The doi 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/e1ee9de9-6ce9-4502-a37c-34b5b1372bed

Isabella Righini; Bart Marrewijk, van; Ntakos, Georgios; Zhang, Pinglin; Jansen, Guido et. al. (2024): 4th Autonomous Greenhouse Challenge: Pre-trial Dwarf Tomato Measurements and Images. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/e1ee9de9-6ce9-4502-a37c-34b5b1372bed.v1

Dataset

• Horticultural Crops
• Artificial Intelligence and Image Processing
• Horticultural Production
• Agricultural and Veterinary Sciences
• Plant Production and Plant Primary Products
• Information and Computing Sciences

Autonomous Greenhouse Challenge, computer vision, destructive, dwarf tomato, non-destructive

view on openstreetmap

2023-09/2023-11

CC BY 4.0

RefWorks, BibTeX, Reference Manager, Endnote, DataCite, NLM, DC, CFF

by Isabella Righini , Bart Marrewijk, van , Georgios Ntakos , Pinglin Zhang , Guido Jansen , S.C. (Stef) Maree , monique bijlaard , H.F. (Feije) de Zwart , S. (Silke) Hemming

This dataset was generated in the peparation of the 4th International Autonomous Greenhouse Challenge in the experimental facilities of the Greenhouse Horticulture Business Unit in Bleiswijk, The Netherlands in 2023. Information regarding the competition can be found here http://www.autonomousgreenhouses.com/

This dataset was collected during a two month dwarf tomato cultivation in a research greenhouse compartment (96 m2), located in Bleiswijk (The Netherlands). The dataset contains raw and processed data. Raw data were collected via climate measuring boxes, manual registrations, outside weather station and two RGBD cameras. This dataset was then used for two online tasks of teams participating in the Online part of the 4th Autonomous Greenhouse Challenge.

The dataset contains:

• Single_Plant_Camera.zip: 479 Individually RGBD-imaged plants, as well their plant traits (height, fresh weight, leaf area, number of red fruits). This dataset was used for the "Part A Computer Vision" challenge.
• Canopy_cam.zip: A canopy RGBD camera taking images 4 times a day over the course of two months to monitor the growth process.
• Timeseries.zip: Manual plant measurements (destructive and non-destructive) over the course of several weeks throughout the cultivation. As well as 5-minute interval greenhouse climate and weather data.

• 2024-06-17 first online, published, posted

4TU.ResearchData

image/png, xlsx

Wageningen University and Research, Greenhouse Horticulture Business Unit