A conversational multi-agent AI system for automated plant phenotyping

Chen, F. orcid.org/0000-0003-2915-599X, Stogiannidis, I. orcid.org/0009-0005-5803-1138, Wood, A. orcid.org/0000-0003-1343-0774 et al. (12 more authors) (2026) A conversational multi-agent AI system for automated plant phenotyping. Nature Communications. ISSN: 2041-1723

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© The Author(s) 2026. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/

Keywords: Information technology; Machine learning; Natural variation in plants; Optical imaging
Dates:
  • Accepted: 12 March 2026
  • Published (online): 3 April 2026
  • Published: 3 April 2026
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Science (Sheffield) > School of Biosciences (Sheffield)
Date Deposited: 15 Apr 2026 16:02
Last Modified: 15 Apr 2026 16:02
Status: Published online
Publisher: Springer Science and Business Media LLC
Refereed: Yes
Identification Number: 10.1038/s41467-026-71090-y
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