cff-version: 1.2.0
abstract: "<p>In this research, we created a dataset of 44 annotated 3D point clouds of tomato plants. Images were captured using fifteen cameras surrounding a single plant. Those images were used to create a point cloud using the shape-form silhouette methodology (Koenderink et al., 2009). The resulting dataset was annotated and separated into three parts. 1) Annotated point clouds with semantic and instance labels. The annotated point clouds were used to render annotated RGB images. 2) Annotated skeletons to analyse plant architecture. 3) Manual measurements of internode length, stem thickness, branching and phyllotactic angle to evaluate phenotyping algorithms from point cloud to plant traits. To view the dataset, please have a look at our git:</p>"
authors:
  - family-names: Marrewijk, van
    given-names: Bart M.
    orcid: "https://orcid.org/0000-0003-3681-8114"
  - family-names: Xin
    given-names: Bolai
  - family-names: van Daalen
    given-names: Tim
    orcid: "https://orcid.org/0009-0003-0308-1969"
  - family-names: van Henten
    given-names: Eldert
    orcid: "https://orcid.org/0000-0002-1623-9855"
  - family-names: Polder
    given-names: Gerrit
    orcid: "https://orcid.org/0000-0003-4896-4776"
  - family-names: Kootstra
    given-names: Gert
    orcid: "https://orcid.org/0000-0002-2579-4324"
title: "TomatoWUR: an annotated dataset of 3D tomato plants to quantitatively evaluate segmentation, skeletonisation, and plant trait extraction algorithms for 3D plant phenotyping"
keywords:
version: 1
identifiers:
  - type: doi
    value: 10.4121/e2c59841-4653-45de-a75e-4994b2766a2f.v1
license: CC BY-SA 4.0
date-released: 2025-03-27