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Wheat 3D PartNet: Annotated Dataset for Part segmentation of wheat

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posted on 2025-10-16, 10:24 authored by Reena ReenaReena Reena, John H. Doonan, Kevin Williams, Fiona M. K. Corke, Huaizhong Zhang, Sven Batke, Yonghuai Liu
<p dir="ltr">Wheat3D PartNet is a large-scale 3D point cloud dataset for wheat phenotyping, containing <b>1,300+ annotated samples</b> of three cultivars (Paragon, Gladius, Apogee). Each point cloud is <b>manually segmented</b> into ear and non-ear regions, enabling tasks such as 3D plant part segmentation, spike counting, and trait measurement. The dataset provides <b>benchmark train/test splits</b> and is openly available for research in deep learning, phenotyping, and precision agriculture.</p><p dir="ltr">Corresponding author contact: 25039814@edgehill.ac.uk</p>

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    DOI - Is published in Wheat3D PartNet

Dates of data collection or creation

2020

Language(s)

English

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  • The research did not include human participants or the use of personal data

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  • Has passed accessibility checks

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