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CORRECTION article

Front. Plant Sci., 27 October 2025

Sec. Sustainable and Intelligent Phytoprotection

Volume 16 - 2025 | https://doi.org/10.3389/fpls.2025.1725871

This article is part of the Research TopicSmart Sensing in Plant Science: Advancing Plant-Environment Interactions for Sustainable PhytoprotectionView all 5 articles

Correction: ADQ-YOLOv8m: a precise detection model of sugarcane disease in complex environment

This article is a correction to:

  1. YOLO-Citrus: a lightweight and efficient model for citrus leaf disease detection in complex agricultural environments

    1. Read original article
Zhaowen Li,Zhaowen Li1,2Jihong Sun*Jihong Sun3*Ying YangYing Yang4Jiangquan ChenJiangquan Chen1Qian YuQian Yu5Zheng ZhouZheng Zhou6Yan YangYan Yang6Tao YinTao Yin1Haokai ZhangHaokai Zhang7Ye Qian*Ye Qian1*
  • 1College of Big Data, Yunnan Agricultural University, Kunming, China
  • 2Key Laboratory of Artificial Intelligence in Yunnan Province, Kunming University of Science and Technology, Kunming, Yunnan, China
  • 3School of Information Engineering, Kunming University, Kunming, China
  • 4College of Animal Veterinary Medicine, Yunnan Agricultural University, Kunming, China
  • 5National Pilot School of Software, Yunnan University, Kunming, China
  • 6Scientific and Technological Achievements Transfer and Transformation Center, Yunnan Provincial Academy of Science and Technology, Kunming, China
  • 7Engineering College, China Agricultural University, Beijing, China

A Correction on
ADQ-YOLOv8m: a precise detection model of sugarcane disease in complex environment

By Li Z, Sun J, Yang Y, Chen J, Yu Q, Zhou Z, Yang Y, Yin T, Zhang H and Qian Y (2025) Front. Plant Sci. 16:1669825. doi: 10.3389/fpls.2025.1669825

Authors “Jiangquan Chen, Tao Yin, and Ye Qian” were erroneously assigned to affiliation 2 “Key Laboratory of Artifcial Intelligence in Yunnan Province, Kunming University of Science and Technology, Kunming, Yunnan, China”. This affiliation has now been removed for authors “Jiangquan Chen, Tao Yin, and Ye Qian”.

The original version of this article has been updated.

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.

Keywords: complex environment, sugarcane diseases, YOLOv8, precise detection, generalization ability

Citation: Li Z, Sun J, Yang Y, Chen J, Yu Q, Zhou Z, Yang Y, Yin T, Zhang H and Qian Y (2025) Correction: ADQ-YOLOv8m: a precise detection model of sugarcane disease in complex environment. Front. Plant Sci. 16:1725871. doi: 10.3389/fpls.2025.1725871

Received: 15 October 2025; Accepted: 17 October 2025;
Published: 27 October 2025.

Approved by:

Frontiers Editorial Office, Frontiers Media SA, Switzerland

Copyright © 2025 Li, Sun, Yang, Chen, Yu, Zhou, Yang, Yin, Zhang and Qian. 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.

*Correspondence: Jihong Sun, c2poOTE4YUBzaW5hLmNvbQ==; Ye Qian, MjAxNDAxNEB5bmF1LmVkdS5jbg==

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.