Front. Plant Sci. Frontiers in Plant Science Front. Plant Sci. 1664-462X Frontiers Media S.A. 10.3389/fpls.2026.1776055 Correction Correction: An improved YOLOv8-seg-based method for key part segmentation of tobacco plants LiuYihao 1 Methodology Data curation Conceptualization Writing – original draft Software Formal analysis ChenDu 2 Writing – review & editing Resources ZhangYawei 1 Funding acquisition Writing – review & editing WangXin 1 * Resources Methodology Supervision Writing – review & editing College of Engineering, China Agricultural University, Beijing, China State Key Laboratory of Intelligent Agricultural Power Equipment, Beijing, China Correspondence: Xin Wang, wangxin117@cau.edu.cn 24 02 2026 2026 17 1776055 26 12 2025 16 02 2026 12 02 2026 Copyright © 2026 Liu, Chen, Zhang and Wang. 2026 Liu, Chen, Zhang and Wang https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. A Correction on An improved YOLOv8-seg-based method for key part segmentation of tobacco plants By Liu Y, Chen D, Zhang Y and Wang X (2025) Front. Plant Sci. 16:1673202. doi: 10.3389/fpls.2025.1673202 YOLOv8 deep learning agricultural robots tobacco harvesting automated harvesting section-at-acceptance Sustainable and Intelligent Phytoprotection

An incorrect Funding statement was provided. The incorrect Funding statement reads: “The author(s) declare financial support was received for the research and/or publication of this article. This work was supported by the Horizontal Research Project of China Agricultural University (Project No. 202405410711069).” The correct sentence reads: “The author(s) declare financial support was received for the research and/or publication of this article. This work was supported by the Key Research and Development Program of China National Tobacco Corporation, titled “Key Technologies Research and Development for Intelligent Tobacco Leaf Harvesting” (Grant No. 110202301016). The authors declare that this study received funding from China National Tobacco Corporation. The funder was not involved in the study design, collection, analysis, interpretation of data, the writing of this article or the decision to submit it for publication.”.

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