Prediction of the Moisture Content in Corn Straw Compost Based on Their Dielectric Properties
Round 1
Reviewer 1 Report
Title: Prediction of Moisture Content in Corn Straw Compost Based on Dielectric Properties
In the manuscript, the authors (Wang et al.) present a new method to predict moisture content in corn straw compost. The proposed method utilizes change of the frequency-dependent complex-valued dielectric constant of the compost that is also dependent on temperature, moisture level, and density of the compost. The core of the proposed method is the PCA-SVR combined algorithm which is shown in Fig. 3 of the manuscript. Both concept and procedure are well explained.
Overall, the results provided in the manuscript are sufficiently convincing as, in particular, shown in Fig. 8. Therefore, I feel that the proposed scheme for a rapid prediction of moisture level is very well demonstrated. In this sense, I would like to recommend this manuscript for publication in the Applied Sciences after a minor revision regarding the following issues.
Minor issues
1. In Figure 8, the results provided look like normalized ones: both measured and predicted values are ranging from 0 to 1, and do not represent the actual values for the moisture content. I recommend the authors to specify how the measured/predicted values can be translated to the moisture content.
2. If I understood correctly, error bars should be available for all predicted values. If so, I would like to suggest to add the error bars.
3. Rp2 in 11th and 12th pages should be Rp2.
Author Response
Response to Reviewer 1 Comments
Point 1: In Figure 8, the results provided look like normalized ones: both measured and predicted values are ranging from 0 to 1, and do not represent the actual values for the moisture content. I recommend the authors to specify how the measured/predicted values can be translated to the moisture content.
Response 1: Thanks for your suggestion, we have changed the measured and predicted values into the moisture content. (Line 321-323)
Point 2: If I understood correctly, error bars should be available for all predicted values. If so, I would like to suggest to add the error bars.
Response 2: Thanks for your suggestion, we have added the error bars. (Line 324 -325)
Point 3: Rp2 in 11th and 12th pages should be Rp2.
Response 3: Dear reviewer, we apologize for this mistake. We have checked and modified this paragraph. (Line 292-340)
Finally, thank you again for your careful reading of our paper. We hope to make progress under your guidance.
Author Response File: 
Author Response.docx
Reviewer 2 Report
Abstract:
In the abstract the main purpose of the study is introduced concretely; the contribution and the main finding are highlighted.
Introduction:
The introduction of the background of the study is profound, the quality and quantity of cited studies is good. The similar researches are well introduced. The novelty of present study is clear.
Materials and methods:
The measurement and analysis methods are introduced. The structure of the section is outstanding. All the necessary information are provided in a clear and profound manner. This can serve the reproducibility of the experiments. The figures and flowchart perfectly support the understanding pf the processes. The necessary measurement and analysis parameters are provided.
Results:
This section is also perfectly structured, each subsection focus on a clear topic / method. The figures and diagrams demonstrate the main results properly. The authors explain the obtained results well. The finding can easily be understood by the readers.
Discussion:
This section provides a good summary of the findings in a descriptive form with concrete numerical data.
Conclusion:
The main findings are clearly highlighted.
Author Response
Response to Reviewer 2 Comments
Dear reviewer,
Thanks very much for taking the time to review this manuscript. And thank you for your recognition of our manuscript. This builds confidence to pursue a more rigorous research career in the future.
Finally, thank you again for your careful reading of our paper. We hope to make progress under your guidance.
With best wishes,
Yours sincerely,
Ruili Wang
Author Response File: Author Response.docx
Reviewer 3 Report
Review of „ Prediction of Moisture Content in Corn Straw Compost Based on Dielectric Properties” by Ruili Wang, Tong Ren, Longlong Feng, Tieliang Wang and Tiejun Wang
This study concentrates on moisture content measurements based on dielectric properties of compost. Using principal component analysis to select the main variables and the support vector machine regression modeling, the proposed method was found feasible to use. The paper is well-structured and clearly presented, with reasonable explanations of the measurements and the algorithm followed to assess the obtained data and validate the method.
Thus, the manuscript is accepted with minor revision.
The review comments are listed below:
1. Please include some statements related to the method of measurement in the Introduction section: whether it was previously used for other moisture-containing materials, What were the errors given by the method in those cases?
2. Are there any data for moisture content of corn straw compost reported in the literature? Some comparisons with the current experimental data should be included.
3. English corrections are much needed.
Comments for author File: 
Comments.pdf
Author Response
Response to Reviewer 3 Comments
Point 1: Please include some statements related to the method of measurement in the Introduction section: whether it was previously used for other moisture-containing materials, What were the errors given by the method in those cases?
Response 1: Thanks for your suggestion. We have added in the introduction section some statements on the use of dielectric properties to detect other structurally similar moisture-containing materials, such as soil. And the errors of these methods are listed.
(Line 38-40)The moisture content of the initial stage of corn straw compost was about 65%, and after the fermentation was completed, it dropped to 28-35%, while the moisture content of its products must be less than 30% [7].
(Line 80-85)Lu Cai et al. [23] determined the moisture content of sew-age sludge composting materials by TDR using coated probes. TDR probes were calibrated as a function of dielectric properties that included temperature effects. The relative error was 0.92±0.72% when comparing the measured values of TDR of the samples with those of the weight method, indicating that the measured values of TDR have high accuracy.
(Line 86-91)Meanwhile, compost has a similar structure to the soil, Calamita et al.[24] investigated the capability of the resistivity measurement technique in soil moisture estimation. The result showed that the resistivity method achieved better results in monitoring soil moisture over large areas with a root mean square error of 4.4% vol/vol on average. In summary, dielectric techniques have potential applications in detecting the moisture content of corn composting materials.
7.Juan, M.; Kai, J.; Liang, S.; Mengting, W.; Xiaojie, Z.; Enshuai, D. Effects of FeSO4 dosage on nitrogen loss and humification during the composting of cow dung and corn straw. Bioresource Technology.2021, 341, 125867. https://doi.org/10.1016/j.biortech.2021.125867.
23.Cai, L.; Chen, T.; Gao, D.; et al. Time domain reflectometry measured moisture content of sewage sludge compost across temperatures. Waste Management. 2013,33(1),12-17. https://doi.org/10.1016/j.wasman.2012.09.014
24.Calamita, G.; Brocca, L.; Perrone, A.; Piscitelli, S. Electrical resistivity and TDR methods for soil moisture estimation in central Italy test-sites.Journal of Hydrology.2012, 454–455,101-112. https://doi.org/10.1016/j.jhydrol.2012.06.001.
Point 2: Are there any data for moisture content of corn straw compost reported in the literature? Some comparisons with the current experimental data should be included.
Response 2: Dear reviewer, We added data for the moisture content of the corn stover compost from the literature. And we compared our data with other moisture content testing methods.
(Line 345-351) McCartney et al. [37]used the far-infrared drying method to determine the moisture content samples of compost materials with a measurement time of 33 min, and the results were accurate to 0.1%. However, it suffers from the inability to achieve real-time measurements and the equipment is more expensive than the regular drying ovens. The time domain reflection method and frequency domain reflection method is indeed very accurate, with test error control within 3%[38], but have the disadvantage of being expensive.
(Line 356-358) This study proposes a method of real-time compost moisture content detection based on dielectric properties, which can detect within 10s compared with other moisture content detection methods.
- McCartney, D.; Tingley, J. Development of a rapid moisture content method for compost materials. Compost Science and Utilization.1998, 6: 14-25.
- Greco, R.; Guida A. Field measurements of topsoil moisture profiles by vertical TDR probes. Journal of Hydrology.2008,348 ( 3 /4 ),442-451. https://doi.org/10.1016/j.jhydrol.2007.10.013.
Point 3: English corrections are much needed.
Response 3: Thanks for your suggestion. We have carefully revised the manuscript according to the reviewers' comments, and also have re-scrutinized to improve the English with a language editing service.
Finally, thank you again for your careful reading of our paper. We hope to make progress under your guidance.
Author Response File: Author Response.docx
