Growth Curve Models and Clustering Techniques for Studying New Sugarcane Hybrids

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

This article applies growth curve models and various clustering techniques (such as K-means, K-medoids, and DBSCAN) to classify the maturity of sugarcane hybrids, demonstrating high innovation and practical significance. The research methodology is rigorous, the experimental design is clear, and the data analysis is comprehensive. The results show that this study can effectively enhance the productivity and sustainability of sugarcane, with particular practical value in the selection and evaluation of sugarcane varieties. Although the article is professional and detailed, some technical details and statistical model explanations may pose challenges for certain readers. It is recommended to simplify some content and improve the clarity of visual charts to enhance readability. Overall, the article makes an important contribution to sugarcane breeding and agricultural production, and I recommend accepting it for publication, though some details and chart presentations need improvement in the final version. Below are some suggested revisions:

1. Some statistical and mathematical models, such as growth curve models and the variance structures used, may be complex for readers unfamiliar with these concepts. It would be helpful to add simplified explanations or provide more detailed background information in an appendix to improve the readability of the article.
2. Line 138: A space is needed at the beginning of the paragraph.
3. Although the article compares K-means, K-medoids, and DBSCAN, it could further elaborate on why a particular algorithm is chosen in specific scenarios, such as how to handle outliers or non-linear data. The authors could also discuss the potential limitations or assumptions underlying each algorithm.
4. The article includes some clustering and growth curve charts that could be more prominently displayed. Presenting these charts in a clearer format and providing detailed explanations would help readers better understand the clustering results and the maturity patterns of the different materials.
5. The authors could explore in more depth how different maturity types (such as early, early-intermediate, intermediate-late, and late) affect overall crop performance and yield. Analyzing how the maturity classification influences industrial practices would further enhance the practical significance of the research.
6. The article could include a section discussing future research directions, such as applying these models to other crops, expanding the study to different geographical regions, or integrating other agricultural variables for a more comprehensive evaluation.

 

Comments on the Quality of English Language

 The English could be improved to more clearly express the research.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

Manuscript "Growth Curve Models and Clustering Techniques for the Study of New Sugarcane Hybrids" is very interesting.

General comments:
The title given in the system ("Growth Curve Models and Clustering Techniques for the Study of New Sugarcane Hybrids: An Integrated Approach with K-Means, K-Medoids, and DBSCAN") and the title contained in the manuscript ("Growth Curve Models and Clustering Techniques for Studying New Sugarcane Hybrids") are not the same.

Authors used growth curve models to analyze sucrose accumulation in 33 sugarcane hybrids under adaptability trials, along with six commercial control varieties. Authors grouped materials using k-means, k-medoids, and DBSCAN to identify their maturity type and select the most promising for the next selection phase.

The Introduction chapter was written correctly. The material and methods used were also written correctly and in a way that allowed the experiment to be repeated.

Table 9: Significance testing of individual parameters is missing. The results should be supplemented with testing.

My suggestions:
It is sufficient to write a vector by giving only one dimension (number of rows). Each vector has one column. For example, we write y is an n-vector.

The authors provide (not propose, because they are known) three methods. Unfortunately, the manuscript lacks a comparison of these methods. The authors do not indicate the assumptions that would make it possible to use each approach.

Paper needs major revision.

Author Response

Please see the attached file.

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

• Provide more details about the growth curve models used. Which specific models (e.g., logistic, Gompertz) were applied, and why were they chosen?
• Include a discussion on the parameters and features used in the clustering algorithms. How were the optimal numbers of clusters determined for K-Means and K-Medoids?
• Consider comparing the performance of the clustering algorithms not only based on the Connectivity and Dunn indexes but also using other validation metrics (e.g., Silhouette score, Calinski-Harabasz index).
• Analyze how different preprocessing steps (e.g., normalization, scaling) might affect the clustering outcomes.
• Incorporate visual representations of the growth curves and clustering results. Graphical outputs can help in understanding the maturity curves and the clustering results more intuitively.
• Use heatmaps or dendrograms to illustrate the relationships between hybrids based on their maturity profiles.
• Discuss the environmental factors considered in the field trials. Were there any significant weather events or conditions that might have impacted the growth of the hybrids?
• Include observations from the field trials that might explain variances in maturity or sucrose content, such as soil conditions or pest pressures.
• How do the clusters formed by the different algorithms correlate with known agronomic traits beyond maturity (e.g., disease resistance, drought tolerance)?
• What criteria were used to select the specific growth curve models for this study? Were any alternative models considered?
• How were the six control varieties selected? Do they represent the best practices in the industry, and how might their performance influence the evaluation of the new hybrids?

Comments on the Quality of English Language

Language should improved

Author Response

Please see the attached file.

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

No further comments.

Reviewer 2 Report

Comments and Suggestions for Authors

The Authors have improved the manuscript according to my suggestions. In cases where they have not followed my suggestions, they have provided credible and satisfactory explanations for their approach. I recommend publishing the manuscript in its current version.