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README.md

@@ -56,4 +56,58 @@ configs:
   - split: train
     path: raw/train-*
   default: true
+license: cc-by-4.0
+task_categories:
+- image-classification
+size_categories:
+- 10K<n<100K
 ---
+# Wild Rice Kernel Quality Classification
+
+RGB images of single Canadian wild rice (Zizania palustris) kernels photographed under controlled laboratory conditions at the University of Manitoba with a Canon EOS R100 and cropped to 512x512 patches. Kernels are graded into eight quality classes: Healthy-Large, Healthy-Medium, Discoloured-Low, Discoloured-High, Broken-Low, Broken-High, Insect-damaged and Unhulled. The raw config holds the 16,632 original images and the augmented config the record's 49,896 augmented copies (three augmentation sets, A to C, per original). The paired VNIR hyperspectral data are in a separate record.  The dataset contains raw and augmented versions.  
+The raw dataset contains 16,632 images.  
+Images per class:
+- broken_high: 2,124
+- broken_low: 2,124
+- discoloured_high: 2,052
+- discoloured_low: 2,016
+- healthy_large: 2,088
+- healthy_medium: 2,052
+- insect_infected: 2,160
+- unhulled: 2,016
+
+The augmented dataset contains 49,896 images.  
+Images per class:
+- broken_high: 6,372
+- broken_low: 6,372
+- discoloured_high: 6,156
+- discoloured_low: 6,048
+- healthy_large: 6,264
+- healthy_medium: 6,156
+- insect_infected: 6,480
+- unhulled: 6,048
+
+
+This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
+
+## Citation
+
+```bibtex
+@article{sikiru2026multimodal,
+  title={A multimodal imaging dataset for quality grading of Canadian wild rice kernels using RGB and VNIR hyperspectral data},
+  author={Sikiru, Yinka and Erkinbaev, Chyngyz},
+  journal={Data in Brief},
+  volume={65},
+  pages={112601},
+  year={2026},
+  publisher={Elsevier}
+}
+```
+
+
+The dataset itself can be cited as:
+
+Sikiru, Y., &amp; Erkinbaev, C. (2026). *RGB dataset of canadian wild rice kernels* [Dataset]. Zenodo. https://doi.org/10.5281/ZENODO.18346354
+
+
+*This dataset was reformatted from its original format to match HuggingFace standards.*