Hyperspectral Estimation of Chlorophyll Content in Wheat under CO₂ Stress Based on Fractional Order Differentiation and Continuous Wavelet Transforms

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

This study effectively integrates fractional order differentiation (FOD) and continuous wavelet transform (CWT) to enhance the estimation of SPAD values in winter wheat under CO2 stress. By overcoming challenges such as spectral sensitivity and baseline drift, the authors achieve high precision in SPAD estimation, with an impressive R² value of 0.906. This approach not only improves the accuracy of SPAD measurements but also offers valuable insights into the effects of CO2 stress on plant health, providing a robust tool for agricultural management and climate adaptation.

 

Line 94-96：How do you control the CO2 concentration? In an airtight greenhouse? How long does it take each time? How does it work？ Please explain those questions and it is best to show the experiment in pictures.

Line103:  How to measure the CO2 stree? What methods were used?

Line 105: Where do the five winter wheat leaves located?  

Line167: The parameters R,i,j of the equtions (1),(2),(3) should be explained.

Line176: The formulas of vegetation indices in Table1 should be marked with source references.

Line179: Table 1. Please adjust the format to follow the Three-Line Table style.

Line189: It would be better to include the equotions for model evaluation.

Line 194-214: Authors should used ANOVA to evaluate the effect of reproductive period and CO2 stresses to SPAD. And the results of multiple comparisons should be marked in Figure 1.

Line 233: Canopy spectra or leaf spectra?

Line397,398,445: The abbreviation of decision tree regression,‘DT’, in line397,398,445:  should consisten with’DTR’ in line 77.

Line446: The excetly deviation values of Figure9(e), Figure10(e), Figure11(e) should be calculated and compared.

Line 461-467: These sentences are better to be moved to the part of introduction. And what is the meaning of CO2 leakage? This description seems not to be correct.

Lin 510: I think one of the important conclusions is the different band of different CO2 stress. The finding of key band will be useful for monitoring the effect of CO2 to wheat yield in larger area. And the conclusion can be displayed in the abstract.

 

 

Comments on the Quality of English Language It is recommended to find native English speaker to modify the language.

Author Response

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Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

The atmospheric concentration of carbon dioxide (CO2) has been constantly increasing, and it is expected to reach 800 ppm at the end of this century. It is well documented that elevated CO2 has various effects on C3 crops, including reducing stomatal conductance, improving net CO2 assimilation rate, enhancing water use efficiency and grain yield. Winter wheat is one of the most important crops in the world, contributing about 20% of the total dietary source of protein. The effects of CO2 on winter wheat physiology, grain yield and quality have been well documented. This suggested that there was a significant interactive effect of genotypes and CO2 on winter wheat physiology. Therefore, understanding the response of winter wheat cultivars to CO2 is of great significance to cope with future climate change and improve crop yield. As such, this study aims to introduced the fractional order derivative (FOD) and continuous wavelet transform (CWT) techniques into the estimation of winter wheat chlorophyll content (SPAD). The results show that the proposed method is of great reference value for the estimation of physiological parameters of other crops under similar environmental stresses.

I think this study is some progress by focusing on SPAD in wheat under CO2 stress based on fractional order differentiation and continuous wavelet transforms. Generally, some revision suggestions are listed below:

1) It's better to add paper review for effects of elevated CO2 on winter wheat in '1. Introduction' since your research is closely associated with this topic.

2) It's better to add a map to illustrate spatial distribution of research area.  Furthermore, takeaway for Practice of your methodology in different geographical locations and climate types is also encouraged to be included in this paper. It should be clear enough to present its universality for local practice.

3) Describe the inadequacy of your study, and based on such inadequacy discuss the future research directions. The current discussion is insufficient.

Author Response

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Reviewer 3 Report

Comments and Suggestions for Authors

1. The data collection process is not well described.

2. In the section on materials and methods, materials are confused with research methods.

3. There are two serial numbers in section 3.7. Please change them.

Author Response

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Reviewer 4 Report

Comments and Suggestions for Authors

In this work, FOD and CWT were introduced in the article to estimate winter wheat SPAD. Besides, combined with the raw hyperspectral data, the machine learning algorithms were used to analyze the spectral response characteristics of winter wheat SPAD under CO₂ stress. I think the manuscript is in the scope of the Remote Sensing and can be considered for the publication after minor revision. The following comments should be clarified before publish.

Comment 1: Learning regression models were used to analyze the spectral response characteristics of winter wheat SPAD under CO₂ stress. However, the abstract does not reflect any learning regression model. The author revise it.

Comment 2: A schematic diagram of the measurement system should be described.

Comment 3: What is the ratio of the prediction set to the training set? The author needs to clarify.

Comment 4: In Figure 9 legend, the author should explain what a-d represent respectively

Comments on the Quality of English Language

English requires minor modifications.

Author Response

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Reviewer 5 Report

Comments and Suggestions for Authors

There is a fundamental error in this paper: SPAD is not chlorophyll content. SPAD is simply an indicator highly correlated with chlorophyll content. Chlorophyll content can be determined by chemical experiments on plant material. SPAD is an indicator of an instrument developed by choosing a wavelength highly correlated with chlorophyll content. Since SPAD itself utilizes specific wavelengths (also described by the authors), understanding the long wavelengths not utilized by SPAD may be a certain scientific finding. At the very least, the study should be planned with an understanding of the findings of McClendon and Fukshansky (1990) and Markwell (1995), and the current description has absolutely no value as a scientific paper.

Comments on the Quality of English Language

There are no problems.

Author Response

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Author Response File: Author Response.pdf

Round 2

Reviewer 5 Report

Comments and Suggestions for Authors

OK

Comments on the Quality of English Language

OK