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Article
Peer-Review Record

The Impact of Wet Fermentation on Coffee Quality Traits and Volatile Compounds Using Digital Technologies

Fermentation 2023, 9(1), 68; https://doi.org/10.3390/fermentation9010068
by Hanjing Wu 1, Claudia Gonzalez Viejo 1,*, Sigfredo Fuentes 1, Frank R. Dunshea 1,2 and Hafiz A. R. Suleria 1,3,*
Reviewer 1:
Reviewer 2: Anonymous
Reviewer 3:
Reviewer 4: Anonymous
Fermentation 2023, 9(1), 68; https://doi.org/10.3390/fermentation9010068
Submission received: 8 December 2022 / Revised: 5 January 2023 / Accepted: 10 January 2023 / Published: 13 January 2023

Round 1

Reviewer 1 Report

The current manuscript reports the assessment of wet fermentation impact on coffee quality using digital technologies.

In general, this is an important and interesting work, well-written, logically structured. The results obtained were qualitatively discussed by the authors. I have only one remark. In the section Sample preparation, I would like to see more specifics in the description of the studied coffee samples, how many samples were taken for research in total, in what quantity each sample was taken, did the authors somehow take into account the place where the coffee was grown?

Author Response

Thank you for reviewing our manuscript and your suggestion for minor revision. We really appreciate your time, efforts, and support to improve our final version. Detailed response has been attached.

Author Response File: Author Response.pdf

Reviewer 2 Report

Please see attached review report.

Comments for author File: Comments.pdf

Author Response

Thank you for carefully reviewing our manuscript and your valuable comments and suggestions. The manuscript has been revised accordingly. We really appreciate your time, efforts, and support to improve our final version. The whole English of manuscript has been reading and polished by Dr. Claudia Gonzalez Viejo and Prof. Frank Dunshea. Detailed response has been attached. Thanks.

Author Response File: Author Response.pdf

Reviewer 3 Report

1 Revise manuscript title, check using word assessment 

2. Revise list of keywords, remove those words which are already in title 

3. Avoid using too short forms in the abstract 

4. Add practical application of study in abstract 

5. Add research gap and objectives of study 

6. add sample pictures 

7. some of the headings seems to incomplete, such as sat of what? 

8. 2.5 E nose why description needed

9. ANN process diagram is missing 

10 Table 1 if four sized reported why not average values ??

11. Color difference determination equation is missing 

12. add relevant research papers 

13 Referhttps://www.researchgate.net/profile/Murlidhar-Meghwal/publication/355066642_Determination_of_Engineering_Properties_of_Coffee_Beans_and_Coffee_Powder/links/615c468ffbd5153f47dd52cb/Determination-of-Engineering-Properties-of-Coffee-Beans-and-Coffee-Powder.pdf

Author Response

Thanks for your kind suggestions for minor revisions. We sincerely appreciate your time and support to improve our final manuscript. Detailed response has been attached.

Author Response File: Author Response.pdf

Reviewer 4 Report

Dear Authors,

the topic presented by you takes up an interesting subject, which undoubtedly has a high practical application. The work is very good, underpinned by an excellently prepared methodology and a clear and coherent description of the results. I ask you to address some of the comments below, which will enrich your manuscript with interesting and useful information.

Please provide a brief commentary on where exactly the research was conducted-this always increases the value of the work.

Why was only one buffer solution used to calibrate the device (pH measurement)? Normally we use 3 buffers-acidic, neutral, alkaline.

On what basis was the number of neurons in the subsequent hidden layers of the models selected?

Why wasn't a validation set separated for the cases included in the models?

What network learning method was chosen and why?

How many cases did you use to evaluate the validity of the models?

What other model evaluation errors could you use to evaluate the predictive properties of the neural models? I recommend reading the paper: 10.3390/agronomy11050885

Please include in the discussion 5 additional papers addressing similar topics from the last 10 years. 

 

Author Response

Thank you for your time and wonderful suggestions regarding content improvement. We really appreciated your time, positive opinion, support, and wonderful recommended papers to improve our final manuscript. Thanks! Detailed response has been attached.

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

Dear Authors, the revised version of the manuscript was much improved and carefully redrafted. I do appreciate all the effort made by Authors for improving quality of presented work. In my opinion, revised manuscript meets journal requirements and may be suitable for reconsidering its publication.

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