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: 10.4121/21960932

Anna Petropoulou; Bart Marrewijk, van; S. (Silke) Hemming; H.F. (Feije) de Zwart; Elings, A. (Anne) et. al. (2023): 3rd Autonomous Greenhouse Challenge: Time-series data on realized climate with annotated crop lettuce-images. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/21960932.v1

Usage statistics

Categories

• Horticultural Crops
• Artificial Intelligence and Image Processing
• Horticultural Production

Keywords

Artificial Intelligence autonomous greenhouse climate control computer vision data driven growing lettuce plant spacing remote control sensors

Geolocation

Licence

CC BY 4.0

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by Anna Petropoulou , Bart Marrewijk, van, S. (Silke) Hemming , H.F. (Feije) de Zwart , A. (Anne) Elings , monique bijlaard

The dataset was generated for the needs of the 3rd International Autonomous Greenhouse Challenge in the experimental facilities of the Greenhouse Horticulture Business Unit in Bleiswijk, The Netherlands in 2022. Information regarding the competition can be found here http://www.autonomousgreenhouses.com/

The dataset contains following folders:

Images

1. Ground Truth: includes [json] with all GT information
2. Depth Images: folder with 388 depth images of 16 bit in [png] format
3. RGB Images: folder with 388 RGB images of 3x8 bit in [png] format
4. Daily Images: includes images of RealSense and Sigrow in [png] format
5. ReadMe document with more information

Time series

1. Meteorological data
2. Greenhouse climate data
3. Greenhouse realized climate controls
4. Greenhouse crop observations

2-4 are given in folders for each of the participating teams.

History

• 2023-03-13 first online, published, posted

Publisher

4TU.ResearchData

Format

application/x-7z-compressed, application/zip, png, json

Associated peer-reviewed publication

Lettuce Production in Intelligent Greenhouses—3D imaging and computer vision for plant spacing decisions

References

• https://doi.org/10.4121/15023088.v1

Language

en-gb

Organizations

Wageningen University & Research, Greenhouse Horticulture Business Unit