EcoBOT: an AI/ML enabled automated phenotyping capability for model plants
The findings of this study demonstrate the potential of the EcoBOT platform for researching plant responses to environmental factors. Future experiments could focus on relating other chemical stresses and microbial interactions to create generalized models of plant responses.
Authors
- Vlastimil Novák (ORCID: https://orcid.org/0000-0001-7890-4593)
- Céline Hernandez (ORCID: https://orcid.org/0000-0001-8664-1340)
- Petrus H. Zwart (ORCID: https://orcid.org/0000-0003-3315-4092)
- James A. Sethian (ORCID: https://orcid.org/0000-0002-7250-7789)
- Trent R. Northen (ORCID: https://orcid.org/0000-0001-8404-3259)
- Marcus M. Noack (ORCID: https://orcid.org/0000-0002-7288-4787)
- Benjamin P. Bowen (ORCID: https://orcid.org/0000-0003-1368-3958)
- Daniela Ushizima (ORCID: https://orcid.org/0000-0002-7363-9468)
- Yezhang Ding (ORCID: https://orcid.org/0000-0001-5903-1870)
- Lloyd T. Cornmesser
- Thomas M. Vess
- John P. Vogel (ORCID: https://orcid.org/0000-0003-1786-2689)
- Zineb Sordo (ORCID: https://orcid.org/0009-0008-3528-5874)
- Stephen Tan
- Peter F. Andeer
- Joseph Zorzi
Institutions
- Berkeley College (US)
- Lawrence Berkeley National Laboratory (US)
- Joint Genome Institute (US)
- Joint BioEnergy Institute (US)
- University of San Francisco (US)
- University of California, Berkeley (US)
Publication Details
- Journal
- Frontiers in Plant Science
- Published
- 2025-12-02
- DOI
- https://doi.org/10.3389/fpls.2025.1633557
- Primary Topic
- Greenhouse Technology and Climate Control
- Type
- article
- Field-Weighted Citation Impact
- 0.00