Machine Learning for Precision Agriculture Using Imagery from Unmanned Aerial Vehicles (UAVs): A Survey

Round 1

Reviewer 1 Report

The article discusses “Machine Learning for Precision Agriculture using Imagery from Unmanned Aerial Vehicles (UAV): A Survey”. This paper presents a survey of how image data collected using UAVs has been used in conjunction with ma-chine learning techniques to support precision agriculture.. Overall, the manuscript is satisfactory and interesting. However, this paper requires major revisions to be suitable for publication.

· The title of the ms suggests this work is done to benefit "precision agriculture ". Yet, none of the results are put into this context. How is this useful in agricultural management? This should be picked up in the discussion.

· From the abstract alone, it is hard to understand what was done in this study and with what aim. It should be rewritten. Overall, the motivation of this work needs to come out more clearly. The introduction is rather confusing to read. What was the issue, what was done and how flying altitude influence accuracy?. This is not very clear at present.

· I would suggest authors to add more practical references related to your survey.

Shin, Jaemyung, Md Mahmud, Tanzeel U. Rehman, Prabahar Ravichandran, Brandon Heung, and Young K. Chang. "Trends and Prospect of Machine Vision Technology for Stresses and Diseases Detection in Precision Agriculture." AgriEngineering 5, no. 1 (2023): 20-39.

Li, W., C. Liu, Y. Yang, M. Awais, W. Li, P. Ying, W. Ru, and M. J. M. Cheema. "A UAV-aided prediction system of soil moisture content relying on thermal infrared remote sensing." International Journal of Environmental Science and Technology 19, no. 10 (2022): 9587-9600.

· In the introduction section, the author should mention the location of the research field and coordinates at the end part.

·  There are lots of typos and grammar errors in the introduction section. Revised the manuscript to improve the English. Add some description of the relationship between the canopy temperature and precision irrigation.

· I think the literature review is not completely done. As a review paper, this study should carefully review the recently published papers in the field.

There are lots of typos and grammar errors in the introduction section. Revised the manuscript to improve the English. Add some description of the relationship between the canopy temperature and precision irrigation.

Author Response

Author Response File: Author Response.pdf

Reviewer 2 Report

The paper summarized the segmentation models and accuracy of detection, in terms of UAV applications, which is important to understand the suitability and level of application.   

1.  Section 2.6: Seed Quality and Germination, please support the previous work references for more understanding.

2. Table 7: Second row 4th column, please indicate the method.

3. 5.2.4: Please change the abbreviation properly.

4. In all the summarized detection model tables, can you add the application or the purpose of use clearly in the tables, and columns, (for example -the detection model was used to detect tomatoes)?

5. Table 9: Please add the heading.

6.  5.2.10: In this paragraph, please use the correct abbreviation for LiDAR 

7. Line 1065: What do you mean by table XII?

Author Response

The response is provided in the file.

Author Response File: Author Response.pdf

Reviewer 3 Report

I want to congratulate the authors on an excellent review, one of the best I have seen in my many years as a reviewer, associate editor, and editor-in-chief of various journals. I particularly like the tabular organization and the way the tables are repeated for each class of method. I have a few very minor comments:

Line 292 Give a reference or two to explain the various vegetation indices.

Line 386 and several other locations: I am not sure what this journal’s policy is regarding commercial hardware. Some journals require the name and location of the manufacturer.

Line 422. Give a sentence to describe what a semi-supervised SVM is.

Line 468 Explain the term “balanced accuracy score”

Line 510 Replace “in specific” with “specifically.”

Line 529. Give a reference for the Plant Village Disease Classification challenge dataset.

Line 566 What is an Xception model?

Line 601 “… the open morphological operator” Give a reference

Line 649 “the Chan-Vese algorithm” Give a reference

Line 964 This should be 5.2.11

Author Response

The response is attached in the file. 

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

The authors has been revised all the comments. The paper has been accepted as its current form.