Dynamic Slicing and Reconstruction Algorithm for Precise Canopy Volume Estimation in 3D Citrus Tree Point Clouds

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

I want to commend the authors for their meticulous work on the article. It is lucid, with well-argued and relevant topics. The use of formulas, tables, and graphs is clear and effectively utilized.

Articles that explain an algorithm in an accessible manner are hard to come by, and this article accomplishes this task. With a detailed approach, the authors contribute to the advancement of science and the potential application of algorithms to other agricultural crops worldwide.

My suggestions are as follows:

1. Consider enhancing the explanation of the phrase: “iterative mean point spacing as the α-value” in the abstract. Also, provide a more comprehensive explanation in the introduction and discussion sections. It would be useful to mention in this summary section that the algorithm uses the average distance between points as a crucial parameter (α value). This will engage readers who lack prior knowledge and motivate them to read the article. Since this concept isn't revisited in the text, I recommend expanding on the importance of this approach in the introduction and discussion. As it's a significant methodological aspect, I suggest revisiting this topic in the text.
2. In the conclusions, would it be beneficial to indicate that some methods, despite their variances, can be viewed as more conservative estimators, and that the challenge lies with the other groups? I comprehend that we have three groups: those who overestimate, the conservatives, and those who underestimate the volumes. If this distinction is made clear, I believe it will provide readers with practical guidance on the algorithm they wish to implement in other scenarios.

Author Response

For point-by-point responses to the comments, please refer to the attachment. The revisions addressing each reviewer's comments are highlighted in different colors in the newly uploaded manuscript (Reviewer 1: light blue, Reviewer 2: green, Reviewer 3: yellow).

Author Response File: Author Response.docx

Reviewer 2 Report

Comments and Suggestions for Authors

Canopy volume estimation in citrus trees is a novel research topic and applicability in smart agriculture. However, the following comments have been made:

1. The objective of the manuscript is not clear; it is recommended to revise and include it.

2. Line 366 states that LIDAR scanning represents more accurately the actual morphology of fruit trees. It is recommended to consider the term greater precision because the manual method provides the reference values in the field.

3. In section 3.1.1. Comparative analysis of volumetric values using various approaches, it is recommended to start with an introductory paragraph mentioning figure 11.

4. In chapter 4. Discussion, it is recommended to include bibliographic citations that serve to give relevance to the findings found in the research.

5. Line 773, include unit of measurement. 

6. In the Conclusions section, it is recommended to divide them into 3 parts: main summary of your work, initial problems to be solved (or summary of the research challenges) and a brief summary of the research directions for future studies.

 

Author Response

For point-by-point responses to the comments, please refer to the attachment. The revisions addressing each reviewer's comments are highlighted in different colors in the newly uploaded manuscript (Reviewer 1: light blue, Reviewer 2: green, Reviewer 3: yellow).

Author Response File: Author Response.docx

Reviewer 3 Report

Comments and Suggestions for Authors

The rapid and accurate estimation of canopy volume plays a crucial role in monitoring fruit tree growth dynamics and enhancing orchard management optimization. The authors proposed a dynamic slicing and reconstruction canopy volume (DR) algorithm and explored its accuracy and efficiency compared with the other six methods. They also thoroughly examined the issue of parameter sensitivity within the DR algorithm. Overall, this work is important and well-suited for the topic of remote sensing. However, there are some areas that need improvement in this article. The authors have reviewed the most recent research relevant to the work presented in this article, which is commendable. However, the description of these related works is superficial. They should not only describe the methods used in these studies, but also provide appropriate evaluations based on their performance evaluation results. It is recommended that the authors make rigorous revisions to this issue. I recommend a revision before accepting the manuscript. Please allow me to clarify. 

 

major concerns:

 

-1, L40-42. "Moveover, this approach enables... This approach enables". Which approach is it? In the beginning of the second paragraph, the authors introduce the advantages and importance of tree canopy. But how could you call a tree canopy an approach?

 

-2, L59-71. The authors reviewed some studies (Ref. 16–20) on measuring canopy volume and simply described the different techniques, but missed the descriptions of their performance and accuracy, which are important and could give more information. It is suggested to add these details, such as R-square (coefficient of determination) and RMSE (root mean square error). 

 

L77-109. There are similar issues in the reviews of Ref. 21–28. It is not sufficient for the relevant studies to simply describe the techniques without providing their accuracy and performance.

 

L125-151. The authors introduce some point cloud-based canopy reconstruction algorithms here. Compared to understanding what these algorithms are and who proposed them, readers may be more interested in knowing the advantages, disadvantages, and performance differences of these methods. To provide this information, the authors could offer an objective summary that incorporates more insightful thinking.

 

-3, This work utilized multiple software development platforms, such as MATLAB, Python, RStudio, CloudCompare, and GoSLAM Studio software. When describing a function or tool used, please make sure to clearly indicate the software platform it belongs to, so that readers can better understand the work content.

 

-4, L152-154, L362-367. On the one hand, the authors claimed that "manual measurements...has a large deviation from the true volume"; On the other hand, they considered that "...the errors between the manual measurement method and the LiDAR scanning data were very small". Please clarify these two perspectives.

 

-5, In the Section of Materials and Methods, it is suggested to provide a performance evaluation system for the algorithm in a sub-chapter, including accuracy evaluation indicators, efficiency evaluation indicators, etc.

 

-6, The discussions about the parameter sensitivity issue and the different algorithm scenarios are commendable. However, first, it is not recommended to include no reference throughout the entire discussion section. Second, please discuss future improvement ideas based on your algorithm's accuracy and efficiency, and combine the latest research progress (with references) to discuss other applicable scenarios of your method.

 

minor concerns:

 

-1, L34-35. "The canopy of a fruit tree constitutes the primary section responsible for light absorption during respiration and photosynthesis." How to understand the description of "light absorption during respiration"? Do you mean Photorespiration?

 

-2, L152-155. Please provide references for this assertion: "...citrus, the world's number one fruit crop."

 

-3, Figure 1. Consider adding a scale bar or longitude and latitude labels to sub-figure 1a.

 

-4, L230. Where is the unique() function from?

 

-5, L369. What is MM? Abbreviations need to be given their full names when they first appear.

 

-6, L795-830. Please streamline the conclusion appropriately to make it more convenient for readers to understand.

 

Author Response

For point-by-point responses to the comments, please refer to the attachment. The revisions addressing each reviewer's comments are highlighted in different colors in the newly uploaded manuscript (Reviewer 1: light blue, Reviewer 2: green, Reviewer 3: yellow).

Author Response File: Author Response.docx

Round 2

Reviewer 3 Report

Comments and Suggestions for Authors

The authors have improved the manuscript regarding my comments. I have no further comments for the authors. Thank you!