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Peer-Review Record

Comprehensive Benefit Evaluation of Technological Models for Fertile Topsoil Restoration in Thin-Layer Black Soil Region: Evidence from Farmer Survey Data in the Southern Songnen Plain, China

Sustainability 2025, 17(20), 9290; https://doi.org/10.3390/su17209290
by Genhong Liang 1, Xiwu Shao 1,* and Kaida Gao 1,2
Reviewer 1:
Reviewer 2: Anonymous
Sustainability 2025, 17(20), 9290; https://doi.org/10.3390/su17209290
Submission received: 9 September 2025 / Revised: 13 October 2025 / Accepted: 17 October 2025 / Published: 19 October 2025

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors
  • Theoretical framework: The article justifies the use of the entropy weight–fuzzy comprehensive evaluation method. Why was this methodology chosen over others (e.g., AHP, DEA, or traditional multi-criteria analysis)? Are the limitations of the chosen method sufficiently discussed?

  • Sample: The study relies on 263 households. Is the statistical representativeness adequately demonstrated with respect to the whole farming population of the Songnen Plain?

  • Sampling bias: Could the most innovative or open-minded households have been overrepresented in the sample, thereby introducing bias in the results?

  • Data temporality: The data were collected in November 2024. Does a single year of data collection truly allow the authors to assess the long-term sustainability (ecological and social) of the soil restoration models?

  • Weight robustness: The article mentions robustness testing of weights by removing indicators (<5% variation). But what about a full sensitivity analysis, for example by randomly adjusting weightings?

  • Measurement of social benefits: Social indicators (satisfaction, income, training, etc.) partly rely on self-reported data. How can the authors ensure these results are not biased by social desirability effects?

  • Spatial heterogeneity: The Songnen Plain is vast. Do the results sufficiently account for intra-regional agro-climatic variability (microclimate, soil texture, straw availability)?

  • Adoption by farm size: The study mentions differences between small- and large-scale farmers. Were results stratified by farm size to derive more targeted recommendations?

  • Ecological assessment: Key indicators such as long-term carbon sequestration, soil biodiversity, or biological soil quality are absent. Why were these not included, given their importance in ecological evaluation?

  • International comparison: The study focuses only on China. Would a comparison with other chernozem regions (Ukraine, Russia, Canada) not enrich the discussion and strengthen the global relevance of the study?

  • No-tillage limitations: The manuscript highlights high pest and weed management costs. Were alternative agronomic solutions (e.g., crop rotations, cover crops) considered in the discussion?

  • Indirect tillage relevance: The low adoption of indirect tillage is attributed to technical complexity. Could this be more a question of institutional limitations (e.g., access to composting or biogas infrastructure)?

  • Public policy dimension: The paper recommends a differentiated promotion system. Have the economic impacts (subsidies, investments) of such a policy been evaluated to test its feasibility at scale?

  • Duration of adoption: Did the study account for how long farmers had been using each technology, since short- and long-term effects may differ significantly?

  • External validity: To what extent can these findings be generalized to other black soil regions in China or abroad, which may have different climatic and socio-economic conditions?

  • Strengthen methodological justification by comparing the chosen approach with alternative multi-criteria methods.

  • Conduct a more in-depth sensitivity analysis to test the robustness of results.

  • Expand ecological evaluation to include fundamental indicators (carbon, biodiversity, biological soil quality).

  • Stratify results by farm size to better inform policy recommendations.

  • Incorporate a temporal dimension (longitudinal or multi-year studies) to evaluate true sustainability.

  • Consider institutional and logistical barriers (straw collection, processing, redistribution).

  • Develop policy scenarios with quantified costs (subsidies, mechanization, training) to check economic feasibility.

  • Connect findings to the international literature for broader global relevance.

  • Explore technological synergies (e.g., strip tillage + organic fertilization) in future perspectives.

  • Clarify biases in subjective data by explaining how farmers’ perception bias was addressed.

  • Please cite this article : https://doi.org/10.1016/j.ecoleng.2006.09.021

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

Review on the manuscript with title: Comprehensive Benefit Evaluation of Technological Models for Fertile Topsoil Restoration in Thin-Layer Black Soil Region: Evidence from Farmer Survey Data in the Southern Songnen Plain, China I suggested a major revision with the following comments:

  1. The abstract section seems to be a list of the key points of each chapter in the entire text, rather than a coherent narrative. It is suggested that the abstract be rewritten, highlighting the research question, core methods, most crucial findings, and the most significant implications.
  2. The article does not clearly define what is meant by "comprehensive benefits" at the beginning. The interrelationships among economic, social and ecological benefits (whether they are simply parallel or involve trade-offs and synergies?) have not been thoroughly examined.
  3.  The article presents the scores of different models, but no statistical tests (such as analysis of variance or non-parametric tests) were conducted to determine whether these score differences are statistically significant. Are the differences in scores real, or could they be caused by sampling errors? Without a significance test, the persuasiveness of the conclusion is greatly reduced.
  4.  The evaluation results are likely to be confounded by the characteristics of the farmers themselves (such as age, educational level, and farm size). A large farmer may rate the deep plowing method highly not because the method is good, but because he has a stronger ability to bear costs. The article did not use a regression model to control for these variables.
  5.  In the social benefit dimension, "farmers' satisfaction" has the highest weight. However, the article does not delve deeper into "why farmers are most satisfied with strip farming"? Is it because the operation is more effortless? Because the yield increase is more stable? Or because the risks are lower?
  6.  The study area covers four counties, but it did not analyze whether different counties (which may have micro-topography, climate or soil differences) are more suitable for different technical models. The proposed "zone adaptation" suggestion lacks empirical spatial basis from this study and appears rather vague.
  7.  The article recommended various technical models, but did not at all discuss the financial investment, institutional capacity building and regulatory costs required for the promotion of these models. A comprehensive benefit assessment should include a rough assessment of the cost of the policy itself.
Comments on the Quality of English Language

The scientific content is strong, but the current language issues lessen its impact and professionalism. Addressing these points will significantly improve the readability, clarity, and overall quality of the paper.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

I recommend acceptance of the article. The authors have taken the comments into account and the manuscript has been improved. 

Reviewer 2 Report

Comments and Suggestions for Authors

My questions were all answered satisfactorily.

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