Mathematical Modelling and Optimization of Seed Metering Unit Performance in Precision Peanut Seeding

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

Comments to Authors

The manuscript entitled “Mathematical Modelling and Optimization of Seed Metering Unit Performance in Precision Peanut Seeding” is interesting.

Based on the analysis of experimental data from five different levels of each independent variable, this paper performed using the CCD, and meaningful mathematical model was developed in cubic form for quality of feed index for peanut seeding and the model was optimized. The overall assessment that the manuscript is well-organized, the methodology is sound, and the results are clearly presented. However, some revision needed before the final acceptance.

Specific comments

Literature Review:

1. The authors could consider adding a brief summary of the key findings from the literature review, highlighting the gaps in the existing knowledge that this study aims to address.

Materials and Methods:

1. The performance criterion: It is recommended to introduce the evaluation methods of performance indicators in detail for easier understanding by readers.(The 128th line of the Materials and Methods)

2.Create and add pictures of the test process so that readers can more intuitively understand how the test is conducted.

3.It is suggested to describe the test process in detail and add illustrative pictures of the test process, so that readers can better understand how the test is carried out.

Results and Discussion:

1.Compare your research with existing literature in the discussion section. What improvements have your research findings made compared to previous ones?

2.lease check that all images are correctly referenced?(The 295th line of the Results and Discussion: ‘Figures 5-7’?)

3.Results and discussion What is the main meaning of the author through Figures 3 and 4?

4.Please check all figures for missing factor units, as shown in figures 5 to 7.

5.Please check that all pictures are numbered in the correct order, especially if there are duplicate numbers.(The 325th line and the 333th line of the Results and Discussion )

6.This paper builds a model based only on the data obtained from 20 groups of experiments. How can the accuracy of the model be guaranteed?

Reference: It's best to update the references and replace them with new.

General Comments

Please double check the spelling, punctuation, ordinal numbers in the manuscript.

Double check that all references are cited within the text, and that all citations within the text have a corresponding reference. Double check the spelling of the author names and its affiliation.

Author Response

We appreciate the contribution of the reviewers for the revision. The paper with the REF. NO. of Applsci-3124148 (Mathematical Modelling and Optimization of Seed Metering Unit Performance in Precision Peanut Seeding) was reorganized by considering the suggestions and corrections of the reviewers and actions taken forms are submitted in the order they were received.

Author Response File: Author Response.doc

Reviewer 2 Report

Comments and Suggestions for Authors

The manuscript is well-structured and provides significant insights into optimizing peanut seeding performance. The methodology is robust, but additional details on statistical analysis and experimental procedures are needed to ensure transparency and replicability.

Introduction

The introduction provides a clear context for the study by highlighting the importance of precise seeding techniques for peanut cultivation. However, it would benefit from a brief review of existing literature to better frame the study's significance and highlight gaps in current knowledge.

The main objective is clearly stated: optimizing the performance of a vacuum-type seed metering unit. The rationale behind this objective is well-articulated.

 

Methodology

Experimental Design - The section lacks details on the specific procedures and calibration methods used for the experimental setup. Including these details would enhance the reproducibility of the study.

Statistical Analysis - The manuscript mentions the use of the Minitab statistical package and stepwise regression analysis but does not provide comprehensive details on the statistical methods. This section should include:

·         Descriptive Statistics: Summary statistics for each variable, including means, standard deviations, and ranges.

·         Regression Analysis: Details on how the regression models were built, including the selection criteria for variables, the handling of multicollinearity, and validation techniques used.

·         Optimization Techniques: Explanation of the optimization methods used in the Maple program, including how derivatives were calculated and how optimum values were determined.

·         Model Validation: Information on how the model's performance was validated against experimental data, including any statistical tests for goodness-of-fit or error analysis.

Providing these details will ensure that the methodology is transparent and allows for replication.

 

Results

Model Equation - The manuscript presents the cubic model equation for the quality of feed index (Iqf) with a high coefficient of determination (R² = 99.5%). The model's predictive capability is strong, but the manuscript should include more details on the model fitting process and any assumptions made.

Optimization and Validation - The optimization results and validation against experimental data are well-presented. The manuscript effectively shows that the optimal conditions lead to high-quality seeding. However, additional statistical validation of the model’s accuracy and robustness would strengthen this section.

 

Discussion

The discussion interprets the results well and places them in the context of existing research. However, it would be beneficial to compare the findings with similar studies in more detail to reinforce the study’s conclusions.

The implications for practice and future research are clearly articulated. The study’s findings are relevant for improving seeding practices and guiding further research.

 

Conclusions

The conclusions summarize the key findings effectively, emphasizing the successful optimization of seeding conditions.

Recommendations for practical applications and future research are appropriate and valuable.

Author Response

We appreciate the contribution of the reviewers for the revision. The paper with the REF. NO. of Applsci-3124148 (Mathematical Modelling and Optimization of Seed Metering Unit Performance in Precision Peanut Seeding) was reorganized by considering the suggestions and corrections of the reviewers and actions taken forms are submitted in the order they were received.

Author Response File: Author Response.doc