Global Reconstruction Method of Maize Population at Seedling Stage Based on Kinect Sensor
Round 1
Reviewer 1 Report
The submitted paper is an interesting proposal for automatic phenotype measurement for multiple plants. The reported results show reliable measurements so far for the chosen test scene. Although a good theoretical guidance for maize phenotypic characterization is described, further research in the field is required in order to achieve a reliable measurement automatic tool with application in a real crop maze scenario.
My suggestions are the followings:
- Would you please mention the reasons why the given test scene plant-to-plant distance, the test acquisition period, and the measuring points locations were chosen?
- In a real maze crop scenario the tested plant-to-plant distance is completely impractical and the tested distance helps to achieve the reported good results in the obtained 3D reconstruction. How does your theoretical analysis and physical measurement developing are affected considering shorter plant-to-plant distances as used in a real maze crop?
- Please clarify the sentence "..the test acquisition period was five days..", literally, it would mean that a measurement was done every five days, which is wrong.
- Some minor paper writing typo errors were found, please find them in the attached paper.
Author Response
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Author Response File: 
Author Response.docx
Reviewer 2 Report
The manuscript presents an insight on the most suitable method to be used in maize population at seedling 2 stage based on Kinect sensor as global reconstruction. The materials and methods are very well explained. The findings presented in the study are interesting and well-articulated. However, very few issues need to be addressed in order to bring the manuscript to an acceptable form:
1. Correct the LiDAR to be LIDAR to consistent in your writing.
2. Add the Zhang Zhengyou reference for calibration method in line 132.
3. Correct the “coefficient of determination (R2)” as “2” should be superscript in lines 405, 406, and 473.
4. Correct the typo error for “tesselation” to “tessellation” in line 387
Author Response
- Please see the attachment
Author Response File: Author Response.docx
Reviewer 3 Report
Thank you for the invitation to review the article “Global reconstruction method of maize population at seedling stage based on Kinect sensor “ (Manuscript ID Agriculture-2167123):
I consider the following observations:
1.- Do you use the acronym ROS without defining it?
2.- Why the variety 92 chosen was Zhenzhennuo 99?? Why 16 plants and why distance 80cms and initial 30cms ? (line 92-93)
3.-Line: 258 The affirmation: In this study, the reconstructed site area was 4 m × 4 m. Multi-point 3D point cloud data gathering is necessary because local reconstruction cannot obtain cloud data for the entire site. The noise level of the plant point cloud increases with the distance from Kinect, as does the inaccuracy. This study screened the point cloud data within 2.25 m of the Kinect origin by setting the radius of the enclosing box to 2.25 m.
What was the method to select the area and distance mentioned ?
4.- (line 446): The distance between the points is sufficient to make the following statement?
showing that the majority of the standard sphere reconstruction point sets vary within 0.8 cm of the original coordinate positions, and only a few point sets verge from the original coordinate positions.
5.- Line (470): This indicates that the global reconstruction algorithm is highly accurate. What does high precision mean and what is the technical meaning of this statement?
Author Response
- Please see the attachment
Author Response File: Author Response.docx
