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Autonomous Agriculture to Support Space Exploration

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Figshare2025-07-24 更新2026-04-28 收录
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https://figshare.com/articles/dataset/Autonomous_Agriculture_to_Support_Space_Exploration/29595234
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Partner Investigators:Vertical Future, UK (Dr. Jennifer Bromley); Axiom Space, USA (Dr. Rahul Goel); University of Adelaide (Profs. Jenny Mortimer, Matthew Gilliham); University of Cambridge (Prof. Alex Webb); University of Western Australia (Prof. A. Harvey Millar); University of Southern Queensland (Prof. Bernadette McCabe, Dr. Cheryl McCarthy); Saber Astronautics Australia/USA (Dr. Jason Held).Data collected at Vertical Future, University of Adelaide, University of Cambridge, University of Western Australia and University of Southern Queensland.Scientists involved included Dr. Ali Gill, Ms Chalotte Bampton and Ms Wendy Sullivan (Adelaide), Dr Samalka Wijeweera and Dr Troy Miller (UWA), Dr Eva Herrero Serrano (Cambridge), Dr John Stamford (Vertical Future).Project Overview (Taken from public Executive Summary of report submitted to the UK Space Agency/Australian Space Agency)This project developed a prototype autonomous controlled-environment agriculture (CEA) system, designed to optimise plant growth in space and support both long-duration missions and scientific experimentation. Through a cross-disciplinary collaboration between plant scientists and space technology providers from the UK, Australia, and the USA, we explored new opportunities for automating crop production in orbit and on Earth.The system was designed with Axiom Station in mind, building on insights from prior experiments aboard the International Space Station (ISS). A key milestone was the successful parabolic flight of the engineering development unit (EDU), significantly advancing its Technology Readiness Level (TRL) and validating core system capabilities under microgravity conditions.The project also established a global testbed of replicated plant growth sites, enabling robust comparison of environmental and phenotypic data streams across research and commercial environments. These testbeds provided critical input into the development of machine vision tools and decision-support systems, forming a strong foundation for future commercial applications in space and terrestrial AgriTech.Public engagement was a key pillar of the project. We delivered a comprehensive outreach programme that engaged with government, industry, education, and the general public. This included the development of free educational resources to promote understanding of how space-based research informs the future of food systems on Earth.This dataset represents an archive of images taken of plants growing in controlled environments and responding to various imposed stresses. These were used to train various algorithms to drive early identification of problems in growing plants and use this to drive early intervention (whether autonomous, remote or in person), reducing crop losses. Images were captured using a raspberry pi system, across 5 remote sites (University of Adelaide, University of Western Australia, and University of Southern Queensland (Australia); University of Cambridge, and Vertical Future Syan Farms (UK).
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2025-07-24
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