Phenotypic Variation in Water-Use Efficiency, Heat Tolerance, and Carbon Isotope Discrimination Across Canadian Spring Wheat Cultivars Under Climate Stress

Round 1

Reviewer 1 Report (New Reviewer)

Comments and Suggestions for Authors

The authors examined different measurable parameters to determine which one clearly explains genotypic variation: WUE. This aim is clearly significant for the breeding program. However, some poor experimental design decisions diminish the value of this manuscript. 

The experiment uses an inconsistent framework, with different grouping strategies in different parts of the results section, without providing any justification for these groupings. The abstract also doesn't mention any grouping, giving a false impression that the results came from one uniform experiment

Line 871-872: Only 2 biological replicates don't represent a well-designed experiment. Either the author should change the statistical method for comparison or acknowledge it as a limitation of the experiment. 

Line 191-192: The authors acknowledge that using too much fertiliser contributed to genetic diversity, yet continued comparing between groups. It is unclear whether excessive fertiliser use has caused any toxicity as well impacting the overall result.

The study lacks a control group. The author didn't use a well-watered plant grown at normal temperatures for comparison.  

The research gap is mentioned very vaguely in this manuscript (lines 112-115). It should be mentioned more clearly. Although the study's aim was stated, the link between the research gap and the aim should have been made explicit. 

Line 18-21: Mentions that the paper aims to investigate adaptive variation and more than a century of breeding progress, but no comparative year-wise analysis was done. Maybe this shouldn't be mentioned as an aim. 

In Figure 1, the names of breeding programs (x-axis) are too unclear to read. Having a colour code would help clarify the graph. 

 

Author Response

RESPONSES TO REVIEWER # 1 COMMENTS

The authors examined different measurable parameters to determine which one clearly explains genotypic variation: WUE. This aim is clearly significant for the breeding program. However, some poor experimental design decisions diminish the value of this manuscript.

Comment #1: The experiment uses an inconsistent framework, with different grouping strategies in different parts of the results section, without providing any justification for these groupings. The abstract also doesn't mention any grouping, giving a false impression that the results came from one uniform experiment

Responses to comment #1: The observed differences in plant responses may have been influenced, at least in part, by the fact that the entire panel of 198 cultivars was not evaluated simultaneously. Due to logistical and facility constraints, the cultivars were assessed in separate experimental runs, which may have introduced some variation in environmental conditions and contributed to differences in plant performance among cultivars. Although efforts were made to maintain consistent growth chamber conditions and experimental protocols across runs, the potential effect of run-to-run variation should be considered when interpreting the results.

 

Comment #2: Line 871-872: Only 2 biological replicates don't represent a well-designed experiment. Either the author should change the statistical method for comparison or acknowledge it as a limitation of the experiment. 

Responses to comment #2: We acknowledge that the use of two biological replicates is a limitation of this large-scale controlled-environment study involving 198 wheat cultivars. However, to improve measurement reliability, four technical chlorophyll fluorescence readings were collected per plant at each growth stage (eight observations per parameter across biological replicates), and 5–10 flag leaves per plant were bulked for δ¹³C analysis to obtain representative isotopic samples. While the limited biological replication may reduce statistical power to detect subtle genotype differences, the highly controlled growth-chamber conditions and extensive technical measurements enhanced the precision and robustness of the phenotypic assessments.

 

Comment #3: Line 191-192: The authors acknowledge that using too much fertilizer contributed to genetic diversity, yet continued comparing between groups. It is unclear whether excessive fertilizer use has caused any toxicity as well impacting the overall result.

Responses to comment #3: We would like to clarify that excessive fertilizer application was not intentionally imposed as an experimental treatment, nor were fertilizer rates applied at levels known to cause phytotoxicity. All cultivars within each experimental run were grown under the same standardized nutrient management regime to ensure adequate nutrient availability and minimize nutrient deficiency effects.

We acknowledge, however, that the 198 wheat cultivars could not be evaluated simultaneously in a single growth chamber experiment because of space and logistical constraints. Consequently, the cultivars were assessed in two separate growth chamber runs. Although identical protocols, environmental settings, soil media, irrigation schedules, and fertilizer applications were used in both runs, it is possible that minor, unavoidable differences between runs contributed to some of the observed variation and may have influenced the grouping patterns. This limitation has now been acknowledged in the revised manuscript.

Importantly, there was no visual evidence of fertilizer toxicity, such as chlorosis, necrosis, growth suppression, or abnormal plant development, during either growth chamber run. Therefore, we do not believe that fertilizer toxicity substantially affected the results. Nevertheless, we recognize that environmental variation between growth chamber runs, together with nutrient effects on trait expression, cannot be completely excluded and should be considered when interpreting the findings. This limitation is now discussed in the revised Discussion section.

 

Comment #4: The study lacks a control group. The author didn't use a well-watered plant grown at normal temperatures for comparison.  

Responses to comment #4: We respectfully clarify that the study did include a well-watered, non-stressed control treatment. Wheat cultivars were evaluated under both non-stress (BBCH 30–36, 37–40, 50–59, and 60–69) and combined heat–drought stress conditions imposed during the booting stage (BBCH 41–49). During the non-stress periods, plants were maintained under optimal growth chamber conditions (22/16°C day/night temperature and soil moisture at field capacity), which served as the control treatment for comparison with the stress treatment.

The objective of this study was to evaluate cultivar responses to a transient combined heat–drought episode imposed during a critical developmental stage and to assess physiological recovery following stress removal. However, the primary focus of the study was not to quantify the magnitude of stress tolerance relative to well-watered conditions during the stress period, but rather to characterize variation among cultivars in their physiological responses and recovery following exposure to a standardized transient stress treatment.

Comments #5: The research gap is mentioned very vaguely in this manuscript (lines 112-115). It should be mentioned more clearly. Although the study's aim was stated, the link between the research gap and the aim should have been made explicit.

Responses to comment #5: We agree that the research gap was not sufficiently articulated in the original manuscript. In the revised Introduction (Lines 107–135), we have clarified the specific knowledge gap by emphasizing the limited understanding of the extent of genetic variation in water-use efficiency, heat tolerance, and carbon isotope composition (δ¹³C) among Canadian spring wheat cultivars under combined heat and drought stress conditions. We further highlight the lack of large-scale physiological evaluations integrating WUE, chlorophyll fluorescence, biomass production, water use, and δ¹³C across a diverse panel of Canadian cultivars.

To strengthen the rationale of the study, we explicitly linked this research gap to the study objectives by stating that the evaluation of 198 cultivars was designed to address these limitations and identify physiological traits and germplasm with potential value for climate-resilient wheat breeding. These revisions provide a clearer connection between the identified knowledge gap and the overall aim of the study.

 

Comment # 6: Line 18-21: Mentions that the paper aims to investigate adaptive variation and more than a century of breeding progress, but no comparative year-wise analysis was done. Maybe this shouldn't be mentioned as an aim.

Responses to comment #6: We agree that the original wording may have implied a direct assessment of breeding progress over time. The primary objective of this study was to evaluate genetic variation and physiological diversity among Canadian spring wheat cultivars rather than to conduct a formal year-wise analysis of breeding progress. Although the cultivar panel spans registrations from 1905 to 2018, the study did not explicitly analyze temporal trends associated with cultivar release year. To avoid potential misinterpretation, we have revised the Introduction and objectives to remove references suggesting an assessment of breeding progress and instead emphasize the characterization of genetic diversity, water-use efficiency, δ¹³C, and heat tolerance across a broad and historically diverse collection of Canadian spring wheat cultivars.

The cultivar panel used in this study represents a broad spectrum of Canadian spring wheat germplasm registered between 1905 and 2018, providing an opportunity to capture a wide range of genetic and physiological diversity.

 

Comment #7: In Figure 1, the names of breeding programs (x-axis) are too unclear to read. Having a color code would help clarify the graph.

Responses to comment #7: To improve readability and facilitate interpretation, Figure 1 has been revised by increasing the font size of the breeding program labels on the x-axis and applying a distinct color scheme to differentiate breeding programs. These modifications enhance visual clarity and make the figure easier to interpret.

Reviewer 2 Report (New Reviewer)

Comments and Suggestions for Authors

Dear authors,

I have read this manuscript carefully. The topic is interesting and useful. The study uses 198 Canadian spring wheat cultivars, and the traits such as WUE, biomass, water use, δ¹³C and chlorophyll fluorescence are meaningful for wheat breeding under drought and heat stress.

However, I think the manuscript still needs major revision before publication.

First, the experimental design is not clear enough. The 198 cultivars were divided into two groups, but the terms “healthy” and “non-healthy” are confusing. If one group was affected by fertilizer problem, plant health or pest pressure, the comparison between cultivars may not be reliable. The authors should explain this clearly and consider this factor in the statistical analysis.

Second, the biological replication is too low. The manuscript only used two biological replicates. Four technical measurements cannot replace biological replicates. The authors should explain why this replication is enough, or make the conclusion more cautious.

Third, the drought and heat stress treatment should be described in more detail. For example, the soil water level, field capacity, pot weighing method, randomization and chamber conditions should be clearly given.

Fourth, the δ¹³C values need to be checked. In the abstract, the values are negative, but in tables and figures they appear as positive values. For wheat, δ¹³C is usually negative. The authors should clarify whether these data are δ¹³C, carbon isotope discrimination, or transformed values.

Fifth, some statistical results are not consistent. For example, the correlation between biomass and water use is reported as r = 0.88 in the abstract, but r = 0.94 in the results or figure. Please check all numbers carefully.

Sixth, the conclusion about Fv/Fm should be more cautious. The relationship between Fv/Fm and WUE or δ¹³C seems weak in some stages. So it may be better to say Fv/Fm can reflect PSII stress response, but not directly prove WUE improvement.

Seventh, the results section is a little too descriptive. Some parts repeat the figures and tables. The authors should highlight the most important cultivars, breeding programs, or useful physiological traits.

Eighth, some figures should be improved. The labels are small and difficult to read. Figure 5b caption seems to have an error. The heatmap is useful, but the genotype names are not clear. More explanation or supplementary table is needed.

Ninth, the term “genetic diversity” should be used carefully. Since most results are based on physiological and phenotypic traits, “phenotypic diversity” or “physiological diversity” may be more suitable if no molecular marker data were used.

The English is understandable, but some sentences are long and repeated. Some terms are also not very clear. I suggest the authors revise the language before resubmission.

Overall, this study has value, but the experimental design, data explanation, figures and conclusions need important improvement. Therefore, I recommend major revision.

Author Response

Responses to Reviewer #2 Comments

Comment # 1: The experimental design is not clear enough. The 198 cultivars were divided into two groups, but the terms “healthy” and “non-healthy” are confusing. If one group was affected by fertilizer problem, plant health or pest pressure, the comparison between cultivars may not be reliable. The authors should explain this clearly and consider this factor in the statistical analysis.

 

Responses to comment #1:  A limitation of this study is that the 198 wheat cultivars were evaluated in two separate growth-chamber runs because the available chamber space could not accommodate all cultivars simultaneously (Figure 1). The space constraints also limited the number of biological replicates that could be included. Although identical protocols, environmental conditions, stress treatments, and measurement procedures were applied in both runs, minor run-to-run variation is difficult to eliminate completely in controlled-environment experiments. Consequently, some observed differences among cultivar groups may partly reflect experimental run effects in addition to genetic variation. Therefore, comparisons among cultivars evaluated in different runs should be interpreted with caution. Future studies using larger controlled-environment facilities and increased biological replication would help further distinguish genetic effects from potential experimental run effects.

 

Figure 1. Growth-chamber setup used to evaluate 198 Canadian spring wheat cultivars under controlled drought and heat stress. Space limitations prevented simultaneous evaluation of all cultivars and additional replicates, requiring two experimental runs.

 

Comment #2: The biological replication is too low. The manuscript only used two biological replicates. Four technical measurements cannot replace biological replicates. The authors should explain why this replication is enough, or make the conclusion more cautious.

Responses to comment #2:  We agree that four technical measurements cannot replace biological replicates. The study was conducted under highly controlled growth-chamber conditions using a large panel of 198 spring wheat cultivars, which imposed substantial space limitations and restricted the number of biological replicates to two. To improve measurement precision, four technical chlorophyll fluorescence measurements were collected per plant at each growth stage, and all flag leaves from each plant were bulked for δ¹³C analysis; however, these measurements were not considered substitutes for biological replication.

 

Comment #3: The drought and heat stress treatment should be described in more detail. For example, the soil water level, field capacity, pot weighing method, randomization and chamber conditions should be clearly given.

Responses to comment #3:  We agree that a more detailed description of the drought and heat stress protocol would improve the reproducibility and clarity of the study. Accordingly, the Materials and Methods section has been substantially revised to provide additional information on growth chamber conditions, field capacity determination, soil water content management, pot-weighing procedures, randomization, and stress imposition.

Specifically, we now describe the environmental conditions maintained in the Conviron BioChamber, including photoperiod, light intensity, temperature, relative humidity, and air circulation. The determination of field capacity and calculation of soil water content are now clearly explained, including the gravimetric approach used to establish field-capacity weight and monitor soil moisture throughout the experiment. We also added details on the daily pot-weighing procedure used to maintain the target drought level (~10% SWC), the use of soil moisture probes to verify soil water status, and the inclusion of unplanted control pots to account for evaporative water loss.

In addition, the manuscript now clarifies that pots were arranged in a completely randomized design and periodically repositioned within the growth chamber to minimize positional effects. Further details have been provided regarding the timing, duration, and intensity of the combined drought and heat stress treatment, including maintenance of severe water deficit for 7 days and exposure to elevated temperature during the reproductive growth stages.

These additions have been incorporated into the revised Materials and Methods section to ensure that the experimental procedures can be fully reproduced and accurately interpreted by readers.

 

Comment #4: The δ¹³C values need to be checked. In the abstract, the values are negative, but in tables and figures they appear as positive values. For wheat, δ¹³C is usually negative. The authors should clarify whether these data are δ¹³C, carbon isotope discrimination, or transformed values.

Responses to comment #4: We confirm that the values reported in this study are δ¹³C (‰) relative to the VPDB standard, and therefore they are expected to be negative for C₃ species such as wheat. The negative δ¹³C values reported in the Abstract are correct. The apparent positive values shown in some tables and figures resulted from the inadvertent omission of the negative sign during data presentation. These have now been carefully checked and corrected throughout the manuscript to ensure consistency. The Methods section has also been revised to explicitly state that δ¹³C values are expressed in ‰ relative to the VPDB standard.

 

Comment #5: Some statistical results are not consistent. For example, the correlation between biomass and water use is reported as r = 0.88 in the abstract, but r = 0.94 in the results or figure. Please check all numbers carefully.

Responses to comment #5: We agree that the reported correlation values should be consistent throughout the manuscript. We have carefully rechecked the correlation analysis and corrected the inconsistency between the abstract, results, and figure. The correlation between biomass and water use has now been reported consistently throughout the revised manuscript. We also reviewed all other statistical values, including correlation coefficients, P-values, and figure annotations, to ensure consistency across the text, tables, and figures.

 

Comment #6: The conclusion about F_V/F_M should be more cautious. The relationship between F_V/F_M and WUE or δ¹³C seems weak in some stages. So it may be better to say F_V/F_M can reflect PSII stress response, but not directly prove WUE improvement.

Responses to comment #6: We agree that the interpretation of F_V/F_M should be more cautious. Although F_V/F_M was sensitive to drought and heat stress and effectively reflected changes in PSII photochemical efficiency across developmental stages, its relationships with WUE and δ¹³C were generally weak. Therefore, we have revised the manuscript to avoid implying a direct association between F_V/F_M and improved water-use efficiency. The conclusions now emphasize that F_V/F_M is a useful indicator of PSII stress response and photosynthetic impairment under combined drought and heat stress, but should not be considered a direct proxy for WUE or carbon isotope composition. This clarification has been incorporated into both the Results and Conclusion sections.

 

Comment #7: the results section is a little too descriptive. Some parts repeat the figures and tables. The authors should highlight the most important cultivars, breeding programs, or useful physiological traits.

Responses to comment #7: We agree that some portions of the Results section were overly descriptive and closely followed the presentation of figures and tables. In the revised manuscript, we have streamlined the Results section by reducing repetitive descriptions and placing greater emphasis on the key findings. Specifically, we now highlight cultivars and breeding programs that exhibited superior performance for WUE, biomass accumulation, water use, and stress tolerance traits, as well as the physiological parameters that showed the strongest associations with plant performance under combined drought and heat stress. Greater attention has also been given to interpreting the biological significance of the observed variation rather than simply restating numerical values presented in the figures and tables. These revisions improve the clarity of the Results section and better emphasize the most relevant findings for wheat improvement and climate-stress adaptation.

 

Comment #8: Some figures should be improved. The labels are small and difficult to read. Figure 5b caption seems to have an error. The heatmap is useful, but the genotype names are not clear. More explanation or supplementary table is needed.

Responses to comment #8:  We have carefully revised the figures and captions to improve clarity and readability. We also reviewed Figure 5b and corrected the caption.

Regarding the heatmap, we agree that displaying all genotype names within the figure is challenging because the analysis includes a large number of cultivars. The primary purpose of the heatmap was to illustrate overall clustering patterns and trait relationships among cultivars. To address this concern, we have expanded the description of the heatmap in the Results section and added a supplementary table listing all cultivar names together with their corresponding cluster assignments. This supplementary information allows readers to identify individual cultivars while maintaining the readability of the heatmap.

 

Comment #9: The term “genetic diversity” should be used carefully. Since most results are based on physiological and phenotypic traits, “phenotypic diversity” or “physiological diversity” may be more suitable if no molecular marker data were used.

Responses to comment #9: We agree that the term “genetic diversity” may imply direct assessment of genetic variation using molecular or genomic data, which was not the primary focus of this study. Because our analyses were based on physiological and phenotypic traits, we have revised the manuscript to replace “genetic diversity” with the more appropriate terms “phenotypic diversity” and/or “physiological diversity,” as applicable. These revisions more accurately reflect the nature of the data and the scope of the study.

 

Comment related to language: The English is understandable, but some sentences are long and repeated. Some terms are also not very clear. I suggest the authors revise the language before resubmission.

Responses to the comment related to language: Thank you for this constructive comment. We have carefully revised the manuscript to improve clarity, readability, and overall language quality. Several long and repetitive sentences have been shortened or restructured, redundant text has been removed, and ambiguous terminology has been clarified. We also conducted a thorough review of the manuscript to improve consistency in wording and presentation throughout the text. These revisions have enhanced the precision and readability of the manuscript.

 

Comment related overall study: Overall, this study has value, but the experimental design, data explanation, figures and conclusions need important improvement. Therefore, I recommend major revision.

Responses to the comment related to overall study: Thank you for your thorough evaluation and constructive feedback. We appreciate your recognition of the value of this study. We have carefully addressed all comments and substantially revised the manuscript to improve the experimental design description, data interpretation, figure quality and presentation, and the clarity and balance of the conclusions. Additional methodological details, limitations, and clarifications have been incorporated where appropriate, and the conclusions have been revised to better reflect the scope of the study. We believe these changes have significantly strengthened the manuscript and improved its scientific rigor, clarity, and overall quality.

Reviewer 3 Report (New Reviewer)

Comments and Suggestions for Authors

This manuscript investigates variation in whole-plant water-use efficiency (WUE), carbon isotope composition (δ¹³C), biomass accumulation, water use, and chlorophyll fluorescence traits among 198 Canadian spring wheat cultivars under combined drought and heat stress. However, several important issues related to experimental design, statistical interpretation, methodological rigor, and manuscript clarity must be addressed before the work can be considered for publication.

 

1. Lines126–130: The classification of cultivars into ‘health-associated’ and ‘non-health-associated’ groups is unclear and scientifically problematic; the authors should clearly define the criteria used for this classification and explain how differences in plant health status were controlled statistically to avoid confounding the interpretation of genotypic variation.
2. Lines 161–165：Check the data in Table 1, and please keep the main text consistent with the table data.
3. Lines 188–196: The statement that excessive fertilizer application may have affected plant health raises concerns regarding experimental consistency, and the authors should clarify the extent of damage, the number of affected plants, and whether compromised samples were excluded from the analyses.
4. Lines 215–218: The study divided the 198 cultivars into two experiments because of limited chamber space, but the manuscript does not provide sufficient evidence demonstrating that environmental conditions between the two experiments were fully comparable.
5. Line 220: ‘bio-mass’ is incorrectly segmented, change it to ‘biomass’.
6. Lines 402–404: The caption of Figure 5b incorrectly begins with ‘Figure 2,’and the figure labeling should be carefully checked throughout the manuscript for consistency and accuracy.
7. Lines 480–486: The authors state that the study integrates phylogenetic analysis; however, no clear phylogenetic methodology is presented in the Materials and Methods section, and this should be clarified or removed.At the same time, the sentence is too long, and the information is heavily clustered. It is recommended to split it into 2-3 sentences.
8. Lines 651–658: The manuscript overstates the breeding implications of the findings because the experiments were conducted only under controlled-environment conditions without field validation across multiple environments.
9. Lines 660–701: The discussion of chlorophyll fluorescence responses is excessively repetitive and should be condensed to focus more directly on the physiological mechanisms underlying stress tolerance.
10. Lines 754–756: The use of only two biological replicates for evaluating 198 cultivars under combined drought and heat stress appears insufficient for robust statistical inference, and the authors should justify the statistical power and experimental reliability of the dataset.
11. Lines 791–800: The calculation of whole-plant WUE should be discussed more critically because pot-based measurements may not accurately represent transpiration efficiency under field conditions, particularly when evaporation losses cannot be completely excluded.

Author Response

Responses to Reviewer #3 Comments

Comment #1: The classification of cultivars into ‘health-associated’ and ‘non-health-associated’ groups is unclear and scientifically problematic; the authors should clearly define the criteria used for this classification and explain how differences in plant health status were controlled statistically to avoid confounding the interpretation of genotypic variation.

Responses to comments #1: Thank you for this important comment. We agree that the terms “health-associated” and “non-health-associated” were inappropriate and have been replaced throughout the manuscript with neutral experimental group designations. The 198 cultivars were evaluated in two separate growth-chamber runs due to space limitations rather than differences in plant health. Although identical protocols and environmental conditions were used, plants in Experimental Run B generally appeared less vigorous than those in Run A. This likely reflects unavoidable run-to-run variation rather than a biological classification. The manuscript has also been revised to acknowledge that differences in vigor between runs may have contributed to some of the observed phenotypic variation. Accordingly, comparisons between cultivars from different runs should be interpreted with appropriate caution.

 

Comment #2: Lines 161–165：Check the data in Table 1, and please keep the main text consistent with the table data.

Responses to comment #2: Thank you for bringing this to our attention. We carefully reviewed Lines 161–165 and cross-checked all values against those presented in Table 1. The text has been revised where necessary to ensure complete consistency with the table data. All numerical values, ranges, means, and associated descriptions have now been verified and corrected to accurately reflect the results reported in Table 1. We have also conducted an additional review of the manuscript to ensure consistency between the main text, tables, and figures throughout the manuscript.

 

Comment #3: Lines 188–196: The statement that excessive fertilizer application may have affected plant health raises concerns regarding experimental consistency, and the authors should clarify the extent of damage, the number of affected plants, and whether compromised samples were excluded from the analyses.

Responses to comment #3: We agree that any potential effects of fertilizer application on plant performance should be clearly addressed. The statement in the previous version has been removed to avoid confusion. No severe fertilizer toxicity symptoms were observed, and no plants were excluded from the analyses due to fertilizer-related damage. All cultivars were grown under the same fertilization regime following standard greenhouse protocols, and measurements were collected from all experimental units. The observed differences among cultivar groups are therefore more likely attributable to genotypic variation and, potentially, minor differences between the two growth-chamber runs used to accommodate the large panel of 198 cultivars, rather than to fertilizer effects. The manuscript has been revised accordingly to clarify the experimental conditions and avoid unsupported interpretations regarding fertilizer impacts.

 

Comment #4: Lines 215–218: The study divided the 198 cultivars into two experiments because of limited chamber space, but the manuscript does not provide sufficient evidence demonstrating that environmental conditions between the two experiments were fully comparable.

Responses to comment #4: Both experiments were conducted in the same growth-chamber facility using identical environmental settings, growth conditions, stress treatments, and measurement protocols. However, because all 198 cultivars could not be accommodated simultaneously, two separate runs were required. We acknowledge that minor run-to-run variation cannot be completely excluded and have revised the manuscript to recognize this as a study limitation. Accordingly, comparisons among cultivars from different runs should be interpreted with appropriate caution.

 

Comment #5: Line 220: ‘bio-mass’ is incorrectly segmented, change it to ‘biomass’.

Responses to comment #5: Thank you for identifying this typographical error. The term “bio-mass” has been corrected to “biomass” throughout the manuscript to ensure consistent terminology and proper scientific usage. We also note that this segmentation may have resulted from document formatting or line-wrapping during manuscript preparation.

 

Comment #6: Lines 402–404: The caption of Figure 5b incorrectly begins with ‘Figure 2,’and the figure labeling should be carefully checked throughout the manuscript for consistency and accuracy.

Responses to comment #6: Thank you for identifying this error. The caption of Figure 5b has been corrected to remove the incorrect reference to “Figure 2.” We have also carefully reviewed all figure numbers, panel labels, captions, and corresponding citations throughout the manuscript to ensure consistency and accuracy. In addition, we recognize that some labeling discrepancies may have arisen during manuscript formatting, and these have been corrected in the revised version.

 

Comment #7: Lines 480–486: The authors state that the study integrates phylogenetic analysis; however, no clear phylogenetic methodology is presented in the Materials and Methods section, and this should be clarified or removed. At the same time, the sentence is too long, and the information is heavily clustered. It is recommended to split it into 2-3 sentences.

Responses to comment $7: We agree that the manuscript did not include a phylogenetic analysis, and the previous wording was inaccurate. The reference to phylogenetic analysis has therefore been removed and replaced with terminology that accurately reflects the analyses performed, namely phenotypic characterization, correlation analysis, principal component analysis, and hierarchical clustering. In addition, the overly long sentence in Lines 480–486 has been revised and divided into multiple shorter sentences to improve clarity and readability.

 

Comment $8: Lines 651–658: The manuscript overstates the breeding implications of the findings because the experiments were conducted only under controlled-environment conditions without field validation across multiple environments.

Responses to comment #8: We agree that the breeding implications should be interpreted cautiously because the study was conducted under controlled-environment conditions and did not include multi-environment field validation. The controlled conditions were intentionally used to minimize environmental variation and enable precise assessment of physiological responses to combined drought and heat stress. However, we acknowledge that genotype performance under controlled conditions may not fully reflect responses under diverse field environments. Accordingly, we have revised the Discussion and Conclusion sections to moderate the breeding implications and emphasize that the identified physiological traits and promising cultivars should be considered as preliminary candidates requiring validation in multi-location and multi-year field trials before their utility in breeding programs can be confirmed. This limitation has also been explicitly acknowledged in the revised manuscript.

 

Comment #9: Lines 660–701: The discussion of chlorophyll fluorescence responses is excessively repetitive and should be condensed to focus more directly on the physiological mechanisms underlying stress tolerance.

Responses to comment #9: Thank you for this helpful suggestion. We agree that portions of the chlorophyll fluorescence discussion were repetitive. The section has been revised and condensed to reduce repetition and focus more directly on the physiological significance of chlorophyll fluorescence as an indicator of PSII stability and photosynthetic responses to combined drought and heat stress. Greater emphasis is now placed on the underlying stress-tolerance mechanisms, while redundant descriptions of the results have been removed to improve clarity and readability.

 

Comment #10: Lines 754–756: The use of only two biological replicates for evaluating 198 cultivars under combined drought and heat stress appears insufficient for robust statistical inference, and the authors should justify the statistical power and experimental reliability of the dataset.

Responses to comment #10: We acknowledge that using two biological replicates is a limitation of the study and have stated this in the revised manuscript. However, the large number of cultivars evaluated (198), the controlled-environment conditions, and multiple technical measurements per plant helped reduce experimental variability and detect significant differences among cultivars. The study was intended as a broad physiological screening of a diverse wheat panel rather than a definitive assessment of cultivar performance. We have therefore presented the conclusions more cautiously and emphasized the need for validation with greater replication and multi-environment field testing.

 

Comment #11: Lines 791–800: The calculation of whole-plant WUE should be discussed more critically because pot-based measurements may not accurately represent transpiration efficiency under field conditions, particularly when evaporation losses cannot be completely excluded.

Responses to comment #11: We agree that whole-plant WUE estimates derived from pot experiments should be interpreted with caution, as they may not fully represent transpiration efficiency under field conditions. Although evaporation losses were minimized through the use of surface perlite and quantified using unplanted control pots, complete exclusion of evaporation may not be possible. We have revised the Discussion to acknowledge this limitation and clarify that the measured WUE reflects relative differences among cultivars under controlled conditions rather than absolute field-level water-use efficiency. We also emphasize that field validation is required to confirm the applicability of these findings under diverse environmental conditions.

 

Reviewer 4 Report (New Reviewer)

Comments and Suggestions for Authors

The manuscript entitled “Genetic Variation in Water-Use Efficiency, Heat Tolerance, and δ¹³C across Canadian Spring Wheat Cultivars under Climate Stress” entails changes in some phylogenetic traits according to genetic variation in Canadian spring wheat varieties under climatic stress. The manuscript's content was written in accordance with the journal's scope. Especially after revision, the scientific rigor and fluency of the English in the article are in a very good state. However, some minor shortcomings and errors have been identified.

TITLE

The title expresses the research paper well and fluently in a mechanical way.

Abstract

The research topic is strong; its language and flow are good, but the clarity of the hypothesis is unclear, and its mechanistic impact needs to be enhanced. To reach the Q1 level, it needs to be shorter, clearer, more mechanistic, and have more story-driven content.

Introduction

1. This section is actually well-written, but it needs to include a paragraph about environmental stressors, their interaction with plant growth, and their global impacts. In particular, paragraph 3 gives the impression that water use efficiency (WUE) data obtained through almost entirely different methods support the optimization study. I don't think that's necessary.
2. When writing the introduction to an article, the paragraphs should follow this order: Paragraph 1: Why is this topic important? Paragraph 2: What do we already know? Paragraph 3: What do we know specifically about your mechanism/system? Paragraph 4: What don't we know yet? (Knowledge gap) Paragraph 5: Hypothesis + Objective
3. Your introduction is almost entirely about the importance of your physiological and anatomical parameters in relation to WUE. It should be rewritten.
4. The article uses an excessive number of citations and references. Furthermore, these references are outdated; 70% are from 2010 or earlier.

 

M&M section

The materials and methods section is written in a nice, fluent, and understandable way.

The experimental design can be made more explicit and schematic.

Do the statistics need to be clarified?

1. Why were only two biological replicates used?
2. "Repeated measures ANOVA was used" is in here. What was the subject factor? The repeated factor? And the covariance structure?
3. Why was LSD used instead of Tukey's HSD or adjusted multiple comparisons?
4. Why were linear regression lines displayed when relationships were evaluated using a non-parametric correlation approach?
5. Why were analyses conducted using multiple software packages? So, SAS 9.1, SAS 9.1.0, R, GGally, and ggplot2 appear mixed up within the paragraph.
6. Were assumptions tested?
7. Why Spearman instead of Pearson?
8. What specific hypothesis was PCA intended to test?
9. How many cultivars were included in the PCA?
10. Only four variables were included in PCA. Was PCA necessary instead of simple correlation analysis?
11. In cluster analyses, were rows standardized, columns standardized, or the entire matrix standardized?
12. How were clusters identified?
13. Overall, the statistical explanations are very incomplete and confusing. They need to be rewritten.

Results

The results of the study are presented clearly and reflect well. The text fluently explained it using tables and figures. But there are still many spelling errors that need to be corrected.

Discussion

Although the results are clearly discussed, many unnecessary and overly assertive sentences, paragraphs, and repetitions go beyond the intended purpose. There are a full five pages of discussion. While it requires intensive research, it should be rewritten using simpler and shorter sentences, supported by references to other studies in the literature. Citations are not evenly distributed; 4-5 citations are made at the end of a long paragraph.

Conclusion

The conclusion is generally well-structured and highlights the importance of physiological screening for climate adaptation breeding. However, some statements regarding the narrowing of the genetic basis of drought and heat tolerance and the presence of adaptive alleles in historical varieties are not directly supported by the phenotypic data presented in this study. These conclusions should be softened or rephrased to avoid overinterpretation. Additionally, adding one or two significant quantitative findings to strengthen the main conclusions of the study would also benefit the conclusion section.

The parameters and values ​​are clearly defined in Figure 1. Converting this into a table would be more logical. Adding Tables 2 and 3 to the supplementary section would be beneficial. This would also help shorten the article somewhat.

Author Response

Responses to Reviewer #4 Comments

M&M section

Comment #1: Why were only two biological replicates used?

Responses to comment #1: Thank you for this important comment. The use of two biological replicates was primarily constrained by growth-chamber capacity and the large scale of the experiment, which involved evaluating 198 spring wheat cultivars under controlled drought and heat stress conditions. Accommodating all cultivars simultaneously required substantial space, and the available growth-chamber facilities limited the number of biological replicates that could be included while maintaining uniform environmental conditions and stress treatments across the entire experiment.

To improve measurement reliability, multiple technical measurements were collected for each plant, including repeated physiological assessments at different growth stages. Furthermore, significant genotypic differences were detected for the major traits evaluated, indicating that the experimental design was sufficient to identify phenotypic variation among cultivars. Nevertheless, we acknowledge that two biological replicates represent a limitation and may reduce the precision of genotype comparisons. This limitation has been explicitly acknowledged in the revised manuscript, and the conclusions have been presented more cautiously. Future studies with additional biological replicates and multi-environment validation will be necessary to further confirm the observed cultivar responses.

 

Comment #2: "Repeated measures ANOVA was used" is in here. What was the subject factor? The repeated factor? And the covariance structure?

Responses to comment #2: We agree that additional details regarding the repeated-measures analysis are necessary. In the repeated-measures ANOVA, cultivar was treated as the subject factor, while growth stage (BBCH stage) was treated as the repeated factor, since chlorophyll fluorescence (F_V/F_M) was measured repeatedly on the same plants across multiple developmental stages. The analysis accounted for the within-subject correlation among repeated observations collected from the same experimental unit over time. An autoregressive covariance structure was selected because measurements taken at adjacent growth stages were expected to be more highly correlated than those separated by longer time intervals. These details have now been added to the Statistical Analysis section to improve clarity and reproducibility of the methodology.

 

Comment #3: Why was LSD used instead of Tukey's HSD or adjusted multiple comparisons?

Responses to comment #3: Thank you for this important comment. Fisher’s Least Significant Difference (LSD) test was selected because the primary objective of the study was to identify and compare differences among a large number of wheat cultivars and to maximize the ability to detect potentially meaningful genotypic variation. The LSD procedure was applied only after a significant overall ANOVA F-test was obtained, which provides an initial control of Type I error. Given the exploratory nature of this large-scale germplasm screening study, LSD offered greater statistical power for detecting cultivar differences than more conservative procedures such as Tukey’s HSD. We acknowledge that Tukey’s HSD and other multiple-comparison adjustments provide stronger control of family-wise error rates, particularly when making all possible pairwise comparisons. This limitation has been acknowledged in the revised manuscript, and the interpretation of cultivar differences has been presented with appropriate caution. The rationale for selecting LSD has also been clarified in the Statistical Analysis section.

 

Comment #4: Why were linear regression lines displayed when relationships were evaluated using a non-parametric correlation approach?

Responses to comment #4: Thank you for this insightful comment. Spearman’s rank correlation was selected because several variables did not fully satisfy the assumptions of normality and linearity required for parametric correlation analyses. Therefore, the statistical significance and strength of trait associations were evaluated using Spearman’s correlation coefficients.

The regression lines shown in the scatterplots were included solely as visual aids to illustrate the overall direction and general trend of the relationships among traits and were not used for statistical inference. We agree that displaying linear regression lines alongside a non-parametric correlation analysis may create confusion regarding the analytical approach. To clarify this point, the figure captions and Methods section have been revised to explicitly state that the regression lines are presented for visualization purposes only and that all reported correlation coefficients and significance tests are based on Spearman’s rank correlation analysis. Alternatively, the regression lines can be removed from the figures if deemed more appropriate.

 

Comment #5: Why were analyses conducted using multiple software packages? So, SAS 9.1, SAS 9.1.0, R, GGally, and ggplot2 appear mixed up within the paragraph

Responses to comment #5: We agree that the description of the statistical software was not sufficiently clear in the original manuscript. Multiple software packages were used because different analyses and visualizations were performed using the programs best suited for each purpose. Specifically, SAS (Version 9.4, SAS Institute Inc., Cary, NC, USA) was used for data management, ANOVA, repeated-measures analysis, and mean comparisons, whereas R was used for data visualization and multivariate analyses, including correlation plots, PCA, heatmaps, and hierarchical clustering. The ggplot2 and GGally packages were used within the R environment to generate publication-quality figures and correlation matrices.

 

Comment #6: Were assumptions tested?

Responses to comment #6: Yes, the assumptions underlying the statistical analyses were evaluated prior to conducting the analyses. For ANOVA and repeated-measures ANOVA, residuals were examined for normality using normal probability plots and the Shapiro–Wilk test, while homogeneity of variance was assessed through residual-versus-predicted value plots and Levene’s test. For repeated-measures analyses, alternative covariance structures were evaluated, and the most appropriate structure was selected based on model fit criteria. When assumptions were not fully satisfied, data were carefully examined, and non-parametric methods, such as Spearman’s rank correlation, were used where appropriate.

A statement describing the assessment of statistical assumptions has now been added to the Statistical Analysis section to improve methodological transparency and reproducibility.

 

Comment #7: Why Spearman instead of Pearson?

Responses to comment #7: Spearman’s rank correlation was selected because several traits did not fully satisfy the assumptions required for Pearson’s correlation, particularly normality and linearity. In addition, some variables exhibited non-normal distributions and potential outliers, which can disproportionately influence Pearson’s correlation coefficients. Spearman’s correlation is a non-parametric method that evaluates the strength and direction of monotonic relationships based on ranked data and is therefore more robust to deviations from normality and the presence of outliers.

Given the large and diverse set of cultivars evaluated in this study, Spearman’s correlation was considered the more appropriate and conservative approach for assessing trait associations. This rationale has now been clarified in the Statistical Analysis section of the revised manuscript.

 

Comment #8: What specific hypothesis was PCA intended to test?

Responses to comment #8: PCA was not conducted to test a specific statistical hypothesis. Rather, it was used as an exploratory multivariate analysis to summarize the overall structure of the dataset, identify the major sources of phenotypic variation among cultivars, and examine relationships among the measured traits. Specifically, PCA was used to determine whether traits related to water-use efficiency (WUE_WP), carbon isotope composition (δ¹³C), biomass accumulation, and water use contributed to distinct patterns of cultivar variation and to identify traits that explained the greatest proportion of the observed phenotypic diversity.

The objective of PCA was therefore descriptive and exploratory rather than inferential. We have revised the manuscript to clarify that PCA was employed to reduce data dimensionality, visualize multivariate relationships among cultivars and traits, and identify the principal trait combinations contributing to phenotypic variation, rather than to formally test a predefined hypothesis.

 

Comment #9: How many cultivars were included in the PCA?

Responses to comment #9: The PCA included all 198 Canadian spring wheat cultivars evaluated in this study. The analysis was performed using cultivar mean values for the measured traits, including δ¹³C, whole-plant water-use efficiency (WUE_WP), biomass accumulation, and water use per plant. Prior to PCA, trait data were standardized (Z-score normalization) to ensure that variables measured on different scales contributed equally to the analysis.

We have clarified in the Materials and Methods section that all 198 cultivars were included in the PCA and that the analysis was based on standardized cultivar mean values to facilitate interpretation of multivariate trait relationships and patterns of phenotypic variation among genotypes.

 

Comment #10: Only four variables were included in PCA. Was PCA necessary instead of simple correlation analysis?

Responses to comment #10: We agree that correlation analysis is useful for quantifying pairwise relationships among traits and, accordingly, correlation analyses were performed and reported in the manuscript. However, the purpose of the PCA was different. PCA was used to provide a multivariate overview of the combined variation among the 198 cultivars, allowing simultaneous assessment of relationships among all four traits and visualization of cultivar distribution in a reduced-dimensional space.

Although only four variables were included, PCA helped identify the principal axes of phenotypic variation, determine the relative contribution of each trait to overall variation, and reveal patterns of cultivar grouping that cannot be fully captured by pairwise correlations alone. Thus, the PCA complemented the correlation analysis by providing an integrated multivariate interpretation of the dataset rather than serving as a substitute for correlation analysis.

To clarify this rationale, we have revised the manuscript to emphasize that PCA was included as an exploratory multivariate tool to visualize overall phenotypic relationships among cultivars and traits, while correlation analysis was used to quantify individual trait associations. We also acknowledge that, given the relatively small number of variables, the PCA should be interpreted primarily as a descriptive visualization of multivariate patterns rather than as a complex dimension-reduction exercise.

 

Comment #11: In cluster analyses, were rows standardized, columns standardized, or the entire matrix standardized?

Responses to comment #11: Prior to hierarchical clustering and heatmap generation, the trait data were standardized by column (trait-wise standardization) using Z-score normalization. Specifically, for each trait (δ¹³C, WUE_WP, biomass accumulation, and water use per plant), the mean was subtracted and the result divided by the corresponding standard deviation across all 198 cultivars. This procedure transformed each trait to a mean of 0 and a standard deviation of 1, ensuring that variables measured on different scales contributed equally to the distance calculations and clustering results.

The standardization was therefore applied independently to each column (trait) rather than to individual rows (cultivars) or the entire data matrix simultaneously. Hierarchical clustering was subsequently performed on the standardized data using Euclidean distance and Ward’s agglomerative clustering method.

 

Comment #12: How were clusters identified?

Responses to comment #12: Clusters were identified using hierarchical agglomerative clustering based on the standardized (Z-score normalized) trait data. Euclidean distance was used as the measure of dissimilarity among cultivars, and Ward’s minimum variance method was applied to merge cultivars into clusters while minimizing within-cluster variation.

The resulting dendrogram was examined to identify major groups and subgroups of cultivars based on similarities in δ¹³C, WUE_WP, biomass accumulation, and water use per plant. Cluster membership was determined from the hierarchical tree structure and was used primarily to visualize patterns of phenotypic similarity among cultivars rather than to define a fixed number of statistically distinct groups. Therefore, the clustering analysis was interpreted as an exploratory tool for identifying relative relationships and grouping patterns within the cultivar panel.To improve clarity, we have revised the manuscript to explicitly describe the clustering procedure, the distance metric and linkage method used, and the basis for identifying clusters from the dendrogram.

 

Comment #13: Overall, the statistical explanations are very incomplete and confusing. They need to be rewritten.

Responses to comment #13: Thank you for this constructive comment. We agree that the original Statistical Analysis section lacked sufficient detail and clarity regarding the analytical procedures. In response, the section has been substantially revised and reorganized to provide a clearer and more comprehensive description of all statistical methods used in the study.

The revised section now explicitly describes: (i) the experimental design and analytical framework; (ii) the ANOVA and repeated-measures ANOVA models, including subject and repeated factors and covariance structure; (iii) assessment of model assumptions, including normality and homogeneity of variance; (iv) the rationale for using Spearman’s rank correlation instead of Pearson’s correlation; (v) the purpose and implementation of PCA as an exploratory multivariate analysis; (vi) data standardization procedures used for PCA and hierarchical clustering; (vii) clustering methodology, including Euclidean distance and Ward’s linkage method; and (viii) the software packages and versions used for each analysis.

 

Results section

Comment #14: The results of the study are presented clearly and reflect well. The text fluently explained it using tables and figures. But there are still many spelling errors that need to be corrected.

Responses to comment #14: Thank you for your positive assessment of the presentation and interpretation of the results. We appreciate your recognition that the findings were clearly presented and effectively supported by the tables and figures. We also acknowledge the presence of spelling, grammatical, and typographical errors in the original manuscript. In response, the entire manuscript has been carefully reviewed and edited to correct spelling mistakes, improve grammar, eliminate inconsistencies, and enhance overall readability. Particular attention was given to technical terminology, figure and table references, formatting consistency, and sentence structure throughout the manuscript. We believe these revisions have substantially improved the quality, clarity, and professionalism of the manuscript.

 

Discussion section

Comment #15: -Although the results are clearly discussed, many unnecessary and overly assertive sentences, paragraphs, and repetitions go beyond the intended purpose. There are a full five pages of discussion. While it requires intensive research, it should be rewritten using simpler and shorter sentences, supported by references to other studies in the literature. Citations are not evenly distributed; 4-5 citations are made at the end of a long paragraph.

Responses to comment #15: Thank you for this thoughtful and constructive comment. We agree that portions of the original Discussion section were overly lengthy, repetitive, and occasionally more assertive than warranted by the scope of the study. In response, the Discussion has been thoroughly revised to improve clarity, conciseness, and scientific balance. Specifically, redundant statements and repetitive descriptions of the results have been removed, and several paragraphs have been condensed or reorganized to focus more directly on the key findings and their biological significance. Long and complex sentences have been rewritten into shorter, clearer statements to improve readability. We have also moderated interpretations and breeding implications where appropriate to ensure that conclusions remain fully supported by the data.

In addition, the discussion has been strengthened through more direct comparisons with relevant studies from the literature, allowing the findings to be placed in a broader scientific context. Citations have been redistributed throughout the Discussion to support specific statements and interpretations rather than being concentrated at the end of lengthy paragraphs. This approach improves both readability and attribution of supporting evidence. We believe these revisions have resulted in a more focused, balanced, and scientifically rigorous Discussion that better reflects the objectives and limitations of the study

 

Conclusion section

Comment #16: -The conclusion is generally well-structured and highlights the importance of physiological screening for climate adaptation breeding. However, some statements regarding the narrowing of the genetic basis of drought and heat tolerance and the presence of adaptive alleles in historical varieties are not directly supported by the phenotypic data presented in this study. These conclusions should be softened or rephrased to avoid overinterpretation. Additionally, adding one or two significant quantitative findings to strengthen the main conclusions of the study would also benefit the conclusion section. The parameters and values are clearly defined in Figure 1. Converting this into a table would be more logical. Adding Tables 2 and 3 to the supplementary section would be beneficial. This would also help shorten the article somewhat.

Responses to comment #16: We agree that some statements in the original Conclusion section extended beyond the direct evidence provided by the phenotypic data. In response, the conclusion has been revised to avoid overinterpretation, and statements regarding the narrowing of the genetic basis of drought and heat tolerance, as well as the presence of adaptive alleles in historical cultivars, have been either removed or rephrased more cautiously. The revised conclusions now focus on the observed phenotypic variation and physiological responses measured in this study rather than inferring underlying genetic mechanisms that were not directly assessed.

We also appreciate the suggestion regarding the presentation of supporting information. Figure 1 was retained because it provides a visual overview of the experimental design and workflow that is more easily interpreted graphically than in tabular form. However, to improve manuscript organization and reduce the length of the main text, Tables 2 and 3 have been moved to the Supplementary Materials, and appropriate references to these tables have been added within the manuscript.

 

Round 2

Reviewer 1 Report (New Reviewer)

Comments and Suggestions for Authors

The manuscript has been improved. 

Author Response

Responses to Reviewer #1 - Round 2

Reviewer #1 - Round 2 – Comment #1: The manuscript has been improved.

Responses to Reviewer # 1 – Round 2 - Comment #1: We appreciate your recognition that the manuscript has been improved. We have carefully addressed the reviewers’ comments through revisions to the methodology, statistical analyses, results interpretation, figures, tables, and overall clarity of the manuscript. We are grateful for the constructive feedback, which has helped strengthen the quality and presentation of our work.

 

Reviewer #1 - Round 2 - Comment #2: The English is fine and does not require any improvement

Responses to Reviewer # 1 – Round 2 - Comment #2: We appreciate your assessment that the English is clear and does not require further improvement.

 

Reviewer #1 – Round 2 - Comment #3: Is the research design appropriate? Can be improved

Responses to Reviewer #1 – Round 2 - Comment #3: We agree that the research design can be further improved. We have revised the manuscript to better describe the experimental design, statistical analyses, and study limitations. We have also clarified the interpretation of the results and acknowledged constraints associated with the experimental setup. These revisions strengthen the rigor and transparency of the study.

 

Reviewer #1 – Round 2 - Comment #4: Are the conclusions supported by the results? Can be improved

Responses to Reviewer #1 – Round 2 - Comment #4: Thank you for your comment. We agree that some conclusions could be stated more cautiously and aligned more closely with the results. We have revised the Discussion and Conclusions sections to ensure that all interpretations are fully supported by the data, avoid overstatement, and clearly distinguish between observed phenotypic responses and broader implications. These revisions provide a more balanced and evidence-based interpretation of the findings.

 

Reviewer #1 – Round 2 -Comment #5: Are all figures and tables clear and well-presented? Can be improved

Responses to Reviewer #1 – Round 2 - Comment #5 We agree that the presentation of some figures and tables could be improved. We have carefully revised all figures and tables to enhance clarity, readability, and consistency. Labels, legends, formatting, and captions have been refined where appropriate to improve the presentation and facilitate interpretation of the results.

Author Response File: Author Response.pdf

Reviewer 2 Report (New Reviewer)

Comments and Suggestions for Authors

1. The most important concern is the separation of cultivar effect and experiment/run effect. The 198 cultivars were divided into two different growth-chamber runs, with 99 cultivars in each run. However, the values of biomass and water use are quite different between Experiment 1 and Experiment 2. Therefore, it is difficult to know whether the observed differences are really caused by cultivar variation, or partly caused by the experimental run. The authors should clearly explain how the run effect was considered in the statistical analysis. If there were no common check cultivars in both runs, the combined analysis of all 198 cultivars should be interpreted more carefully.

2. Table 1 should be checked carefully again. Some statistical values seem not consistent with each other. For example, in Experiment 2, the biomass mean, range and CV do not match well with the reported standard deviation. This may be only a typing mistake, but it is important because many conclusions are based on this table. The authors need to re-check SD, CV, LSD and P values before the manuscript can be accepted.

3. Some conclusions are still too strong compared with the data. For example, the manuscript still uses expressions such as “genetic differentiation” and “limited adaptive capacity”, but the study mainly measured phenotypic and physiological traits, not genetic markers. Also, FV/FM may be useful as an indicator of photosynthetic stress response, but it should not be over-stated as a direct screening index for WUE or δ13C. The authors should make these statements more cautious and consistent with the actual results.

Author Response

Responses to Reviewer 2 Round 2

 

Reviewer 2 - Round 2 - Comments #1: The most important concern is the separation of cultivar effect and experiment/run effect. The 198 cultivars were divided into two different growth-chamber runs, with 99 cultivars in each run. However, the values of biomass and water use are quite different between Experiment 1 and Experiment 2. Therefore, it is difficult to know whether the observed differences are really caused by cultivar variation, or partly caused by the experimental run. The authors should clearly explain how the run effect was considered in the statistical analysis. If there were no common check cultivars in both runs, the combined analysis of all 198 cultivars should be interpreted more carefully.

 

Responses to Reviewer 2 - Round 2 - Comments #1: We agree that separating cultivar effects from potential experiment/run effects is critical when cultivars are evaluated in separate growth-chamber runs. The 198 cultivars could not be assessed simultaneously because of growth chamber space limitations and were therefore evaluated in two independent runs, each containing 99 cultivars. Both runs were conducted in the same Conviron BioChamber using identical protocols, environmental settings (temperature, humidity, photoperiod, and light intensity), soil media, irrigation procedures, fertilizer applications, and stress treatments. However, because the two runs did not include common check cultivars, it is not possible to fully separate cultivar effects from potential run effects.

Consequently, comparisons among cultivars are most reliable within each experimental run, whereas direct comparisons between cultivars evaluated in different runs should be interpreted with caution. Our primary objective was to characterize the overall range of phenotypic variation present within the Canadian spring wheat collection rather than to make definitive statistical comparisons among all 198 cultivars across runs. We acknowledge that part of the observed variation may reflect uncontrolled run-to-run differences despite the use of identical experimental protocols.

Previous studies have shown that plant growth chamber experiments are subject to both chamber effects and temporal (run) effects. Even when environmental conditions are programmed identically, subtle differences in light distribution, airflow, temperature gradients, humidity control, equipment performance, and environmental drift over time can influence plant growth and physiological responses, potentially resulting in variation among experimental runs (Potvin and Tardif, 1988; Porter et al., 2015).

References:

• Porter, A. S., Evans-Fitzgerald, C., McMahon, B. J., Ylioja, T., & Pappinen, A. (2015). How well do you know your growth chambers? Testing for chamber effect using plant traits. Plant Methods, 11, 44. https://doi.org/10.1186/s13007-015-0083-4.
• Potvin, C., & Tardif, S. (1988). Sources of variability and experimental designs in growth chambers. Functional Ecology, 2, 123–130.

This limitation has now been explicitly acknowledged in the Materials and Methods and Discussion sections. We have also clarified that conclusions regarding cultivar performance across the entire panel should be interpreted cautiously and that future studies should include common check cultivars and replicated chamber runs to enable more robust estimation and adjustment of run effects.

In conclusion, direct comparisons between the two growth chamber runs are limited by the absence of common check cultivars. Therefore, the findings should be interpreted primarily within runs, while acknowledging that differences between runs may reflect both cultivar variation and run effects.

 

 

 

Reviewer 2 - Round 2 - Comments #2:  Table 1 should be checked carefully again. Some statistical values seem not consistent with each other. For example, in Experiment 2, the biomass means, range and CV do not match well with the reported standard deviation. This may be only a typing mistake, but it is important because many conclusions are based on this table. The authors need to re-check SD, CV, LSD and P values before the manuscript can be accepted.

 

Responses to Reviewer 2 - Round 2 - Comments #2: We have re-examined all values reported in Table 1, including the mean, range, standard deviation (SD), coefficient of variation (CV), LSD, and P-values for both experiments. During this verification process. The values have now been corrected in the revised manuscript. We confirm that all summary statistics were recalculated directly from the original dataset, and the consistency among mean, range, SD, and CV has been verified. The corrected Table 1 has been updated accordingly. Importantly, these corrections do not alter the overall interpretation of the results or the conclusions of the study regarding phenotypic variation in biomass, water use, water-use efficiency, δ¹³C, and chlorophyll fluorescence traits. We appreciate the reviewer’s attention to detail, which helped improve the accuracy and clarity of the manuscript.

 

 

Reviewer 2 - Round 2 - Comments #3: Some conclusions are still too strong compared with the data. For example, the manuscript still uses expressions such as “genetic differentiation” and “limited adaptive capacity”, but the study mainly measured phenotypic and physiological traits, not genetic markers. Also, F_V/F_M may be useful as an indicator of photosynthetic stress response, but it should not be over-stated as a direct screening index for WUE or δ13C. The authors should make these statements more cautious and consistent with the actual results.

 

Responses to Reviewer 2 - Round 2 - Comments #3: We agree that some statements in the original manuscript were stronger than warranted by the data. Because this study evaluated phenotypic and physiological responses rather than molecular markers or genomic data, we have revised the terminology throughout the manuscript to avoid implying direct genetic characterization. Specifically, expressions such as “genetic differentiation” have been replaced with more appropriate terms such as “phenotypic variation” or “variation among cultivars,” and references to “limited adaptive capacity” have been revised to indicate “limited phenotypic variation in the measured traits under the experimental conditions.”

We also agree that F_V/F_M should not be presented as a direct screening index for water-use efficiency or δ¹³C. Our results showed only weak relationships between F_V/F_M and both WUE and δ¹³C, indicating that F_V/F_M is better interpreted as an indicator of photosynthetic stress response and PSII performance under combined heat and drought stress. Accordingly, we have revised the Abstract, Results, Discussion, and Conclusions to clarify that F_V/F_M may be useful for assessing physiological stress responses and identifying stress-sensitive or stress-tolerant cultivars, but should not be considered a direct surrogate for WUE or δ¹³C. These revisions ensure that the conclusions remain fully consistent with the scope of the data and the observed relationships among traits.

Reviewer 3 Report (New Reviewer)

Comments and Suggestions for Authors

1、Sections 2.1 and 2.2 are excessively long. The Results section should primarily present the major findings of the study rather than provide detailed explanations of every observed pattern. It is recommended that these sections be condensed and that some of the explanatory content be moved to the Discussion section.

2、The heading of the discussion section should be numbered

3、The conclusion section is too long.

Author Response

Responses to Reviewer #3 Round 2

 

Reviewer #3 – Round 2 – Comment #1: Sections 2.1 and 2.2 are excessively long. The Results section should primarily present the major findings of the study rather than provide detailed explanations of every observed pattern. It is recommended that these sections be condensed and that some of the explanatory content be moved to the Discussion section.

Responses to Reviewer #3 – Round 2 – Comment #1: We agree that the original versions of Sections 2.1 and 2.2 contained excessive detail and included explanatory interpretations that are more appropriate for the Discussion section. In response, we substantially condensed both sections to focus on the principal findings, including the key ranges, significant cultivar effects, trait distributions, diversity indices, and major correlation patterns. Detailed explanations and interpretation of the observed trends have been reduced in the Results section and, where appropriate, moved to the Discussion. These revisions improve the clarity and readability of the manuscript while ensuring that the Results section remains focused on the primary outcomes of the study.

 

 

Reviewer #3 – Round 2 – Comment #2: The heading of the discussion section should be numbered

Responses to Reviewer #3 – Round 2 – Comment #2: We have revised the manuscript to ensure that the Discussion section heading is numbered consistently with the journal formatting and the other main sections of the manuscript. The Discussion section is now appropriately numbered.

 

 

Reviewer #3 – Round 2 – Comment #3: The conclusion section is too long.

Responses to Reviewer #3 – Round 2 – Comment #3: We agree that the original Conclusion section was overly detailed and contained information that was more appropriate for the Discussion. In response, we have substantially shortened the Conclusion to focus on the main findings, key implications, and overall significance of the study.

 

 

Reviewer #3 – Round 2 – Comment #4: Is the research design appropriate? Must be improved.

Responses to Reviewer #3 – Round 2 – Comment # 4: We have clarified the experimental design, stress treatments, replication, and statistical analyses, and emphasized that cultivar comparisons are valid within growth-chamber runs because no common check cultivars were included across runs. These revisions improve the transparency and justification of the research design.

 

 

Reviewer #3 – Round 2 – Comment #5: Are the methods adequately described? Can be improved.

Responses to Reviewer #3 – Round 2 – Comment #5: We have revised the Methods section to provide additional details and clarifications regarding the experimental setup, stress treatments, measurements, replication, and statistical analyses. These revisions improve the clarity, transparency, and reproducibility of the study.

 

 

Reviewer #3 – Round 2 – Comment #6: Are the results clearly presented? Can be improved.

Responses to Reviewer #3 – Round 2 – Comment #6: We have revised the Results section to improve clarity and readability by condensing overly detailed descriptions, focusing on the main findings, and improving the presentation of figures, tables, and statistical results. These changes enhance the overall clarity and interpretation of the results.

 

 

Reviewer #3 – Round 2 – Comment #7: Are the conclusions supported by the results? Can be improved.

Responses to Reviewer #3 – Round 2 – Comment #7: We have revised the Discussion and Conclusion sections to ensure that all interpretations and conclusions are directly supported by the results. Statements that were overly strong have been moderated, and the conclusions now more accurately reflect the scope and limitations of the data.

 

 

Reviewer #3 – Round 2 – Comment #8: Are all figures and tables clear and well-presented? Cn be improved.

Responses to Reviewer #3 – Round 2 – Comment #8: We have carefully reviewed and revised Figure 6 and Table 1 to improve their clarity and presentation. Labels, captions, formatting, and figure quality were enhanced, and minor inconsistencies were corrected to ensure that the data are presented clearly and are easier to interpret.

 

Author Response File: Author Response.pdf

Reviewer 4 Report (New Reviewer)

Comments and Suggestions for Authors

The authors have made revisions based on the referees' suggestions. These revisions and responses have improved the quality of the article and addressed any shortcomings. But, it still uses an excessive number of citations and references. Furthermore, these references are outdated; 70% are from 2010 or earlier. I wish you success.

Author Response

Responses to Reviewer #4

 

Reviewer #4 – Round 2 – Comment #1: The authors have made revisions based on the referees' suggestions. These revisions and responses have improved the quality of the article and addressed any shortcomings. But it still uses an excessive number of citations and references. Furthermore, these references are outdated; 70% are from 2010 or earlier. I wish you success.

 

Responses to Reviewer #4 – Round 2 – Comment #1: We thank the reviewer for the positive assessment of the revised manuscript and for recognizing the improvements made in response to the reviewers' comments.

We acknowledge the concern regarding the number and age of the references. The literature cited includes several foundational studies that remain highly relevant to the topics of water-use efficiency, carbon isotope discrimination, and physiological responses of wheat to drought and heat stress. Nevertheless, we agree that incorporating more recent literature would strengthen the manuscript. We have therefore reviewed the reference list and added several recent studies where appropriate while retaining key seminal references that provide important scientific context and support for the interpretation of our findings.

 

 

Reviewer #4 – Round 2 – Comment #2: Are all figures and tables clear and well-presented? Can be improved

 

Responses to Reviewer #4 – Round 2 – Comment #2: We have carefully reviewed all figures and tables and made several improvements to enhance their clarity and presentation. Figure 6 labels, captions, axis titles, fonts, and formatting have been reviewed and standardized, and minor inconsistencies were corrected. Table 1 was also checked and revised for accuracy, readability, and consistency. We believe these changes have improved the overall presentation of the manuscript.

Author Response File: Author Response.pdf

Round 3

Reviewer 2 Report (New Reviewer)

Comments and Suggestions for Authors

The author has made the necessary changes; no further issues remain.

This manuscript is a resubmission of an earlier submission. The following is a list of the peer review reports and author responses from that submission.

 

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The objectives of the study are to (i) assess the genetic diversity and relationships among whole-plant water-use efficiency (WUEWP), δ¹³C, and related physiological traits associated with drought and heat tolerance in Canadian spring wheat cultivars registered between 1905 and 2018, and (ii) quantify the extent of genetic differentiation among these cultivars. The topic is relevant, and the study appears to offer novel and potentially useful insights for the readership of Plants. However, several issues should be addressed before the manuscript can be considered for publication. In addition, the manuscript contains some spelling and punctuation errors that require careful revision.

After this general assessment, please find my specific comments below:

1. The Abstract should not be divided into subsections (e.g., Background, Materials and Methods). A single, structured paragraph is more appropriate.
2. Key quantitative findings should be included in the Abstract to better reflect the significance of the results.
3. The Abstract shows a conceptual inconsistency: it reports “meaningful genotypic variation” while also concluding “low genetic diversity.” This point requires clarification, particularly regarding whether the observed variation is sufficient for breeding purposes or mainly driven by environmental effects.
4. The sequence of table citations is incorrect (e.g., starting from Table 3 in Line 115). Tables and figures should be cited in numerical order and carefully checked throughout the manuscript.
5. In Figure 1d, “Breedinbg” should be corrected to “Breeding.”
6. Figure 4 is difficult to interpret. The background of the chart is unclear, and it is not evident whether all parameters are presented on the same scale. This figure should be revised for clarity.
7. All equations should be numbered sequentially.
8. The stress conditions (e.g., severity, duration, and control conditions) are not clearly described and should be better defined in the Materials and Methods section.
9. It is unclear whether assumptions of normality and homogeneity were tested prior to analysis. This should be clarified in Section 4.6 (Data Analysis).

Comments on the Quality of English Language

revision needed especially for spelling or punctuation mistakes.

Author Response

Response to Reviewer 1
Comment 1: The Abstract should not be divided into subsections.
Response: We agree with the reviewer. The Abstract has been reformatted into a single, structured paragraph in accordance with the journal’s guidelines.

Comment 2: Key quantitative findings should be included in the Abstract.
Response: We have revised the Abstract to include key quantitative results (e.g., ranges of WUEWP, δ¹³C variation, and correlation coefficients), thereby improving the clarity and impact of the findings.

Comment 3: Conceptual inconsistency between “meaningful genotypic variation” and “low genetic diversity.”
Response: We appreciate this important observation. The apparent inconsistency has been clarified in the revised Abstract and Discussion. Specifically, we distinguish between: (i) detectable phenotypic/genotypic variation among cultivars under stress conditions, and (ii) the overall narrow genetic base of modern Canadian spring wheat.
We now explicitly state that while variation exists and allows identification of contrasting genotypes, the overall genetic diversity remains limited, which may constrain long-term breeding progress. This clarification resolves the inconsistency between “meaningful genotypic variation” and “low genetic diversity.”

Comment 4: Incorrect sequence of table citations.
Response: We have carefully reviewed and corrected all table and figure citations to ensure they appear in proper order throughout the manuscript.

Comment 5: Typographical error in Figure 1d (“Breedinbg”).
Response: The typographical error has been corrected to “Breeding” in the revised figure.

Comment 6: Figure 4 is difficult to interpret.
Response: We agree and have revised Figure 4 to improve clarity. Specifically, we have: (i) simplified the background, (ii) ensured consistent scaling or clearly indicated when different scales are used, and (iii) improved labeling and legend descriptions.
These changes enhance readability and interpretation of the figure.

Comment 7: Equations should be numbered sequentially.
Response: All equations have now been numbered sequentially and consistently referenced in the text.

Comment 8: Stress conditions are not clearly described.
Response: We agree and have expanded the Materials and Methods section to provide detailed descriptions of stress conditions, including severity (e.g., soil moisture at 10% field capacity), temperature regimes (day/night), duration of stress, and control conditions. This improves reproducibility and transparency.

Comment 9: Unclear whether assumptions of normality and homogeneity were tested.
Response: We thank the reviewer for this important point. Section 4.6 (Data Analysis) has been revised to explicitly state that assumptions of normality and homogeneity of variance were tested prior to analysis (e.g., Shapiro–Wilk and Levene’s tests), and appropriate transformations or non-parametric methods were applied where necessary.

Reviewer 2 Report

Comments and Suggestions for Authors

1. Lack of standardized descriptions for environmental control and stress intensity
   The abstract only mentions "water-deficient and high-temperature conditions" without providing specific parameters such as soil moisture content, temperature gradients, or stress duration. This lack of detail compromises the reproducibility of the results and hinders cross-study comparisons.

2. Unclear link between measured traits and final yield/quality
   Although physiological parameters such as chlorophyll fluorescence, leaf water potential, and photosynthetically active radiation were measured, final economic traits—such as grain yield, thousand-kernel weight, protein content, or processing quality—were not directly assessed. Consequently, it remains unclear whether the observed physiological responses translate into actual yield losses or quality changes.

3. Overly generalized conclusions and lack of clear improvement pathways
   The conclusion recommends introducing new germplasm and strengthening integrated phenotyping, but it does not specify which species or sources (e.g., wild relatives, ancient landraces, wheat from other arid regions) might provide beneficial alleles, nor does it recommend specific phenotyping technology combinations.

4. Limited depth of the study, leaning more toward describing phenomena rather than generating conclusions through experimentation
   The overall scope of the study is relatively superficial, focusing more on observational descriptions of patterns rather than deriving robust conclusions from well-designed experimental manipulations.

 

Author Response

Response to Reviewer 2

Comment 1: Lack of standardized descriptions for environmental control and stress intensity.
Response: We agree with the reviewer and have revised the Abstract and Materials and Methods sections to include precise descriptions of stress conditions. Specifically, we now report soil moisture levels (expressed as % field capacity), temperature regimes (day/night), and the duration and timing of stress imposition relative to developmental stages. These additions improve reproducibility and enable cross-study comparisons.

Comment 2: Unclear link between measured traits and final yield/quality.
Response: We acknowledge this limitation and have clarified the study objective in the Introduction, emphasizing that this work focuses on physiological screening rather than yield evaluation. The Discussion has been strengthened to better link measured traits (e.g., chlorophyll fluorescence, leaf water status) with yield performance based on established literature. Furthermore, we now explicitly state that the contrasting cultivars identified in this study have been selected for subsequent field evaluation, where agronomic traits such as grain yield, thousand-kernel weight, and grain quality will be assessed.
1. Quantitative yield impact:
Reductions in chlorophyll fluorescence parameters, particularly FV/FM, reflect impairment of photosystem II (PSII) and reduced photosynthetic efficiency; such declines are closely associated with decreased carbon assimilation and can contribute to substantial yield losses in wheat, which under combined heat and drought stress may reach 10–50% or even 50–60% under severe water limitation [5–8]
2. Mechanistic link to yield and quality:
A decline in FV/FM indicates photoinhibition and damage to PSII, leading to reduced electron transport and carbon fixation; this limits biomass accumulation and grain filling, ultimately reducing both yield and grain quality traits such as protein accumulation and kernel development [78,91]

Comment 3: Overly generalized conclusions and lack of clear improvement pathways.
Response: We appreciate this comment and have revised the Conclusion to provide more specific recommendations. The revised text now identifies potential germplasm sources, including wild relatives, landraces adapted to arid environments, and germplasm from heat- and drought-prone regions. In addition, we specify integrated phenotyping strategies combining physiological measurements with high-throughput tools such as chlorophyll fluorescence imaging, thermal imaging, and spectral reflectance.

Comment 4: Limited depth of the study, leaning toward descriptive observations.
Response: We respectfully clarify that the study was designed as a controlled-environment screening experiment to identify physiological variation among wheat cultivars under drought and heat stress. To address the reviewer’s concern, we have: (i) clarified the experimental design and stress imposition strategy (Materials and Methods), (ii) strengthened the Discussion to emphasize physiological mechanisms and cultivar contrasts rather than descriptive patterns, and (iii) explicitly framed the study as a first-stage screening step within a broader breeding pipeline. The selection of contrasting genotypes for field validation further demonstrates the applied significance of the study.

Reviewer 3 Report

Comments and Suggestions for Authors

This article is a large-scale study assessing the genetic diversity of Canadian spring wheat varieties for traits associated with drought and heat tolerance. The study addresses a pressing issue—climate change (increasing frequency of droughts and heat waves)—making its results important for breeding programs. The authors use a comprehensive methodological approach rather than focusing solely on a single parameter. A particularly valuable result is the confirmation of a weak relationship between water use efficiency (WUE) and carbon isotope discrimination (δ13C) under stress conditions.

The article contains all necessary sections. However, the study has several significant shortcomings that require correction and clarification prior to potential publication.

1. Error in the calculation of leaf water potential (Table 2)

The authors define the leaf water potential (LWP) parameter as LWP = FM/F0. This is either a serious typo or a fundamental methodological error, as leaf water potential is measured in pressure units (MPa or kPa) and cannot be a dimensionless ratio of fluorescence parameters. This seriously undermines the credibility of the section on plant water status. The authors need to correct the formula or provide a clear explanation of which parameter they actually measured.

2. The Impact of Aphid Infestation on Results (Section 2.2)

In Section 2.2, the authors indicate that some plants were infested with aphids, resulting in a bimodal distribution of biomass and water use. The decrease in biomass could have been caused by either the pest or water stress. The authors themselves acknowledge that the classification of varieties into groups was based on "plant health status," not solely on genetic traits. In this case, comparing the water use efficiency of "sick" and "healthy" plants is not entirely accurate.

3. Insufficient Number of Biological Replications

Using only two biological replicates (n=2) is the absolute minimum that formally allows for the calculation of variance, but is insufficient for statistically valid conclusions about genetic diversity and for correlation analysis (Pearson/Spearman). The accepted standard in plant physiology is 3 to 6 replicates.

Due to the small number of replicates: the influence of random factors (differences in plant health, substrate drying rate) increases significantly; estimates of the standard deviation and coefficient of variation become unstable; correlations at the r = 0.14–0.19 level (Fig. 3) may become statistically insignificant with a larger sample size.

Therefore, the obtained data should be considered preliminary (screening), requiring verification on an independent sample with a larger number of replicates. Authors should include a corresponding note in the Conclusions section, highlighting this limitation. 4. Insufficient information on technical replicates

The paper does not indicate how many analytical measurements (technical replicates) were performed for each biological replicate. Without this information, it is impossible to assess the contribution of measurement error to the overall variability of the traits.

The manuscript requires technical revision: Tables 1 and 2 should be moved from the "Results" section to the "Materials and Methods" section. Figures and tables should be placed immediately after their first mention in the text, rather than randomly.

The paper addresses a relevant topic and contains interesting preliminary data; however, it requires significant revision.

Author Response

Response to Reviewer 3

Comment 1: Error in the calculation of leaf water potential (Table 2).
Response: We thank the reviewer for identifying this issue. The expression “LWP = FM/F₀” was incorrect, as it represents a chlorophyll fluorescence parameter rather than leaf water potential. This has been corrected in the Materials and Methods section, where we clarified that plant water status was assessed indirectly using fluorescence parameters. The incorrect formula has been removed, terminologies have been revised throughout, and Table 2 has been updated accordingly.

Comment 2: Impact of aphid infestation on results (Section 2.2).
Response: We agree that aphid infestation is a confounding factor. We clarified its effect on plant grouping (Section 2.2), acknowledged it as a limitation in the Discussion, and moderated WUE comparisons. However, results indicate that plant health status did not significantly affect WUE. Selected cultivars will be re-evaluated under pest-free field conditions in future work.

Comment 3: Insufficient number of biological replications.
Response: We acknowledge that two replicates are a limitation. This was a preliminary screening study; the number of replications used in the study is now stated, limitations are noted, and selected genotypes will be validated under field conditions.

Comment 4: Insufficient information on technical replicates.
Response: We thank the reviewer for this important point. The number of technical replicates per biological replicate has now been explicitly added to the Materials and Methods section. We have also clarified how measurements were averaged prior to statistical analysis, allowing better assessment of measurement variability and error contribution.

Comment 5: Technical revision (placement of tables and figures).
Response: We have revised the manuscript structure in accordance with the reviewer’s suggestion. Specifically: (i) Tables 1 and 2 have been moved to the Materials and Methods section, and (ii) all figures and tables are now placed immediately after their first mention in the text.

These changes improve the clarity and readability of the manuscript.

Round 2

Reviewer 2 Report

Comments and Suggestions for Authors

Since the data are largely conceptual in nature, I am unable to assess the scientific validity of this paper, as it falls outside my area of expertise. Therefore, I cannot provide a proper evaluation and must reject the manuscript. 

Reviewer 3 Report

Comments and Suggestions for Authors

A re-review of the revised manuscript and the authors' responses to the previously raised comments merits a positive evaluation.
The authors have made significant revisions to the manuscript. Nearly all previously noted technical and methodological issues have been resolved, and the corresponding changes have been incorporated into the text.
I consider this revision satisfactory.
Based on the above, I believe the manuscript can be recommended for publication.