Project-AgML/fava_bean_stomata_imprint

Fava Bean Stomata Imprint

This dataset provides high-resolution RGB images of stomata imprints from faba bean leaves, captured in a field environment at Taastrup campus, Denmark. Images were acquired using a fixed platform equipped with a Leica DM750 light microscope and ICC50 HD digital microscope camera during the 2021-2022 growing season. The dataset contains 2,064 images with no classification, segmentation, or bounding-box annotations.

This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.

Citation

@article{wacker2025stomata,
  title={Stomata morphology measurement with interactive machine learning: accuracy, speed, and biological relevance?},
  author={Wacker, Tomke S. and Smith, Abraham G. and Jensen, Signe M. and Pflüger, Theresa and Hertz, Viktor G. and Rosenqvist, Eva and Liu, Fulai and Dresbøll, Dorte B.},
  journal={Plant Methods},
  volume={21},
  pages={95},
  year={2025},
  publisher={BioMed Central}
}

Wacker, T. S., Smith, A. G., Jensen, S. M., Pflüger, T., Herz, V., Rosenqvist, E., Liu, F., & Dresbøll, D. B. (2025). Datasets used in "Stomata Morphology Measurement with interactive Machine Learning: Accuracy, Speed, and Biological Relevance?" [Dataset]. Zenodo. https://doi.org/10.5281/zenodo.15316123

This dataset was reformatted from its original format to match HuggingFace standards.