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Article
Peer-Review Record

Study on the Identification of Mildew Disease of Cuttings at the Base of Mulberry Cuttings by Aeroponics Rapid Propagation Based on a BP Neural Network

Agronomy 2023, 13(1), 106; https://doi.org/10.3390/agronomy13010106
by Yinan Guo, Jianmin Gao *, Mazhar Hussain Tunio and Liang Wang
Reviewer 2:
Agronomy 2023, 13(1), 106; https://doi.org/10.3390/agronomy13010106
Submission received: 29 November 2022 / Revised: 24 December 2022 / Accepted: 27 December 2022 / Published: 29 December 2022
(This article belongs to the Section Horticultural and Floricultural Crops)

Round 1

Reviewer 1 Report

This subject addressed is within the scope of the journal. However, the manuscript in the present version contains several problems. Appropriate revisions should be undertaken in order to justify recommendation for publication.


1. It is mentioned that
BP neural networks are used. What are the advantages of adopting these particular methods over others in this case? How will this affect the results? More details should be furnished.

2.      For readers to quickly catch your contribution, it would be better to highlight major difficulties and challenges, and your original achievements to overcome them, in a clearer way in abstract and introduction.

3. There is a serious concern regarding the novelty of this work. What new has been proposed?

4. Abstract needs to modify and to be revised to be quantitative. You can absorb readers' consideration by having some numerical results in this section.

5. There are some occasional grammatical problems within the text. It may need the attention of someone fluent in English language to enhance the readability.


6. The discussion section in the present form is relatively weak and should be strengthened with more details and justifications.

7. In conclusion section, limitations and recommendations of this research should be highlighted.

8. The authors have to add the state-of-the art references in the manuscripts.

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Reviewer 2 Report

Comments are attached here

Comments for author File: Comments.pdf

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Round 2

Reviewer 1 Report

Accept in present form

Author Response

The manuscript has been revised further as per your valuable suggestions. Thank you for your precious time.

Reviewer 2 Report

The Reviewer thanks the authors for their clarification; however, there are still some minor issues to be explained

1. Why there is no a deep analysis of the proposed NN using the convergence of the net and confusion matrix?. 

2. Why it is intended to generalize their results by just using one trial and one comparison method? 

3. The graphical art has not been improved yet, it is poor. Thus it is highly recommended that most figures are readable. Symbols and letters in plots should be at least as the caption size. 

4. It was not clarified yet why only using a BPNN and not accounting for a better feature extraction process to then be used in a Deep net.

5. It has not been justified again how to tune the hyper parameters of the back propagation neural network. 

6. It has not included an organization paragraph at the end of the Introduction Section, which is helpful for readers of the coming text.

7. The document formatting is not correct. There is a figure without caption in the same page.

8. The strong concern is that is has been neglected current neural network topologies and architectures. There is no clear reason why it should be used the proposed one instead of others from the current literature.

 

Author Response

Please see the attachment.

Author Response File: Author Response.docx

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