MISPEL: A Multi-Crop Spectral Library for Statistical Crop Trait Retrieval and Agricultural Monitoring
Round 1
Reviewer 1 Report
As a reviewer, I am pleased to have the opportunity to review the paper titled "MISPEL: A Multi-Crop Spectral Library for Statistical Crop Trait Retrieval and Agricultural Monitoring." This study addresses a significant scope by integrating remotely sensed crop traits into crop growth models, enabling seamless crop monitoring and yield forecasting. The findings of this research hold great value for farmers as they can make informed management decisions, leading to more sustainable precision farming practices, improved resource efficiency, and better cost-benefit ratios. I am inclined to accept the paper with a few minor concerns.
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Question on sampling design: I would appreciate it if the authors could describe the design of SSUs (Subsampling Units) within an ESU (Essential Sampling Unit). This clarification would enhance the reader's understanding.
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Error in the caption of Figure 2: I believe there is an error in Figure 2, where it should refer to leaf area index (LAI). Please correct this discrepancy.
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The caption of Table 2: In the caption of Table 2, please describe what "N" represents to provide better clarity.
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Lines 140 and 141: I found lines 140 and 141 confusing. The authors mention that fresh above-ground biomass was determined by destructive harvesting of the "entire plot." Could you please clarify whether the entire plot refers to an ESU? Additionally, it would be helpful to explain whether biomass was harvested for each SSU and then assigned a mean value for each ESU. Furthermore, please provide details regarding the units used for measuring biomass (e.g., grams per square meter).
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Division of section "2.2.1. Hyperspectral Measurements and Reference Data Acquisition": To improve comprehension, I suggest dividing the section "2.2.1. Hyperspectral Measurements and Reference Data Acquisition" into two separate sections.
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Line 182: Could you please clarify the meaning of the ABBBB sequence mentioned in line 182? If it is not a well-known sequence, please provide a description for better understanding.
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Line 202: This study must emphasize the significance of using normalized root mean square error (NRMSE, Eq. 3). Please explain its relevance.
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DEMMIN test site: Considering that DEMMIN is also a city in Germany, it would be helpful to properly distinguish or define the abbreviation of DEMMIN as it relates to the test site.
- Add the key findings (with R2 and RMSE values) again to the conclusion and in the same order as the research objectives defined in the introduction. Please note that after publication, the conclusion should be read in isolation.
Author Response
Please see the attachment.
Author Response File: 
Author Response.docx
Reviewer 2 Report
The article is of high interest in the scientific community as it fills gaps in remote sensing-based derivation of crop traits. Therefore, I have only two general comments:
1) Even after rereading the draft, it has not become clear to me whether and in what way MISPEL is or should be available to potential users. Please address this in the revision.
2) Some chapters are very difficult to read, especially due to the juxtaposition of the results for the different models when using the respective abbreviations. Examples are lines 280 to 289, 291 to 303, and 311 to 321. More generalization could be made here. The specific results could be better presented in tables or figures, if not already done anyway.
Author Response
Please see the attachment.
Author Response File: Author Response.docx
Reviewer 3 Report
This paper establish a newly comprehensive spectral library (MISPEL) to derive diverse crop traits of multiple crops in Germany. It is interesting work. Minor information for revised as below:
Figre 3, 4, 5, can be figured as color.
Section 4.2 need more clear to discuss the effort of validation, not only about RSQ, NRMSE, RMSE etc.
Author Response
Please see the attachment.
Author Response File: Author Response.docx
