CORRECTION article

Front. Plant Sci., 10 July 2025

Sec. Sustainable and Intelligent Phytoprotection

Volume 16 - 2025 | https://doi.org/10.3389/fpls.2025.1648292

Correction: Deep learning-based text generation for plant phenotyping and precision agriculture

  • 1. School of Computer Science, Guangzhou Maritime University,Guangzhou, Guangdong, China

  • 2. Hubei University of Economics, Wuhan, China

  • 3. Hebei Academy of Fine Arts, Shijiazhuang, Hebei, China

  • 4. Hanyang University, Ansan-si, Gyeonggi-do, Republic of Korea

Author “Shan Ren” was assigned as corresponding author. The correct corresponding author is “Long Tang”.

The original version of this article has been updated.

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Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Summary

Keywords

plant phenotyping, deep learning, generative model, biologically-constrained optimization, precision agriculture

Citation

Zhu L, Tang L and Ren S (2025) Correction: Deep learning-based text generation for plant phenotyping and precision agriculture. Front. Plant Sci. 16:1648292. doi: 10.3389/fpls.2025.1648292

Received

17 June 2025

Accepted

27 June 2025

Published

10 July 2025

Volume

16 - 2025

Edited and reviewed by

Frontiers Editorial Office, Frontiers Media SA, Switzerland

Updates

Copyright

*Correspondence: Long Tang,

Disclaimer

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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