Modeling Foliar Infection Dynamics in Wheat Using a SEIR Framework: Effects of Seed Treatment and Foliar Fungicide Under Mediterranean Conditions
Round 1
Reviewer 1 Report
Comments and Suggestions for AuthorsIntroduction
L48-49. Although the introduction extensively cites relevant literature, some claims, such as the effects of climate change on pathogen virulence, could benefit from more recent references or meta-analyses to strengthen credibility.
L51. The introduction is rich in detail. Sections such as canopy architecture and climate change impacts could be condensed to maintain focus on the modeling objective. Highly specific physiological details should be moved to the discussion or methods section.
L66-75. To strengthen the justification for the study, the gap in published data on the interaction between pathogen biology, environmental variables, and management timing could be emphasized earlier and more explicitly.
L 84-87. The transition from context to objectives is somewhat implicit. Adding a clear and concise sentence summarizing the purpose of the study would improve readability.
L 88-90. Ensure consistent use of terms such as “epidemic growth rate,” “r(t),” and “SEIR compartments” when introducing them to avoid confusion for readers unfamiliar with epidemiological modeling.
Material and Methods
Several sentences are written in first person (“I believe that…”), which is inappropriate for a scientific manuscript.
2.1 and 2.2. Several methodological elements are difficult to follow because they are embedded in long explanatory paragraphs. The manuscript does not clearly distinguish which parameters were actually used in the simulations, which values were empirically derived versus assumed, how environmental data (temperature, humidity) were collected, processed, or interpolated, and how model results were validated against field observations.
The β₀ values (0.55 for Z. tritici and 0.38 for P. tritici-repentis) are discussed in relation to the literature, but the calibration or estimation procedure is not described.
Environmental scaling functions for temperature and humidity are introduced, but the source and processing of the daily T(t) and RH(t) data are not specified.
The fungicide decay function uses fixed constants (δ = 0.8, λ = 0.2), but no empirical justification or citation is provided.
A single comprehensive table summarizing all model parameters - along with their values, units, data sources, and calibration methods - would be extremely beneficial. This would allow for a quick understanding of the assumptions and input data underlying the simulations.
2.3. The initial conditions (S₀ = 0.94, E₀ = 0.05, I₀ = 0.01) are said to be based on field data, but no description of the field sampling method is provided. Also no explanation is given for why E₀ remains unchanged under seed treatment. The assumption that S₀ = 1 – E₀ – I₀ – R₀ is mathematically correct but biologically simplistic. A brief description of the field dataset and how these values were derived would strengthen the section.
2.6. The Euler method is appropriate for short time horizons, but the author should justify the choice of Δt = 1 day and discuss potential numerical instability. Author must indicate whether smaller time steps were tested and clarify whether compartment values were constrained to [0,1] programmatically. This would improve confidence in the numerical implementation.
2.7. The section mentions UAV data, NDVI/NDRE, and field trials, but does not specify the exact years of data collection, plot layout, cultivar, agronomic practices, disease scoring methods and weather station location and resolution. Since the model claims empirical grounding, these details are necessary.
Results
Table 1 and Table 2 present extensive numerical data, but the biological significance of these values is not always explained. Changes in β(t) or S(t) values are presented, but the text does not clarify how these changes translate into disease severity or observable canopy symptoms. This limits the practical relevance of the findings.
The results are presented without confidence intervals or any quantification of uncertainty. Given that SEIR models are very sensitive to parameter choice, the absence of uncertainty metrics limits the strength of the conclusions.
Although the manuscript states that the model is empirically grounded, the Results section does not clearly compare the simulated values with actual field measurements. Without validation plots or error metrics, it is difficult to assess how well the model reflects real epidemic dynamics.
Although Z. tritici and P. tritici repentis are modeled separately, the Results section often discusses them in parallel, without emphasizing their distinct epidemiological behaviors. This reduces the clarity of pathogen-specific information.
The section includes Figure 1 showing trends in r(t), but no plots of S(t), I(t), or cumulative infection are provided. Additional visualizations would help readers assess whether the model behaves realistically across compartments.
Author Response
Dear Reviewer
We appreciate your suggestion and we thank you for making constructive comments.
Introduction
L48-49. Although the introduction extensively cites relevant literature, some claims, such as the effects of climate change on pathogen virulence, could benefit from more recent references or meta-analyses to strengthen credibility.
We have added recent and authoritative references on climate‑driven changes in pathogen dynamics
Shaw, M.W., & Osborne, T.M. (2011). Geographic distribution of plant pathogens in response to climate change. Plant Pathology, 60, 31-43. DOI:10.1111/J.1365-3059.2010.02407.X
Garrett, K.A., Garrett, K.A., Nita, M., Wolf, E.D., Esker, P.D., Gomez-Montano, L., & Sparks, A.H. (2021). Plant pathogens as indicators of climate change. Climate Change. DOI:10.1016/B978-0-444-63524-2.00021-X
Kumar, D., & Mukhopadhyay, R. (2024). Climate change and plant pathogens: Understanding dynamics, risks and mitigation strategies. Plant Pathology. DOI:10.1111/ppa.14033
L51. The introduction is rich in detail. Sections such as canopy architecture and climate change impacts could be condensed to maintain focus on the modeling objective. Highly specific physiological details should be moved to the discussion or methods section.
We have streamlined the Introduction to maintain a clearer focus on the modeling objective. The section on canopy architecture has been moved to lines 650-664.
L66-75. To strengthen the justification for the study, the gap in published data on the interaction between pathogen biology, environmental variables, and management timing could be emphasized earlier and more explicitly.
Dear reviewer, we have added lines 88-91.
L 84-87. The transition from context to objectives is somewhat implicit. Adding a clear and concise sentence summarizing the purpose of the study would improve readability.
We have now added a clarifying paragraph in lines 91-94 of the revised manuscript.
L 88-90. Ensure consistent use of terms such as “epidemic growth rate,” “r(t),” and “SEIR compartments” when introducing them to avoid confusion for readers unfamiliar with epidemiological modeling.
We have added lines 101-104.
Material and Methods
Several sentences are written in first person (“I believe that…”), which is inappropriate for a scientific manuscript.
Changed to, We believe that the environment …
2.1 and 2.2. Several methodological elements are difficult to follow because they are embedded in long explanatory paragraphs. The manuscript does not clearly distinguish which parameters were actually used in the simulations, which values were empirically derived versus assumed, how environmental data (temperature, humidity) were collected, processed, or interpolated, and how model results were validated against field observations.
The β₀ values (0.55 for Z. tritici and 0.38 for P. tritici-repentis) are discussed in relation to the literature, but the calibration or estimation procedure is not described.
We added lines 164-202, including references.
Environmental scaling functions for temperature and humidity are introduced, but the source and processing of the daily T(t) and RH(t) data are not specified.
We have now added a clarifying paragraph in lines 260-263 of the revised manuscript.
The fungicide decay function uses fixed constants (δ = 0.8, λ = 0.2), but no empirical justification or citation is provided.
We have now added a clarifying paragraph in lines 251-254 of the revised manuscript.
2.3. The initial conditions (S₀ = 0.94, E₀ = 0.05, I₀ = 0.01) are said to be based on field data, but no description of the field sampling method is provided. Also no explanation is given for why E₀ remains unchanged under seed treatment. The assumption that S₀ = 1 – E₀ – I₀ – R₀ is mathematically correct but biologically simplistic. A brief description of the field dataset and how these values were derived would strengthen the section.
Dear reviewer,
Initial conditions for the SEIR compartments were derived from field observations collected during consecutive growing seasons (published work) in winter wheat fields in Thessaly, Greece. At BBCH 37, ten 1 m row segments were randomly selected per plot, and all leaves within each segment were visually assessed for the presence of latent lesions (E), visible sporulating lesions (I), and necrotic tissue (R). The proportion of healthy tissue (S) was calculated as the remaining leaf area. Across years and plots, mean values at BBCH 37 were S₀ = 0.94, E₀ = 0.05, and I₀ = 0.01, with negligible necrosis (R₀ ≈ 0). These values were used as the baseline initial conditions for both pathogens.
Under seed treatment with fluxapyroxad (Systiva®), I₀ was reduced to 0.01 based on field measured reductions of approximately 80% in early infection pressure. In contrast, E₀ was kept unchanged because seed applied SDHI fungicides primarily suppress initial infection success and early sporulation but do not eliminate latent, asymptomatic colonization already present at BBCH 37. This distinction reflects the biological difference between preventing new infections and clearing latent infections that have already occurred.
2.6. The Euler method is appropriate for short time horizons, but the author should justify the choice of Δt = 1 day and discuss potential numerical instability. Author must indicate whether smaller time steps were tested and clarify whether compartment values were constrained to [0,1] programmatically. This would improve confidence in the numerical implementation.
Dear reviewer,
To simulate the temporal evolution of the SEIR compartments, we employed the forward Euler method, a first order explicit numerical scheme suitable for short epidemiological time horizons. A daily time step (Δt = 1 day) was selected because the biological processes represented in the model—latent progression, infectiousness, and removal—operate on multi day scales.
2.7. The section mentions UAV data, NDVI/NDRE, and field trials, but does not specify the exact years of data collection, plot layout, cultivar, agronomic practices, disease scoring methods and weather station location and resolution. Since the model claims empirical grounding, these details are necessary.
Dear reviewer,
The primary study field (0.73–0.85 ha) has been monitored and has been used in previous published work on wheat foliar diseases and SDHI seed treatments.Disease progression data (2016–2018) were collected through standardized visual assessments during tillering and stem elongation, following the methodology described in Vagelas et al. (2022). Structured trials evaluated fluxapyroxad (Systiva®) seed treatment using a randomized complete block design with four replicates and commonly grown winter wheat cultivars.
Disease scoring followed a standard area diagram (SAD) approach, examining 8–10 plants at regular intervals per plot and estimating the percentage of leaf area with chlorosis, necrosis, or pycnidia. These assessments provided the empirical basis for deriving S₀, E₀, I₀, and R₀ at BBCH 37.UAV multispectral imaging (NDVI, NDRE) was conducted using Parrot Sequoia sensors at 30–45 m altitude, with orthomosaics processed in Pix4DMapper and QGIS. These data served as an independent validation layer for canopy vigor and spatial disease patterns under seed treatment.Daily temperature and relative humidity were obtained from the Hellenic National Meteorological Service (HNMS) station.
Together, these multi‑year field observations, UAV measurements, and meteorological data provided the empirical foundation for model calibration and validation under Mediterranean wheat‑growing conditions.
Results
Table 1 and Table 2 present extensive numerical data, but the biological significance of these values is not always explained. Changes in β(t) or S(t) values are presented, but the text does not clarify how these changes translate into disease severity or observable canopy symptoms. This limits the practical relevance of the findings.
The results are presented without confidence intervals or any quantification of uncertainty. Given that SEIR models are very sensitive to parameter choice, the absence of uncertainty metrics limits the strength of the conclusions.
Dear reviewer
the SEIR model produces four compartmental trajectories (S(t), E(t), I(t), R(t)), but we chose to present r(t) graphically because it provides a concise and biologically interpretable summary of epidemic rate. The epidemic growth rate integrates the effects of β(t), S(t), and γ(t) into a single metric that directly reflects whether the epidemic is expanding or being suppressed. For this reason, r(t) is the most informative visualization for comparing management scenarios.
Although the manuscript states that the model is empirically grounded, the Results section does not clearly compare the simulated values with actual field measurements. Without validation plots or error metrics, it is difficult to assess how well the model reflects real epidemic dynamics.
Although Z. tritici and P. tritici repentis are modeled separately, the Results section often discusses them in parallel, without emphasizing their distinct epidemiological behaviors. This reduces the clarity of pathogen-specific information.
We have now added a clarifying paragraph in lines 398-406 of the revised manuscript.
The section includes Figure 1 showing trends in r(t), but no plots of S(t), I(t), or cumulative infection are provided. Additional visualizations would help readers assess whether the model behaves realistically across compartments.
We have now added a clarifying paragraph in lines 707-715 of the revised manuscript.
Author Response File: 
Author Response.docx
Reviewer 2 Report
Comments and Suggestions for AuthorsSuggestions for improving the manuscript:
1) Figures 1 and 2 could be merged into only one figure;
2) Equations should be numbered;
3) Revise misleadings and typesettings;
4) Discussion could be improved in terms of the applicability of results;
5) More comparisons with scientific literature are expected;
6) Abstract: more key findings and quantitative results could be presented;
7) More recent references could be used to improve the discussion and comparisons, favoring the authors' insights.
Author Response
Dear Reviewer,
We thank you and we fully agree with your comments.
As suggested the section discussing canopy architecture and microclimate (previously located at lines 51–65 in the Introduction) has been removed from the Introduction and relocated to lines 679-693, where it is used to biologically interpret the model outputs
For highlighting the need to strengthen the biological interpretation of the model outputs. In response, we have added a concise explanatory sentence (lines 716-721) in the same section.
For highlighting the need for clearer justification of the baseline transmission rate β₀, we have added a dedicated subsection in the Materials & Methods (now Section 2.3: Calibration of Baseline Transmission Rate (β₀)), where we explicitly describe how β₀ was estimated.
to streamline the mathematical presentation. We have moved the detailed step‑by‑step numerical calculations and intermediate Euler updates (previously at lines 384–472 and 627–720) to the Supplementary Materials.
Further we added lines 88-91, 91-94, 101-104, 164-202, 260-263, 251-254, 398-406, 707-715 of the revised manuscript.
Further, we have added a short paragraph at lines 922–927, explicitly highlighting the practical implications of our findings for fungicide timing (BBCH 37) and the transferability of the SEIR framework to other foliar pathosystems.
For terminology and English writing
We changed, recovery period to latent period (line 33), population growth to epidemic development (line 100), population increase to epidemic increase (line 106). Lines 130-132 from the point where they infect their host, until symptoms are expressed, until they cause tissue to die, or the plant recovers to initial infection to symptom expression and eventual tissue necrosis. Line 137 recovered tissue changed to non-infectious. Line 150 recovery changed to non-infectious tissue. Line 284, density of viruses changed to infection rate. Line 284, percentage of area infested changed to the. Line 378, new leaf changed to new leaf tissue
English improvement
Line 13, estimating the change in r(t) and y(t) over the 10-day period changed to daily dynamics of r(t) and γ(t) over a 10‑day period
Lines 15-16, positive and transient during an early period of the epidemic with continuing suppression over time changed to positive only during the early phase of the epidemic, followed by progressive suppression
Line 27m food resources changed to food security crop
Lines 40-41, a decrease in temperature (and therefore in humidity) leads to a corresponding decline changed to lower temperatures (and thus lower humidity) reduce pathogen growth
Lines 695-697, the emergence of repeated cycles of lesion formation and spore dispersal is the most frequent form of developing foliar epidemics changed to Foliar epidemics typically develop through repeated cycles of lesion formation and spore dispersal
Line 84, The two-pronged approaches that constitute an Integrated changed to two main components of …
Reviewer 3 Report
Comments and Suggestions for AuthorsThis manuscript uses a compartmental, SEIR model to describe the efficacy of fungicides against two foliar diseases of wheat under two scenarios of disease control.
I was reading with care the manuscript three times before writing my opinion. I recognize the scientific value of this contribution but, at the same time, I think that the manuscript is too long, difficult to read, with an unclear and confusing structure; and this prejudices the usability of the content. There are many mathematical formula, and this makes the reader overloaded and distracted from the biological meaning of the research. I would suggest to make the manuscript easier to read, more focussed on biology rather than on mathematics. I agree that mathematic is highly relevant in this research, but I suggest that the Author uses the Supplementary Material for detailed description of the mathematical framework.
Concerning the SEIR model, I do not have concerns; the model framework is suitable for the purpose of the research. However, I have concerns about some model parametrisations, which seem too subjective and not well supported by evidence/data. For instance, the long explanation of studies on microscopy, transcriptomics, and effector biology related to Zt spread does not explain why a baseline transmission rate =0.55 was assigned.
In the Discussion and Conclusions section, I would suggest to focus on the relevant outcomes for wheat disease control and the transferability of the approach to other disease control situations.
I also suggest to play higher care in the English writing and on the use of plant pathology and botanical epidemiology terminology.
I then suggest to warmly ask the Author to reorganise the manuscript based on the previous considerations.
I suggest to play higher care in the English writing.
Author Response
Dear Reviewer,
We thank you and we fully agree with your comments.
As suggested the section discussing canopy architecture and microclimate (previously located at lines 51–65 in the Introduction) has been removed from the Introduction and relocated to lines 679-693, where it is used to biologically interpret the model outputs
For highlighting the need to strengthen the biological interpretation of the model outputs. In response, we have added a concise explanatory sentence (lines 716-721) in the same section.
For highlighting the need for clearer justification of the baseline transmission rate β₀, we have added a dedicated subsection in the Materials & Methods (now Section 2.3: Calibration of Baseline Transmission Rate (β₀)), where we explicitly describe how β₀ was estimated.
to streamline the mathematical presentation. We have moved the detailed step‑by‑step numerical calculations and intermediate Euler updates (previously at lines 384–472 and 627–720) to the Supplementary Materials.
Further we added lines 88-91, 91-94, 101-104, 164-202, 260-263, 251-254, 398-406, 707-715 of the revised manuscript.
Further, we have added a short paragraph at lines 922–927, explicitly highlighting the practical implications of our findings for fungicide timing (BBCH 37) and the transferability of the SEIR framework to other foliar pathosystems.
For terminology and English writing
We changed, recovery period to latent period (line 33), population growth to epidemic development (line 100), population increase to epidemic increase (line 106). Lines 130-132 from the point where they infect their host, until symptoms are expressed, until they cause tissue to die, or the plant recovers to initial infection to symptom expression and eventual tissue necrosis. Line 137 recovered tissue changed to non-infectious. Line 150 recovery changed to non-infectious tissue. Line 284, density of viruses changed to infection rate. Line 284, percentage of area infested changed to the. Line 378, new leaf changed to new leaf tissue
English improvement
Line 13, estimating the change in r(t) and y(t) over the 10-day period changed to daily dynamics of r(t) and γ(t) over a 10‑day period
Lines 15-16, positive and transient during an early period of the epidemic with continuing suppression over time changed to positive only during the early phase of the epidemic, followed by progressive suppression
Line 27m food resources changed to food security crop
Lines 40-41, a decrease in temperature (and therefore in humidity) leads to a corresponding decline changed to lower temperatures (and thus lower humidity) reduce pathogen growth
Lines 695-697, the emergence of repeated cycles of lesion formation and spore dispersal is the most frequent form of developing foliar epidemics changed to Foliar epidemics typically develop through repeated cycles of lesion formation and spore dispersal
Line 84, The two-pronged approaches that constitute an Integrated changed to two main components of …
Round 2
Reviewer 1 Report
Comments and Suggestions for AuthorsThe authors have addressed several of the previously requested revisions; however, additional changes are still necessary.
The abstract refers to the daily dynamics of r(t) and y(t) without explaining what these terms represent. These should be briefly defined or the wording simplified, and the repeated phrase “change in r(t) and y(t) over the 10‑day period” should be removed to avoid redundancy.
In the Introduction, several sentences contain grammatical errors or merged phrases (“cropfood resources”, “growtha decrease in temperature”), and these should be corrected for clarity.
The study objective is embedded within a long paragraph and is not clearly articulated; it should be rewritten as a concise and explicit statement.
In the Methods section, subsections labeled “2.45”, “2.56”, and “2.67” must be corrected to standard numbering. Additionally, the SEIR equations are presented twice and should appear only once in a single, well‑organized subsection.
Replacing “I believe” with “We believe” does not resolve the issue, as scientific manuscripts should avoid first‑person expressions of belief altogether, the sentence should be rewritten in an objective, evidence‑based form
In the Results section, the formula for r(t) is repeated multiple times (L361, L376, L401), and the accompanying narrative reiterates the same interpretation. The results should be presented once, clearly and succinctly, and supported by figures or tables where appropriate.
Table 1 also requires revision: the column headers “Theoretical / Empirical” are not explained, and units are missing.
Several references appear as numbers without proper formatting (e.g., “1,16,19”) and some citations are missing from the reference list.
The conclusion currently restates results, it should highlight key insights and practical implications
Author Response
The authors have addressed several of the previously requested revisions; however, additional changes are still necessary.
The abstract refers to the daily dynamics of r(t) and y(t) without explaining what these terms represent. These should be briefly defined or the wording simplified, and the repeated phrase “change in r(t) and y(t) over the 10‑day period” should be removed to avoid redundancy.
We thank you for this helpful comment. We have revised the Abstract accordingly. Specifically, we added the following clarification: “…focusing on the daily epidemic growth rate r(t) (net infection increase) and the removal rate y(t) (loss of infectious tissue).” (lines 13-14).
In the Introduction, several sentences contain grammatical errors or merged phrases (“cropfood resources”, “growtha decrease in temperature”), and these should be corrected for clarity.
We thank the reviewer for pointing out these issues. We have carefully revised the Introduction to correct all grammatical errors and merged phrases. Specifically, the phrases “cropfood resources” and “growtha decrease in temperature” have been corrected to “food security crop” and “lower temperatures (and thus lower humidity) reduce pathogen growth,” respectively.
The study objective is embedded within a long paragraph and is not clearly articulated; it should be rewritten as a concise and explicit statement.
We thank you for this valuable comment. We have revised the long paragraph “In order to address this situation, we used mathematical modelling to develop an SEIR model… ifferent management schemes [1, 2, 16, 18, 19].” with "The objective of this study was to develop an SEIR‑based modeling framework capable of quantifying early epidemic dynamics of Z. tritici and P. tritici‑repentis under different fungicide management scenarios."
In the Methods section, subsections labeled “2.45”, “2.56”, and “2.67” must be corrected to standard numbering. Additionally, the SEIR equations are presented twice and should appear only once in a single, well‑organized subsection.
We thank the reviewer for this important observation. We have corrected the subsection numbering throughout the Methods section to follow standard sequential formatting (2.4, 2.5, 2.6, etc.).. In addition, the SEIR equations, which previously appeared twice, have now been consolidated into a single subsection to improve readability and avoid redundancy.
Replacing “I believe” with “We believe” does not resolve the issue, as scientific manuscripts should avoid first‑person expressions of belief altogether, the sentence should be rewritten in an objective, evidence‑based form
Dear reviewer, we have revised lines 291–294 and 406-407 accordingly.
In the Results section, the formula for r(t) is repeated multiple times (L361, L376, L401), and the accompanying narrative reiterates the same interpretation. The results should be presented once, clearly and succinctly, and supported by figures or tables where appropriate.
Dear reviewer, we thank you for this helpful comment. The repeated instances of the r(t) formula in the Results section have been removed (L376, L401).
Table 1 also requires revision: the column headers “Theoretical / Empirical” are not explained, and units are missing.
Dear reviewer, Table 1 has been revised: the meaning of the “Theoretical” and “Empirical” columns is now clearly defined in the caption.
Several references appear as numbers without proper formatting (e.g., “1,16,19”) and some citations are missing from the reference list.
We thank the reviewer for this observation!! The citation formatting issues at lines 195 and 203 have been corrected.
The conclusion currently restates results, it should highlight key insights and practical implications
Dear reviewer, the requested revisions have been made, and the conclusion has been adjusted to highlight the key insights and practical implications as suggested.
Reviewer 3 Report
Comments and Suggestions for AuthorsMaybe, I was not clear enough in my comments to the original submission. I then reiterate my comments.
The text is too long, the structure is confused and Sections are not numbered in some part of the text.
The manuscript is not focused on the biological meaning of the research; there is too much mathematics, which can be moved to SM, as previously suggested. I would like to stress that there is no novelty in the mathematical structure used in this research, so that mathematics should not be the main part of the manuscript. The whole section 2.7 is not needed or can be moved to SMs; mentioning the Euler method for integration in the main text is enough. All the section with “calculation for Table x” should be moved to SMs, and summarised in the main text so that the reader can focus on what is biologically relevant.
Model parameterization for Ptr was not modified as for Zt; I mentioned the criticism for Zt as an example.
Overall, the text is really difficult to understand and the reader becomes lost. My request for English revision cannot be solved by changing only six short sentences. A full revision by a mother-tongue is needed.
I suggest to play higher care in the English writing.
Author Response
Maybe, I was not clear enough in my comments to the original submission. I then reiterate my comments.
The text is too long, the structure is confused and Sections are not numbered in some part of the text.
The manuscript is not focused on the biological meaning of the research; there is too much mathematics, which can be moved to SM, as previously suggested. I would like to stress that there is no novelty in the mathematical structure used in this research, so that mathematics should not be the main part of the manuscript. The whole section 2.7 is not needed or can be moved to SMs; mentioning the Euler method for integration in the main text is enough. All the section with “calculation for Table x” should be moved to SMs, and summarised in the main text so that the reader can focus on what is biologically relevant.
Model parameterization for Ptr was not modified as for Zt; I mentioned the criticism for Zt as an example.
Overall, the text is really difficult to understand and the reader becomes lost. My request for English revision cannot be solved by changing only six short sentences. A full revision by a mother-tongue is needed.
We thank the reviewer for the detailed and constructive comments.
Dear Reviewer, all points raised have been carefully addressed in the revised manuscript. The structure of the manuscript has been clarified, the mathematical content in the main text has been substantially reduced as suggested, and the model parameterization for P. tritici-repentis has been revised to ensure consistency with the reviewer’s earlier comments. The English language has also been thoroughly revised by a native speaker. We believe these revisions address all concerns raised and significantly improve the clarity, focus, and accessibility of the manuscript.
Round 3
Reviewer 1 Report
Comments and Suggestions for AuthorsThe values of some parameters, such as decay constants and susceptibility decay coefficients, appear to be adjusted to fit empirical results, rather than derived from independent data. A clearer distinction is needed between empirically measured parameters, parameters derived from the literature, and model-adjusted parameters.
The Results section includes long narrative explanations of each day’s r(t) and I(t) values. This level of detail is unnecessary and distracts from the broader epidemiological patterns. Figures and tables already convey the trends.
Figures lack axis units, and the legends could be more informative.
Table 1 include both theoretical and empirical S(t) values without clearly explaining why both are needed.
Author Response
Response to Reviewer
We thank the reviewer for the constructive and valuable comments.
In the revised manuscript, we clarified the origin of all SEIR parameters. Supplementary Table S1 now explicitly categorizes each parameter as empirically measured, literature‑derived, or model‑calibrated, and the text in Section 2.2 has been updated accordingly.
The Results section has been revised to remove day‑by‑day narrative descriptions of r(t) and I(t), focusing instead on broader epidemiological patterns that are already conveyed by the figures and tables.
All figures have been updated to include complete axis units (e.g., day⁻¹), and the legends have been expanded to clearly indicate pathogen identity and treatment scenario.
A brief explanatory sentence has been added to the Table 1 caption, clarifying that theoretical S(t) values represent model‑defined canopy susceptibility, whereas empirical S(t) values derive from field‑calibrated simulations.
