Sugarcane Yield Forecast in Ivory Coast (West Africa) Based on Weather and Vegetation Index Data

Round 1

Reviewer 1 Report

1. Line 51-52, The references of the full text are too old. Try to cite the literature in recent 5 years, and quote the papers of journals with high impact factors. Literature 8 is too old, please refer to IPCC AR6 WG1 Chapter 12 and Atlas. literature 4 and 9 are also very old, which can not explain the problem.
2. Line 78, Climate service is very important. In the final conclusion of your paper, it is mentioned again that climate service is a good method to deal with disaster risk. Disaster early warning is a new tool and also the key direction of WMO's future development of climate service. Please add literature to express it.
3. Line 128-134, This paragraph is unnecessary and can be deleted.
4. Line 390-391, Simple yield normalization and Evolution of standardized yields can not reflect the relationship between historical yield and temperature & precipitation. Regression analysis is widely used and discussed in your article. It is suggested to supplement this missing content. The effects of temperature and precipitation on historical yield were analyzed by quadratic orthogonal rotary regression equation. I noticed your Table 5, but unfortunately, there is no process. Therefore, the key missing part of the full text is here, which should be added.
5. Line 451, Figure 5, line 462, Figure 6, line 518, Figure 3….. There are some small mistakes in the article, which should be carefully checked and revised before submission.
6. Line 536-537, The fitting equations of the full text should be listed and should not be deleted. At the same time, the R2 in the article is very low, which actually reflects that the regression model can not be well expressed, In most scientific experiments, R2 will be greater than 0.85.

Author Response

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Author Response File: Author Response.docx

Reviewer 2 Report

Comments_Atmosphere-1402889:  Sugarcane yield forecast in Ivory Coast (West Africa) based on weather and vegetation index data

Recommendation: MINOR Revisions

The subject paper is a nice effort to forecast the sugarcane yield based on two important data sets i.e., weather and vegetation index. The message and idea of the paper are appealing and structured appropriately. The language of the paper needs some sort of improvement, however.

Title: The title is ok.

Abstract: The abstract is ok. However, I would suggest the author to mention the names of satellite variables for clarity of the content.

Introduction: It is well-presented and coherently developed if some punctuation marks, typos or grammatical or mistakes are handled with just a thorough read by the authors.

Moreover, I would like to suggest the authors to cite some latest studies with climate change impact on crops along with adaptation strategies, not from South African rainfed territories, but also rainfed areas of other most vulnerable regions to climate change like Pakistan (e.g., Mahmood et al. 2019, Mahmood et al. 2020) to highlight the importance of rainfed agriculture under climate change globally.

Study area and data: The author has drafted this section in a very good way. However, there are couple of small concerns:

Does the meteorological data for the said period in the manuscript is sufficient for the analyses?

Which technique was used by the author to overcome the problem of missing values? Because dropping the station(s) from analysis due to missing is not right option.  

Methodology: This section is comprehensively written, and it is ok

Results and Discussion: Overall, results are well-presented with fewer than required implications. Why are the regression results not presented in table 1?

Is it sufficient to include only cropping practices in the model along with climatic variables?

Conclusion: Based on the used methods and obtained results, this section is fine.

• Mahmood, N., Arshad, M., Kächele, H., Ma, H., Ullah, A., & Müller, K. (2019). Wheat yield response to input and socioeconomic factors under changing climate: Evidence from rainfed environments of Pakistan. Science of the Total Environment, 688, 1275-1285.

 

• Mahmood, N., Arshad, M., Kächele, H., Shahzad, M. F., Ullah, A., and Müller, K. (2020). Fatalism, climate resiliency training and farmers’ adaptation responses: Implications for sustainable rainfed-wheat production in Pakistan. Sustainability, 12(4), 1650.

Author Response

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Author Response File: Author Response.docx

Reviewer 3 Report

General Comments

The present study investigates the perspective to anticipate sugarcane production prior to harvest based on a set of cropping practices, meteorological and satellite data by utilizing linear regression and machine learning models.

It is interesting and well-structured research. However, Some Figures need a serious improvement of quality (see specific comments in the following comments and the attached file)

In general, I believe that it is noteworthy research with an interesting topic that requires in general minor revision. Nevertheless, since the improvement of the Figures is crucial for the enhancement of the manuscript quality I suggest a major revision in order to check this upgrade.

 

Some Specific Comments

Abstract	The Abstract is much longer than 200 words. I think you should decrease it
Lines 108-127:	These two paragraphs can be merged into one since they have 1-2 similar sentences and a different objective of used models.
Figure 1	I think that this figure is quite amateur. No coordinates, no place-names, north arrow. Also, the map of the Cultivated Plots could be larger and more detailed
Lines 185-189	The places of the meteorological stations should be plotted in Figure 1 or in another Figure, and probably with a different shape or color to present which of those finally utilized.
Table 1	Table 1 is not referenced in the text
Section 2.2.3	I think that a Figure which will demonstrate the final images of NDVI and EVI calculated indices, is necessary for this section.
Line 208	It absorbs also in the Green spectral zone?
Line 212	Probably you mean NIR (near infrared)
Line 227	...providing less saturated results
Figure 2	This Figure needs improvement (very low quality)
Table 2	The Table 2 reference is missing in the text
Figure 3	Low quality, needs improvement
Figure 4	Same comment as in Figures 2 & 3. Also, more subdivisions on the Y-axis are needed (elongation of the ax) in order to become more obvious the difference
Line 451	Of course it is not Figure 1, correct it
Lines 462-463	Of course, it is not Figure 2, correct it The words on the Y-axis can't be read
Lines 518-519 & 526-527	You should correct the Figures’ numbering

 

Comments for author File: Comments.pdf

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Round 2

Reviewer 1 Report

All the problems have been solved and can be accepted for publication

Reviewer 3 Report

The authors have addressed all comments and remarks. I suggest the manuscript to be accepted in its current form and considered for publication.