Related Experiment Video
Updated: Jan 11, 2026

Using Flatbed Scanners to Collect High-resolution Time-lapsed Images of the Arabidopsis Root Gravitropic Response
Published on: January 25, 2014
Annotated 3D Point Cloud Dataset of Broad-Leaf Legumes Captured by High-Throughput Phenotyping Platform
Alexander Galba1, Jan Masner2, Jana Kholová1,3
1Department of Information Technologies, Faculty of Economics and Management, Czech University of Life Sciences, Kamýcká 129, Prague, 165 00, Czech Republic.
None:
This data descriptor presents novel, annotated 3D point cloud plant scans generated by a high-throughput phenotyping platform (LeasyScan, ICRISAT, India). It focuses on broad-leaf legume species (mungbean, common bean, cowpea, and lima bean). The dataset, generated by PlantEye(R) F600 technology, captures multispectral 3D scans of plant canopies. It includes 223 scans, providing detailed organ-level segmentation annotations for embryonic leaves, leaves, petioles, stems, and whole plants. The dataset fills a critical gap in plant phenomics research by offering a base of annotated data to support AI model development efforts in 3D computer vision. Data preprocessing, annotation procedures, and potential applications in crop research disciplines are further discussed. The dataset, preprocessing code, annotations, and a MIAPPE-compliant data sheet are also presented via the GitHub repository for further updates and expansion.

