4th Autonomous Greenhouse Challenge: Dwarf Tomato Timeseries and Images

DOI:10.4121/fa102772-32db-4b30-bace-12f2016722ce.v1
The DOI displayed above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
DOI: 10.4121/fa102772-32db-4b30-bace-12f2016722ce

Datacite citation style

Maree, Stef; Zhang, Pinglin; van Marrewijk, B. M. (Bart); H.F. (Feije) de Zwart; monique bijlaard et. al. (2025): 4th Autonomous Greenhouse Challenge: Dwarf Tomato Timeseries and Images . Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/fa102772-32db-4b30-bace-12f2016722ce.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Dataset

This dataset was collected during the 4th International Autonomous Greenhouse Challenge in the experimental facilities of the Greenhouse Horticulture Business Unit in Bleiswijk, The Netherlands in 2024.


We kindly refer the reader to additional information the competition to http://www.autonomousgreenhouses.com/. The experiment in described in detail in the accompanied paper Autonomous Greenhouse Cultivation of Dwarf Tomato: Performance Evaluation of Intelligent Algorithms for multiple-sensor feedback by the same authors.


This dataset was collected during a two month dwarf tomato cultivation in a research greenhouse compartment (96 m2), located in Bleiswijk (The Netherlands). Six different compartments were controlled remotely and autonomosly by six international teams using intelligent algorithms.


The dataset contains raw and processed data. Raw data were collected via climate measuring boxes, manual registrations, outside weather station and RGBD cameras. From this, energy usage, and costs are computed. Manual plant measurements are collected to evaluate the final harvest.


The dataset contains:

  • Timeseries.zip: 5-minute interval greenhouse climate, control state and weather data, as well as plant measurements related to yield (fruits, count, weights and ripeness).
  • Canopy_camera.zip: For each compartment, a canopy RGBD camera taking images 4 times a day over the course of two months to monitor the growth process for each compartment.


History

  • 2025-06-23 first online, published, posted

Publisher

4TU.ResearchData

Format

image/png, text/csv

Organizations

Greenhouse Horticulture Business Unit, Wageningen University and Research

DATA

Files (3)