Project-AgML/grapevine_roots_phenotyping

Grapevine Roots Phenotyping

This dataset provides ground truth RGB images of grapevine roots captured in a field environment at the Ramat Negev Research and Development Center in Israel. The images were collected using handheld minirhizotron cameras and an I-CAP system during 2012-2013. The dataset contains 528 images, each paired with the following ground-truth measurement(s): 0.0.

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

The original train/test/val split has been preserved in the split column.

Citation

@article{khoroshevsky2024cnn,
  title={A CNN-based framework for estimation of root length, diameter, and color from in situ minirhizotron images},
  author={Khoroshevsky, Faina and Zhou, Kaining and Bar-Hillel, Aharon and Hadar, Ofer and Rachmilevitch, Shimon and Ephrath, Jhonathan E. and Lazarovitch, Naftali and Edan, Yael},
  journal={Computers and Electronics in Agriculture},
  volume={227},
  pages={109457},
  year={2024},
  publisher={Elsevier}
}

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