Feature Extraction for Cocoa Bean Digital Image Classification Prediction for Smart Farming Application

Round 1

Reviewer 1 Report

No clearly defined goal of the work.

The authors did the research but did not show how they can be used.

The title does not correspond to the scope of the work - the results are not translated into Smart Farming Application.

No reference to other studies on this type or studies of similar material.
Fig. 3. - what the abbreviations mean.

No comment to table 5. The table contains the results of the work, but the authors do not comment on whether the results are good, bad or acceptable.

Lack of discussion of the results with the literature - whether the obtained results are satisfactory and do they correspond with the results of other researchers.

Author Response

We appreciate the time and effort form Editorial Board and the reviewers dedicated to providing feedback on our manuscript. We are grateful for the insightful comments on valuable improvements to our paper. We have incorporated all of the suggestions made by reviewers. Changes are highlighted in the manuscript. Please see below the attachment for a point-by-point response to the reviewer’s comments and concerns.

Author Response File: Author Response.pdf

Reviewer 2 Report

This paper presents extraction for Cocoa Beans digital image classification prediction in smart farming application. I believe this paper is innovative through demonstrating a method for textural feature analysis with the deep learning. However, the key issue is that this paper is not well presented. Whilst this paper is meaningful, the organisation of this paper looks like a report.

Abstract, I cannot see the background and the research gap motivating authors to conduct this research? How about the research aim and objectives and the significance of this paper?

Introduction, authors have merely presented the research background. However, authors have not well respected existing literature to generate a clear gap and aim of this paper.

Authors would like to use the 2. related work to present studies or an introductory section. Authors have not critically described related work

To develop of a new method :"Architecture Description and Methodology, authors have not presented the rationale authors do this.

 The experimental environment should be a part of the research methods. In addition, authors has briefly introduced by the results. This should be future expanded.

Author Response

We appreciate the time and effort form Editorial Board and the reviewers dedicated to providing feedback on our manuscript. We are grateful for the insightful comments on valuable improvements to our paper. We have incorporated all of the suggestions made by reviewers. Changes are highlighted in the manuscript. Please see below the attachment for a point-by-point response to the reviewer’s comments and concerns.

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

1. Please add a few words of comment to the drawing
2. The title should probably read: "Feature Extraction for Cocoa Beans Digital Image Classification Prediction for Smart Farming Application". The article describes a method intended for Smart Farming and not currently used in such systems.
3. In the Conclusion part you should find a reference to Smart Farming (it is in the title of the article)

Author Response

Manuscript ID: agronomy-938644 - Minor Revisions- Due to 4 Oct
Respected Editor,
Journal Agronomy (ISSN 2073-4395; CODEN: ABSGGL)
Special Issue Editors,
Prof. Dr. Thomas Scholten, Dr. Ruhollah Taghizadeh-Mehrjardi and Dr. Karsten Schmidt
Special Issue “Machine Learning Applications in Digital Agriculture”
Thank you for allowing to submit a revised draft of the manuscript:
• Title: Feature Extraction for Cocoa Beans Digital Image Classification Prediction in Smart Farming Application
• Authors: Yudhi Adhitya *, Setya Widyawan Prakosa, Mario Köppen, Jenq-Shiou Leu

We appreciate the time and effort form Editorial Board and the reviewers dedicated to providing feedback on our manuscript. We are grateful for the insightful comments on valuable improvements to our paper. We have incorporated all of the suggestions made by reviewers. Changes are highlighted in the manuscript. Please see below the attachment on the next page for a point-by-point response to the reviewer’s comments and concerns.

Thank you for your consideration.
on behalf of the authors.

Yudhi Adhitya
Ph.D. Student
Graduate School of Creative Informatics
Department of Computer Science and Systems Engineering
Kyushu Institute of Technology Fukuoka 820-8502, Japan
[email protected], [email protected]

Author Response File: Author Response.pdf

Reviewer 2 Report

I believe authors have significantly improved this paper. Authors should further improve this paper in several aspects:

1. Research significance should be added at the end of abstract
2. The introduction has been improved a lot. The inclusion of Figure 1 is attractive. Why not also include the traditional farming concept as a comparison to the smart farming concept.
3. The title of Figure 1 should be more comprehensive
4. You are suggested to separate the current 2. Materials and Methods into to two parts: one for development of the methodology for textural feature analysis on cocoa bean's digital images; the other for the application of this methodology or case study. Readers will then be attracted by your novel methodology. The case study and the results will be more clear.

Therefore, the outline of this paper will be:

1. Introduction
2. Development of a new methodology for textural feature analysis on cocoa bean's digital images
3. Case study and results (in this part, you will include some materials and experiments description and results analysis).
4. Discussion
5. Conclusions

I hope you can follow this pattern. Thanks.

Author Response

Manuscript ID: agronomy-938644 - Minor Revisions- Due to 4 Oct
Respected Editor,
Journal Agronomy (ISSN 2073-4395; CODEN: ABSGGL)
Special Issue Editors,
Prof. Dr. Thomas Scholten, Dr. Ruhollah Taghizadeh-Mehrjardi and Dr. Karsten Schmidt
Special Issue “Machine Learning Applications in Digital Agriculture”
Thank you for allowing to submit a revised draft of the manuscript:
• Title: Feature Extraction for Cocoa Beans Digital Image Classification Prediction in Smart Farming Application
• Authors: Yudhi Adhitya *, Setya Widyawan Prakosa, Mario Köppen, Jenq-Shiou Leu

We appreciate the time and effort form Editorial Board and the reviewers dedicated to providing feedback on our manuscript. We are grateful for the insightful comments on valuable improvements to our paper. We have incorporated all of the suggestions made by reviewers. Changes are highlighted in the manuscript. Please see below the attachment on the next page for a point-by-point response to the reviewer’s comments and concerns.

Thank you for your consideration.
on behalf of the authors.

Yudhi Adhitya
Ph.D. Student
Graduate School of Creative Informatics
Department of Computer Science and Systems Engineering
Kyushu Institute of Technology Fukuoka 820-8502, Japan
[email protected], [email protected]

Author Response File: Author Response.pdf