ArticleScientific data2024
Labeled temperate hardwood tree stomatal image datasets from seven taxa of Populus and 17 hardwood species.
Article in Scientific data, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The trial behind it
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Who cites it
4 citing papers in PubMed.
- FieldDino: Rapid In-Field Stomatal Anatomy and Physiology Phenotyping.Plant, cell & environment · 2026Article
- Spatially explicit and regionalized quantification of blue and green crop water footprints in a water-stressed river basin.Water science and technology : a journal of the International Association on Water Pollution Research · 2026Article
- Stoma Detection in Soybean Leaves and Rust Resistance Analysis.Plants (Basel, Switzerland) · 2025Article
- Application of deep learning for the analysis of stomata: a review of current methods and future directions.Journal of experimental botany · 2024Review
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Machine learning (ML) algorithms have shown potential in automatically detecting and measuring stomata. However, ML algorithms require substantial data to efficiently train and optimize models, but their potential is restricted by the limited availability and quality of stomatal images. To overcome this obstacle, we have compiled a collection of around 11,000 unique images of temperate broadleaf angiosperm tree leaf stomata from various projects conducted between 2015 and 2022. The dataset includes over 7,000 images of 17 commonly encountered hardwood species, such as oak, maple, ash, elm, and hickory, and over 3,000 images of 55 genotypes from seven Populus taxa. Inner_guard_cell_walls and whole_stomata (stomatal aperture and guard cells) were labeled and had a corresponding YOLO label file that can be converted into other annotation formats. With the use of our dataset, users can (1) employ state-of-the-art machine learning models to identify, count, and quantify leaf stomata; (2) explore the diverse range of stomatal characteristics across different types of hardwood trees; and (3) develop new indices for measuring stomata.
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Registered trials
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