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Data Descriptor
Peer-Review Record

A Data Descriptor for Black Tea Fermentation Dataset

Reviewer 1: Anonymous
Reviewer 2: Anonymous
Received: 9 March 2021 / Revised: 15 March 2021 / Accepted: 15 March 2021 / Published: 19 March 2021
(This article belongs to the Special Issue Machine Learning in Image Analysis and Pattern Recognition)

Round 1

Reviewer 1 Report

Thanks to the authors for updating the manuscruipt and for providing good clarifications.

Author Response


We would like to express our sincere appreciation for your constructive comments and suggestions which have improved our manuscript. Thank you.

Author Response File: Author Response.pdf

Reviewer 2 Report

This revised vesion is improved greatly. Some issues should be addressed before further processiing. 

  1. The conclusion should be rewritten, among which  "Specifically, these approaches are needed in this era of Covid-19  where social distance and other protocols must be adhered to. In our future studies, we endevour to collect fermentation images of coffee and cocoa." is not supported by the results.
  2.  Figure 4 should be expressed as a Table. 

Author Response

We would like to appreciate your important comments on our manuscript. Please see as an attachment our responses to each of your comments and suggestions.

Author Response File: Author Response.pdf

This manuscript is a resubmission of an earlier submission. The following is a list of the peer review reports and author responses from that submission.


Round 1

Reviewer 1 Report

    Fermentation is a key process in the formation of black tea quality. The optimum fermentation level is traditionally evaluated by sensory assessment. The manuscript describes a method to collect parameters including images, temperature and humidity conditions in which tea leaf color changing from green to coppery brown was signified optimum fermentation levels. The topics is interesting. However, some issues should be clarifies before further processing.

    1.A full dataset should be collected as described in Figure 1 and submitted as supplements for reuse by the readers.

    2.The presented dataset should be verified by an independent experiment.

Reviewer 2 Report

-the paper is too short, 10 pages is well
-please add measurement + arrows what is what?;;;
-please add block diagram of the proposed research step by step ;;; what is the result of paper?;;;
-please add block diagram of the proposed method;;;
-please add photo/photos of application of the proposed research ;;;;
-please add sentences about future analysis;;;
-The authors should put at least 20-30 references (50% of them should be 2018-2021 Web of Science).;;;
-The authors should show knowledge. Please compare with other methods;;;

Reviewer 3 Report

This manuscript has a title inducing the reader in a false path. It is describing only a dataset collection process.

This manuscript only describes a dataset collection with an IoT platform and not a data mining process by using machine learning techniques.

The data collection must be structured better, potential issues and data discrepancies must be discussed.

 

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