PONE-D-25-19024Precise Tea Leaf Disease Detection Using UAV Low-Altitude Remote Sensing and Optimized YOLO11 ModelPLOS ONE

Dear Dr. Wu,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

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Comments to the Author:

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Please submit your revised manuscript by Aug 22 2025 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

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We look forward to receiving your revised manuscript.

Kind regards,

Farman Ullah

Academic Editor

PLOS ONE

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3. Thank you for stating the following in the Acknowledgments Section of your manuscript:

The authors extend their appreciation to the Science and Technology Research Projects of Henan Province (Grant No. 252102111173) and Cangnan County Modern Agricultural Industry Enhancement Project (Grant No. 2024CNYJY08).

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This research was funded by Science and Technology Research Projects of Henan Province (Grant No. 252102111173) and Cangnan County Modern Agricultural Industry Enhancement Project (Grant No. 2024CNYJY08). The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

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Additional Editor Comments:

Comments to the Author:

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Partly

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: No

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3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: No

Reviewer #2: Yes

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4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

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5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The manuscript addresses an important and current challenge in agricultural monitoring achieving accurate and real-time detection of tea leaf diseases through the integration of low-altitude remote sensing via Unmanned Aerial Vehicles (UAVs) and an enhanced, lightweight deep learning framework, namely the FCHE-YOLO model, which is an optimization of the YOLO11 architecture. The study is technically well-founded and represents a meaningful contribution to the ongoing development of UAV-assisted plant health monitoring systems, which are critical for promoting sustainable agricultural practices and mitigating crop losses due to pests and diseases.

The study is technically competent and makes an important contribution to the continuous development of UAV-assisted plant health monitoring systems, which are vital for encouraging sustainable agricultural practices and decreasing crop losses due to pests and diseases. Overall, the paper is clearly written, logically structured, and supported by a robust set of experimental results that demonstrate the potential benefits of the proposed improvements. Nevertheless, in order to meet the publication standards of PLOS ONE and to maximize the impact and reproducibility of the work, several aspects require further elaboration.

Major comments

• The manuscript introduces a novel backbone module (FC_C3K2), a redesigned neck structure (HSFPN), and a lightweight detection head (Efficient-Head), all integrated into the YOLO11 framework. While these modular enhancements are technically reasonable and well-supported by the experiments, the degree of incremental novelty compared to recent lightweight YOLO versions, such as YOLOv8 or other contemporary architectures, is not yet clearly demonstrated.

To strengthen the contribution and improve clarity for readers, I suggest the authors to provide a more rigorous discussion quantifying and explaining how the proposed FCHE-YOLO architecture differs both functionally and conceptually from existing lightweight variants, including examples like YOLOv8-RCAA and YOLO-Tea. Additionally, presenting a comparative table that outlines the module-wise differences would greatly help to highlight the specific innovations introduced in this study.

• The dataset used in this study consists of approximately 5,400 images obtained through data augmentation, all originally collected from a single tea plantation (Siwangshan). This limited source of data raises valid concerns regarding the potential for overfitting and questions the generalizability of the model to other locations and conditions. Moreover, The data augmentation techniques could be described with precise parameter ranges (e.g., how much brightness adjustment? what rotation angles?).

I suggest the authors to provide a thorough discussion of possible site-specific biases and clarified whether data from additional plantations, different seasons, or varying lighting conditions were included in the dataset or are planned for future work.

• The comparative experiments presented in the manuscript primarily concentrate on conventional models such as Faster R-CNN, SSD, and earlier versions of the YOLO series. However, the recent advancements in transformer-based or hybrid CNN-transformer detection frameworks, such as DE-TR and Swin-Transformer, are not addressed or evaluated in this study.

I recommend the authors to discuss why transformer-based or attention-heavy detectors were not compared or tested. Even if not deployed on UAVs due to resource constraints, this would contextualize the chosen architecture.

• Although the model demonstrates high frame rates on a desktop GPU, its performance decreases to approximately 15 FPS when deployed on edge UAV devices, which could limit its real-time effectiveness in the field. While the manuscript briefly mentions plans for model pruning and TensorRT optimization, I recommend authors to include more specific details on current inference latency and energy consumption during UAV operations. Providing this information would offer a clearer understanding of the model’s practical feasibility and highlight any technical constraints that need to be addressed for successful real-world deployment.

• Many hyperparameters are listed, but key training details such as random seed, augmentation pipeline code, and training/validation split reproducibility are missing. I recommend authors to consider adding the full training pipeline and data splits to a supplementary file or public repository to meet PLOS ONE’s data availability standards.

Minor Comments

• The manuscript has minor grammatical issues and redundant phrases. For example, “the model significantly improves the adaptability and expressiveness” could be shortened, in addition, some references are embedded mid-sentence and break the flow

I Recommend authors a careful language editing and to ensure consistent citation style;

• Figures illustrating the system architecture and modules should be labeled more clearly and be of higher resolution. Some figures (heatmaps, detection examples) are low-resolution and need clearer labeling.

I recommend to use high-resolution annotated figures with consistent color maps and scale bars.

• Some cited papers (e.g., [20], YOLO-Tea) should be cross-checked for accuracy and updated if more recent works exist.

Reviewer #2: The review has been attached for the consideration of authors. There are few key areas that require modification and further test results need to be provided. The paper provide an interesting approach and if revisions are performed it can be put for a review again.

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Reviewer #1: No

Reviewer #2: No

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Attachments

Attachment

Submitted filename: PONE-D-25-19024_Review#OB.pdf

Attachment

Submitted filename: Review_PONE-D-25-19024.pdf

PONE-D-25-19024R1Precise Tea Leaf Disease Detection Using UAV Low-Altitude Remote Sensing and Optimized YOLO11 ModelPLOS ONE

Dear Dr. Wu,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Dec 06 2025 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

• A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
• A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
• An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Farman Ullah

Academic Editor

PLOS ONE

Journal Requirements:

If the reviewer comments include a recommendation to cite specific previously published works, please review and evaluate these publications to determine whether they are relevant and should be cited. There is no requirement to cite these works unless the editor has indicated otherwise.

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: (No Response)

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

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4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: (No Response)

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5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: No

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6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The revised manuscript shows clear improvements in both clarity and scientific rigor. The authors addressed the major concerns raised in the first review, and the paper is now significantly stronger.

Strengths of the Revision:

- The novelty of the FCHE-YOLO framework is now articulated more clearly, supported by a comparative table against other YOLO variants.

- The dataset section has been expanded, with explicit acknowledgment of site-specific limitations and suggestions for future multi-site validation.

- Transformer-based methods are now discussed, and the rationale for focusing on CNN-based architectures is convincingly explained.

- Figures and tables are clearer, and the manuscript benefits from improved language editing.

The remaining points are minor refinements that could further strengthen the paper: (i) briefly reiterate dataset limitations in the Conclusions for balance, (ii) include approximate energy consumption data from UAV deployment to reinforce field feasibility, and (iii) ensure the data and code repository fully complies with PLOS ONE standards, with unrestricted access to raw data, annotations, augmentation scripts, and trained weights.

A final proofreading pass is recommended to eliminate minor redundancies and improve flow

Conclusion:

The manuscript has been substantially strengthened in response to reviewer feedback. The technical soundness is solid, the results are convincing, and the revisions significantly improve clarity and reproducibility. Some minor refinements remain, particularly regarding the explicit availability of data/code and the contextualization of the model’s novelty and deployment feasibility.

Reviewer #2: Please check the attached review file. Please provide response letter against each of the comment and also indicate where your changes are in the paper.

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7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

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[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

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Attachments

Attachment

Submitted filename: Review_PONE-D-25-19024R1.pdf

Precise Tea Leaf Disease Detection Using UAV Low-Altitude Remote Sensing and Optimized YOLO11 Model

PONE-D-25-19024R2

Dear Dr. Wu,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Chong Xu

Academic Editor

PLOS One

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Partly

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

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5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: I would like to thank the authors for their thoughtful and thorough revisions. The manuscript has improved substantially through each round, and the current version (R2) fully addresses the remaining concerns raised in the previous reviews. The study now meets the scientific, technical, and transparency standards expected by PLOS ONE. The FCHE-YOLO model represents a meaningful advancement in lightweight, UAV-based plant disease detection, with potential applications in real-world agricultural monitoring.

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7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

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