation in apple.Horticulture research · 2026Article
- Genetic markers of stomatal cluster development in Begoniaceae revealed through trait analysis assisted by interactive deep-learning.Plant physiology · 2026Article
- Machine Learning-Driven Construction of High-Yielding Cucumber Plant Architectures in Greenhouse Environments.Plant biotechnology journal · 2026Article
- Genome-wide association studies and modeling of stomatal gas conductance reveal genetic control of water-use efficiency in sorghum.Plant physiology · 2026Article
- Advanced phenotyping features utilizing deep learning techniques for automated analysis of stomatal guard cell orientation.Scientific reports · 2025Article
- Article
- Smarter stomata: emergent technologies unlocking yield potential in a changing climate.AoB PLANTS · 2025Review
- Genetic mapping and haplotype analysis identify novel candidate genes for high night temperature tolerance in winter wheat.The plant genome · 2025Article
- Stomata morphology measurement with interactive machine learning: accuracy, speed, and biological relevance?Plant methods · 2025Article
- Stomata-Photosynthesis Synergy Mediates Combined Heat and Salt Stress Tolerance in Sugarcane Mutant M4209.Plant, cell & environment · 2025Article
- Interannual Variation of Stomatal Traits Impacts the Environmental Responses of Apple Trees.Plant, cell & environment · 2025Article
- Machine learning-enabled computer vision for plant phenotyping: a primer on AI/ML and a case study on stomatal patterning.Journal of experimental botany · 2024Review
- Application of deep learning for the analysis of stomata: a review of current methods and future directions.Journal of experimental botany · 2024Review
- Stomatal development in the changing climate.Development (Cambridge, England) · 2024Review
- Genetic Analysis of Soybean Flower Size Phenotypes Based on Computer Vision and Genome-Wide Association Studies.International journal of molecular sciences · 2024Article
- Investigation of a Perspective Urban Tree Species,Plants (Basel, Switzerland) · 2024Article
- Plant microphenotype: from innovative imaging to computational analysis.Plant biotechnology journal · 2024Review
- Comparative analysis of stomatal pore instance segmentation: Mask R-CNN vs. YOLOv8 on Phenomics Stomatal dataset.Frontiers in plant science · 2024Article
- Analysis of stomatal characteristics of maize hybrids and their parental inbred lines during critical reproductive periods.Frontiers in plant science · 2024Article
- Pilot-scale genome-wide association mapping in diverse sorghum germplasms identified novel genetic loci linked to major agronomic, root and stomatal traits.Scientific reports · 2023Article
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10 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Stomatal density (SD) and stomatal complex area (SCA) are important traits that regulate gas exchange and abiotic stress response in plants. Despite sorghum (Sorghum bicolor) adaptation to arid conditions, the genetic potential of stomata-related traits remains unexplored due to challenges in available phenotyping methods. Hence, identifying loci that control stomatal traits is fundamental to designing strategies to breed sorghum with optimized stomatal regulation. We implemented both classical and deep learning methods to characterize genetic diversity in 311 grain sorghum accessions for stomatal traits at two different field environments. Nearly 12,000 images collected from abaxial (Ab) and adaxial (Ad) leaf surfaces revealed substantial variation in stomatal traits. Our study demonstrated significant accuracy between manual and deep learning methods in predicting SD and SCA. In sorghum, SD was 32%-39% greater on the Ab versus the Ad surface, while SCA on the Ab surface was 2%-5% smaller than on the Ad surface. Genome-Wide Association Study identified 71 genetic loci (38 were environment-specific) with significant genotype to phenotype associations for stomatal traits. Putative causal genes underlying the phenotypic variation were identified. Accessions with similar SCA but carrying contrasting haplotypes for SD were tested for stomatal conductance and carbon assimilation under field conditions. Our findings provide a foundation for further studies on the genetic and molecular mechanisms controlling stomata patterning and regulation in sorghum. An integrated physiological, deep learning, and genomic approach allowed us to unravel the genetic control of natural variation in stomata traits in sorghum, which can be applied to other plants.
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