Estimating leaf nitrogen concentration based on the combination with fluorescence spectrum and first-derivative

Leaf nitrogen concentration (LNC) is a major indicator in the estimation of the crop growth status which has been diffusely applied in remote sensing. Thus, it is important to accurately obtain LNC by using passive or active technology. Laser-induced fluorescence can be applied to monitor LNC in crops through analysing the changing of fluorescence spectral information. Thus, the performance of fluorescence spectrum (FS) and first-derivative fluorescence spectrum (FDFS) for paddy rice (Yangliangyou 6 and Manly Indica) LNC estimation was discussed, and then the proposed FS + FDFS was used to monitor LNC by multivariate analysis. The results showed that the difference between FS (R2 = 0.781, s.d. = 0.078) and FDFS (R2 = 0.779, s.d. = 0.097) for LNC estimation by using the artificial neural network is not obvious. The proposed FS + FDFS can improved the accuracy of LNC estimation to some extent (R2 = 0.813, s.d. = 0.051). Then, principal component analysis was used in FS and FDFS, and extracted the main fluorescence characteristics. The results indicated that the proposed FS + FDFS exhibited higher robustness and stability for LNC estimation (R2 = 0.851, s.d. = 0.032) than that only using FS (R2 = 0.815, s.d. = 0.059) or FDFS (R2 = 0.801, s.d. = 0.065).

Decision letter (RSOS-191941.R0) 17-Jan-2020 Dear Dr Yang: Title: Estimating leaf nitrogen concentration based on the combination with fluorescence spectrum and first-derivative Manuscript ID: RSOS-191941 Thank you for submitting the above manuscript to Royal Society Open Science. On behalf of the Editors and the Royal Society of Chemistry, I am pleased to inform you that your manuscript will be accepted for publication in Royal Society Open Science subject to minor revision in accordance with the referee suggestions. Please find the reviewers' comments at the end of this email.
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Once again, thank you for submitting your manuscript to Royal Society Open Science. The chemistry content of Royal Society Open Science is published in collaboration with the Royal Society of Chemistry. I look forward to receiving your revision. If you have any questions at all, please do not hesitate to get in touch. ********************************************** RSC Associate Editor: Comments to the Author: (There are no comments.) RSC Subject Editor: Comments to the Author: (There are no comments.) ********************************************** Reviewer comments to Author: Reviewer: 1 Comments to the Author(s) Please see the attached file Reviewer: 2 Comments to the Author(s) The manuscript presents interesting results on application of fluorescence excitation spectra for estimation of leaf nitrogen content in rice leaves. The innovativeness of the study is in application of first-derivative spectra instead of traditional approaches, which led to improvements in estimation when using the multivariate analysis. The manuscript is very well written, the text is clear an concise. The abstract is mostly informative and accurate. The study is well introduced, including clear aims. The description of material and methods is very brief, but mostly sufficient. Results are well presented and appropriately discussed. Overall, the quality of the manuscript is high, and the results are worth to be published. I recommend accepting the manuscript for publication after addressing my comments within MINOR REVISION.
Comments: 1. Based on the title or abstract, the reader has no idea what kind of crop the subject of the study was. Please, provide the information into the abstract, including the type of rice and genotypes used. 2. Please, explain more in detail the "an absolute block design" used in this study. 3. Please, indicate what kind of mathematical or statistical software was used for calculations and analyses. 4 In Fig. 2 and 4 captions, put the information about the small graphs (inserts) added together with the main distribution graphs.

Reviewer: 3
Comments to the Author(s) The authors present a method useful for non-invasive estimation of paddy rice leaf nitrogen concentration, which has been widely utilized in remote sensing. In this study, the laser-induced fluorescence (LIF) was analyzed using the fluorescence spectrum (FS) and first-derivative fluorescence spectrum (FDFS). And the principal component analysis was used for main fluorescence characteristics extraction. The proposed method is quite innovative, and, based on the results, seems to be quite efficient. 1. Authors are advised to show more details on the materials, such as the growing period, picking time, and the fluorescence lidar detection time. 2. Any experimental photo is preferred.
3. Why PCA is selected and its principle should be added. 4. A space is generally placed between the unit of measure and the quantity. Percentages and angles are exempted from this rule. 5. The font size in figures should be resized to be clear.

Response:
Thank you very much for your comments. According to the advices, the manuscripts has been checked again.

Response:
Thank you very much for your helpful advices.
"Xi" has been revised to the form of mathematics formula "Xi".

Response:
Thank you very much for your helpful advices.
"i" denotes the corresponding wavelength in this manuscript. Which relative content has been added "i is the corresponding wavelength".

Response:
Thank you very much for your helpful advices.
In this paper, the major target is to analyze the performance of fluorescence spectrum (FS) and first-derivative fluorescence spectrum (FDFS) for paddy rice (Yangliangyou 6 and Manly Indica) LNC estimation, and then the proposed FS+FDFS was used to monitor LNC by multivariate analysis. Thus, the second-derivative FS was not used in this paper. However, the application of second-derivative FS in the LNC estimation is good ideas, we will discuss in the next work.

Response:
Thank you very much for your helpful advices.
The description of PCA was showed in 3.4. Analytical Methods "Principal Component Analysis (PCA) can efficiently reduce the number of original parameters by extracting the key characteristics variables and deleting lower-level components.
However, the major spectral information will be not lost [47]. Thus, PCA served as a statistical multivariate analysis method was applied in data dimension reduction [48].
The extracted variables can be calculated by the linear combinations of the original variables. Therefore, the analysis procedure will be greatly simplified by utilizing fewer extracted parameters than the original data [49]." 6. The font size in figures 2 and 3 should be larger.

Response:
Thank you very much for your helpful advices.
The figures were prepared according to the Author Instruction, which with 300dpi.
Thank you very much for your help.

Reviewer: 2
Comments to the Author(s) The manuscript presents interesting results on application of fluorescence excitation spectra for estimation of leaf nitrogen content in rice leaves. The innovativeness of the study is in application of first-derivative spectra instead of traditional approaches, which led to improvements in estimation when using the multivariate analysis.
The manuscript is very well written, the text is clear an concise. The abstract is mostly informative and accurate. The study is well introduced, including clear aims. The description of material and methods is very brief, but mostly sufficient.
Results are well presented and appropriately discussed. Overall, the quality of the manuscript is high, and the results are worth to be published. I recommend