Indirect Quantitative Analysis of Biochemical Parameters in Banana Using Spectral Reflectance Indices Combined with Machine Learning Modeling

Round 1

Reviewer 1 Report

Good work. It would be appreciable if you add little bit more about the plant material and its traits. Since biochemical variation is highly depend upon the genotype, shape, size and geographical origin. 

Also mention the method and software which you used for comparing means and other parameters statistically.  

Too much old references could be replaced with latest, if possible. 

Line 40 - give species name and make it italic

Line 49 - start line with "Being a perishable crop"

Line 57- use microclimatic conditions instead of environmental circumstances 

Line 60 - use livelihood instead of living conditions 

Line 62- add reference 

Line 111- if possible add reference of banana

Line 129- add morphological traits of bunches

Line 230 - add reference 

Line 244 - fruits

Line 250 - check references 

Line 309 - who published?

 

Author Response

Response: We greatly appreciate your critical observations as well as your constructive and helpful comments. We hope that we could address your questions/comments by the explanations and revisions made in the manuscript.

Good work. It would be appreciable if you add little bit more about the plant material and its traits. Since biochemical variation is highly depend upon the genotype, shape, size and geographical origin. Also mention the method and software which you used for comparing means and other parameters statistically.  

Response: many thanks for comment. We have added the name banana cultivar at materails and methods in line 141.  Also we have added the new section (2.9. Statistical analysis) to cover this point data analysis.

Too much old references could be replaced with latest, if possible. 

Line 40 - give species name and make it italic

Response: many thanks for comment. We added species name at line 41.

Line 49 - start line with "Being a perishable crop".

Response: many thanks for comment. It was modified at line 50.

Line 57- use microclimatic conditions instead of environmental circumstances 

Response: many thanks for comment. It was modified at line 59.

 

Line 60 - use livelihood instead of living conditions 

Response: many thanks for comment. It was modified at line 61.

Line 62- add reference 

Response: many thanks for comment. It was added.

Line 111- if possible add reference of banana

Response: many thanks for comment. It was added.

Line 129- add morphological traits of bunches

Response: many thanks for comment. We have added the name of cultivar at line 41 and the bunches at full mature. Since we did not measured morphological traits of bunches.

Line 230 - add reference 

Response: many thanks for comment. It was added.

Line 244 – fruits

Response: many thanks for comment. It was modified at line 267.

Line 250 - check references 

Response: many thanks for comment. It was modified at line 272.

Line 309 - who published?

Response: many thanks for comment. The published indices as describe at table 1.

Author Response File: Author Response.docx

Reviewer 2 Report

Dear Authors,

I had the opportunity to read and review the manuscript entitled „Indirect Quantitative Analysis of Biochemical Parameters in Banana Using Spectral Reflectance Indices Combined With Machine Learning modeling” (ID Horticulturae-1714240).

A major objective of the manuscript is to examine the biochemical parameters of banana fruits at different stages of ripening using published and newly developed spectral reflectance indices (SRIs), and machine learning modeling (Artificial Neural Networks and support vector machine regression; SVMR).

I find the manuscript to be interesting and within the scope of the journal. The relevant aspects of the topic are present. This study contributes to the development of a methodology for assessing the biochemical characteristics of fruit species, as well as providing technological assistance for monitoring and assessing the quality of banana fruits during artificial ripening and storage.

My review below suggests some improvements.

Title: Informative and consistent with the study's content.

Abstract: The abstract is clear and reasonable. In my opinion, in the abstract, the authors should present the main findings in a descriptive way. The numerical results should be included in the Results and Discussion section.

Keywords: In my opinion, the keywords are consistent with the content of the study.

1. Introduction: This section provides adequate insight into the research issues, and points out the timeliness and importance of the research topic.
2. Materials and methods: The measured physical and chemical parameters, as well as the spectral reflectance measurements and model specifications, are described clearly. It would also be good to mention the statistical tests used, such as ANOVA with Duncan's post hoc test.
3. Results and Discussion: In my opinion, the evaluation of the results is correct. The fundings of the study were compared with the results of previous research.

In Tables 2-4, for a better comparison of the mean values, I suggest providing the minimum and maximum values in parentheses next to the mean.

In Table 4, please check the letter notation for GI: if there are two groups, please use 'a' and 'b', not 'a' and 'c'.

Lines 311-312 (411-412): Proposed wording: The published SRIs also significantly determined the selected biochemical parameters.

The title of Table 5 should be corrected. Proposed title: The adjusted coefficients of determination measuring the proportion of variance in Chl a, Chl b, respiration rate, TSS, and firmness that can be explained by twenty-seven SRIs of banana fruits.

4. Conclusion: Although this section is short, it presents, in my opinion, the most relevant findings. The section can be extended by comparing the findings of the study with those of previously published publications.

Author Response

I had the opportunity to read and review the manuscript entitled „Indirect Quantitative Analysis of Biochemical Parameters in Banana Using Spectral Reflectance Indices Combined With Machine Learning modeling” (ID Horticulturae-1714240).

A major objective of the manuscript is to examine the biochemical parameters of banana fruits at different stages of ripening using published and newly developed spectral reflectance indices (SRIs), and machine learning modeling (Artificial Neural Networks and support vector machine regression; SVMR).

I find the manuscript to be interesting and within the scope of the journal. The relevant aspects of the topic are present. This study contributes to the development of a methodology for assessing the biochemical characteristics of fruit species, as well as providing technological assistance for monitoring and assessing the quality of banana fruits during artificial ripening and storage.

Response: We greatly appreciate your critical observations as well as your constructive and helpful comments. We hope that we could address your questions/comments by the explanations and revisions made in the manuscript.

My review below suggests some improvements.

Title: Informative and consistent with the study's content.

Response: many thanks.

Abstract: The abstract is clear and reasonable. In my opinion, in the abstract, the authors should present the main findings in a descriptive way. The numerical results should be included in the Results and Discussion section.

Response: many thanks for your comments. The numerical results were reduced in abstract as possible.

Keywords: In my opinion, the keywords are consistent with the content of the study.

Response: many thanks.

Introduction: This section provides adequate insight into the research issues, and points out the timeliness and importance of the research topic.

Response: many thanks.

Materials and methods: The measured physical and chemical parameters, as well as the spectral reflectance measurements and model specifications, are described clearly. It would also be good to mention the statistical tests used, such as ANOVA with Duncan's post hoc test.

Response: many thanks for your comments. We have added the new section (2.9. Statistical analysis) to cover this point.

 

Results and Discussion: In my opinion, the evaluation of the results is correct. The fundings of the study were compared with the results of previous research.

Response: many thanks

In Tables 2-4, for a better comparison of the mean values, I suggest providing the minimum and maximum values in parentheses next to the mean.

Response: many thanks for this comment. The mean values were changed to bold format for a better comparison in tables 2 and 4.

In Table 4, please check the letter notation for GI: if there are two groups, please use 'a' and 'b', not 'a' and 'c'.

Response: many thanks for this comment. It was corrected.

Lines 311-312 (411-412): Proposed wording: The published SRIs also significantly determined the selected biochemical parameters.

Response: many thanks for this comment. It was modified.

The title of Table 5 should be corrected. Proposed title: The adjusted coefficients of determination measuring the proportion of variance in Chl a, Chl b, respiration rate, TSS, and firmness that can be explained by twenty-seven SRIs of banana fruits.

Response: many thanks for this comment. It was corrected.

Conclusion: Although this section is short, it presents, in my opinion, the most relevant findings. The section can be extended by comparing the findings of the study with those of previously published publications.

Response: many thanks. It was extended by adding the results of previously published indices at lines 443 to 445.

Author Response File: Author Response.docx

Reviewer 3 Report

I have reviewed the manuscript entitled “Indirect Quantitative Analysis of Biochemical Parameters in Banana Using Spectral Reflectance Indices Combined with Machine Learning Modeling” and found it to be excellent in both the quality of the research conducted and written presentation of the work.

The manuscript thoroughly addressed important research questions about the biochemical parameters of banana fruits such as chlorophyll a (Chl a), chlorophyll b (Chl b), respiration rate, total soluble solids (TSS), and firmness. I was impressed by the breadth of the research as it investigated from a variety of angles, including published and newly developed spectral reflectance indices (SRIs), integrated with machine learning modeling (Artificial Neural Networks; ANN and support vector machine regression; SVMR) at different ripening degrees. The experiments were well designed, the research methodologies were scientifically sound and the data were appropriately analyzed and interpreted.

The rational of research was clearly stated, the experiments were described in detail, and the results were clearly presented in tables, graphs and text. The English grammar and language were also good. so I have very few editorial suggestions for your consideration. I have indicated my editorial suggestions on attached PDF file. I would also recommend to please narrow down the abstract and introduction section.

 

 

Comments for author File: Comments.pdf

Author Response

I have reviewed the manuscript entitled “Indirect Quantitative Analysis of Biochemical Parameters in Banana Using Spectral Reflectance Indices Combined with Machine Learning Modeling” and found it to be excellent in both the quality of the research conducted and written presentation of the work.The manuscript thoroughly addressed important research questions about the biochemical parameters of banana fruits such as chlorophyll a (Chl a), chlorophyll b (Chl b), respiration rate, total soluble solids (TSS), and firmness. I was impressed by the breadth of the research as it investigated from a variety of angles, including published and newly developed spectral reflectance indices (SRIs), integrated with machine learning modeling (Artificial Neural Networks; ANN and support vector machine regression; SVMR) at different ripening degrees. The experiments were well designed, the research methodologies were scientifically sound and the data were appropriately analyzed and interpreted.The rational of research was clearly stated, the experiments were described in detail, and the results were clearly presented in tables, graphs and text. The English grammar and language were also good. So I have very few editorial suggestions for your consideration. I have indicated my editorial suggestions on attached PDF file.

Response: We greatly appreciate your critical observations as well as your constructive and helpful comments. We hope that we could address your questions/comments by the explanations and revisions made in the manuscript. We have modified the manuscript according to suggestions on attached PDF file.

 I would also recommend to please narrow down the abstract and introduction section.

Response: many thanks for this comment. The abstract and introduction section was shorted as possible.

Author Response File: Author Response.docx