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Agriculture
Volume 13
Issue 1
10.3390/agriculture13010047
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Article
Peer-Review Record

An Artificial-Intelligence-Based Novel Rice Grade Model for Severity Estimation of Rice Diseases

Agriculture 2023, 13(1), 47; https://doi.org/10.3390/agriculture13010047
by Rutuja Rajendra Patil 1, Sumit Kumar 2,*, Shwetambari Chiwhane 1, Ruchi Rani 3 and Sanjeev Kumar Pippal 4
Reviewer 1: Anonymous
Reviewer 2:
Mbuyu Sumbwanyambe
Reviewer 3:
Xuliang Duan
Agriculture 2023, 13(1), 47; https://doi.org/10.3390/agriculture13010047
Submission received: 8 October 2022 / Revised: 5 December 2022 / Accepted: 19 December 2022 / Published: 23 December 2022
(This article belongs to the Special Issue The Application of Machine Learning in Agriculture)

Round 1

Reviewer 1 Report

Overall, the study is technically strong. However, following answers are required to be answered in the manuscript to further improve the quality:

1. What would happen if multiple bounding boxes are detected on the input image?
2. What would happen if it shows two spots with two different grades
in the same image?
3. What would happen if it shows two spots with two different diseases
in the same image?
4. Table 7. represents the comparison with the state-of-the-art
approaches, the table can be improved.

Author Response

Please see the attachment

Author Response File: Author Response.docx

Reviewer 2 Report

The paper must just be checked for minor grammatical errors. 

Author Response

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Author Response File: Author Response.docx

Reviewer 3 Report

1 Generally, disease severity grading should be completed by experts in the field. Is it appropriate to determine the grading by simply calculating a proportion? Is the classification reasonable only based on the proportion of disease areas?

2 This paper determines the disease classification by collecting a large number of close-up static images instead of real-time video or remote sensing images, this processing cycle is relatively long and can not achieve timely warning.  Does it have application value?

3 From the technical point of view, the basic principles are not complicated, and there is no obvious improvement has been made in the algorithm or model structure.

4 The data set is not sufficient for a deep learning model.

Author Response

Please see the attachment

Author Response File: Author Response.docx

Round 2

Reviewer 3 Report

The author answered the questions I care about in the previous manuscript, and made improvements in the new version. However, the poor resolution of some diagrams affect the quality of the manuscript.

Author Response

Please see the attachment

Author Response File: Author Response.docx

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