Local Climate and Cultivation Practice Shape Total Protein and Phenolic Content of Mulberry (Morus sp.) Leaves in Sub-Mediterranean and Sub-Pannonian Regions of Slovenia

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The manuscript 'Local Climate and Cultivation Practice Affect Biochemical Composition of Mulberry (Morus sp.) Leaves in Submediterranean and Subpannonian Regions of Slovenia', systematically analyzed the biochemical components (proteins, phenolic compounds) of mulberry leaves in the Mediterranean and Apannonia regions of Slovenia and their associations with climatic factors (temperature, precipitation, sunshine duration) and pruning practices. The research design is rigorous and the data is detailed, which is of great value for the protection of mulberry germplasm resources, the optimization of sericulture and the study of plant adaptability. The overall quality of the paper is relatively high, but some parts need further clarification and improvement.

3.2- Bioclimatic parameters are based solely on June–August 2023. Include historical climate data (e.g., 10-year averages) to ensure findings reflect long-term trends rather than seasonal anomalies. Please add appropriate data to the supplement

-It is not enough to only include the duration of sunlight. I think other parameters related to light need to be added, such as total solar radiation or photosynthetically active radiation, effective accumulative temperature (growing degree days)

-Line 591-592 The text states Slovenian Hills has "statistically significantly highest" caffeoylquinic acids, but Table 3 shows no significant difference vs. Drava Plain/Gorica Hills. Reconcile this discrepancy.

-Line 594-596 Figure 6A shows the content of coumaroylquinic acid derivatives, chlorogenic acid was not include

 

Author Response

 RESPONSE TO REVIEWER 1

Thank you very much for taking the time to review our manuscript and for your thoughtful and constructive comments. We have carefully considered all suggestions and have made the corresponding revisions, which are detailed in the point-by-point responses below.

To facilitate the review of the revised manuscript, we have prepared three versions of the file:

• Track_changes_marked_JELEN_Climate affects mulberry biochemical composition.docx: This version includes all modifications with tracked changes, and new or revised sections are additionally highlighted in yellow for clarity.
• Yellow_marked_JELEN_Climate affects mulberry biochemical composition_REVISED.docx: This version includes only yellow highlights to indicate newly added or modified content, without track changes.
• JELEN_Climate affects mulberry biochemical composition_REVISED.docx: This is the clean version of the revised manuscript, with all changes incorporated and no markings.

We have thoroughly reviewed the manuscript and improved the English by correcting grammatical errors and enhancing the overall clarity and flow of the text. WE have also improved Figures and tables.

 

COMMENT 1: 3.2- Bioclimatic parameters are based solely on June–August 2023. Include historical climate data (e.g., 10-year averages) to ensure findings reflect long-term trends rather than seasonal anomalies. Please add appropriate data to the supplement

RESPONSE 1: Thank you for this valuable suggestion. We have included historical long-term climate data. Specifically, we added 30-year averages (1970–2000) for mean, minimum, and maximum temperature, precipitation, and solar radiation from the WorldClim database (Flick and Hijmans, 2017). For growing degree days above 10 °C and growing season length, we used data from the Chelsa Climate database (1980–2010) (Karger at al., 2017 ). Unfortunately, these are the only datasets available that are directly comparable to our Agencija Republike Slovenije za Okolje (ARSO) data. In addition, we have added the parameters related to light, as suggested in Comment 3; however, ARSO does not provide corresponding data for the specific 2023 sampling season. The long-term averages are now presented in Table 2, and maps (A-L) illustrating the long-term trends are shown in Figure 4.

COMMENT 2: It is not enough to only include the duration of sunlight. I think other parameters related to light need to be added, such as total solar radiation or photosynthetically active radiation, effective accumulative temperature (growing degree days)

RESPONSE 2: We included solar insolation because this was the only light-related dataset that the Slovenian Environment Agency (operating under the Ministry of Environment, Climate, and Energy) could provide at a 30-second horizontal resolution for our sampling season (June–August 2023). However, following your valuable suggestion to include long-term trends, we incorporated three additional light-related parameters: solar radiation, growing degree days above 10 °C (°C), and growing season length. These parameters have been compared across mesoregions (Chapter 3.2) and further integratedin Principal Component Analysis combining biochemical data (Chapter 3.5) . We sincerely thank you for this suggestion, as it has made our article more complete and has significantly improved its overall quality.

COMMENT 3: Line 591-592 The text states Slovenian Hills has "statistically significantly highest" caffeoylquinic acids, but Table 3 shows no significant difference vs. Drava Plain/Gorica Hills. Reconcile this discrepancy.

RESPONSE 3: Thank you for noticing this mistake. We have corrected the dicrepancy and deleted the 'statistically significant,' so now it reads: The highest median content was found in white mulberries from Slovenian Hills, with a median value of 15.26 mg/g DW.

COMMENT 4: Line 594-596 Figure 6A shows the content of coumaroylquinic acid derivatives, chlorogenic acid was not include

RESPONSE 4: Thank you for pointing this out. The mistake is a consequence of observing individual caffeoylquinic acids derivatives within the total caffeoylquinic acid derivatives. We revised the sentence and corrected incorrect referencing of the graphs by revising the citations in the text in paragraph 5 of the chapter 3.3. Variations in protein and phenolic content in white mulberry leaves across Submediterranean and Subpannonian mesoregions in Slovenia.

We thank the reviewers for valuable comments that have significanlty improved the quality of the article.

Authors of the manuscript:

Špela Jelen, Martin Kozmos, Jan Senekovič, Danijel Ivajnšič, Silvia Cappellozza and Andreja Urbanek Krajnc

 

 

Reviewer 2 Report

Comments and Suggestions for Authors

This study aimed to identify differences of old local white (M. alba L.) and black mulberry (M. nigra L.) leaves by performing a chemotype analysis of monitored local varieties, and evaluate the influence of selected bioclimatic factors and pruning practices on the biochemical composition of leaves of white mulberry trees across Slovenian mesoregions. The research is interesting, and the findings highlight the influence of climate and pruning on mulberry biochemical diversity and adaptation. However, the manuscript is too long and with some data over-expressed, major revision is recommended, questions and suggestions are as follows.

1 the title of the paper should be reconsidered, biochemical composition is a very big range, only total protein content and phenolics were investigated in this study.

2 keywords could be reconsidered to delete some not key words.

3 line 390, Figure 2 should be Figure 3, and the figure pixel could be improved.

4 Have some of the data in Figure 6 and 7 been reflected in Table 3?

5 The discussion section is very long, the subtitles are suggested to be added for good structural hierarchy.

6 as discussed in line 817-829 about the nutritional profile of mulberry leaves, which are the important and main nutritional components? Why only protein content was considered?

7 Although Ward’s hierarchical clustering analysis using Euclidean distance was conducted, are the any correlations between total content and phenolic levels (total and individual phenolics) of mulberry leaves?

8 the conclusion section is suggested to be simplified.

Author Response

Response to Reviewer 2

Thank you very much for taking the time to review our manuscript and for your thoughtful and constructive comments. We have carefully considered all suggestions and have made the corresponding revisions, which are detailed in the point-by-point responses below.

To facilitate the review of the revised manuscript, we have prepared three versions of the file:

• Track_changes_marked_JELEN_Climate affects mulberry biochemical composition.docx: This version includes all modifications with tracked changes, and new or revised sections are additionally highlighted in yellow for clarity.
• Yellow_marked_JELEN_Climate affects mulberry biochemical composition_REVISED.docx: This version includes only yellow highlights to indicate newly added or modified content, without track changes.
• JELEN_Climate affects mulberry biochemical composition_REVISED.docx: This is the clean version of the revised manuscript, with all changes incorporated and no markings.

We have thoroughly reviewed the manuscript and improved the Figures and tables.

COMMENT 1: the title of the paper should be reconsidered, biochemical composition is a very big range, only total protein content and phenolics were investigated in this study.

RESPONE 1: We agree with your comment and have accordingly corrected the title to: Local Climate and Cultivation Practice Shape Total protein and Phenolics content of Mulberry (Morus sp.) Leaves in Submediterranean and Subpannonian Regions of Slovenia

COMMENT 2:  keywords could be reconsidered to delete some not key words.

RESPONSE 2: We have deleted inventory and combined air temperature, precipitation, total insolation and added three additional keyword: climatic effect, local genetic resources, metabolite screening

COMMENT 3: line 390, Figure 2 should be Figure 3, and the figure pixel could be improved.

RESPONE 3: Thank you for noticing our mistake, we have corrected the referencing from Figure 2 to Figure 3. And improved the pixel quality as .emf and then saving as .png.

COMMENT 4: Have some of the data in Figure 6 and 7 been reflected in Table 3

RESPONSE 4: We appreciate the reviewer’s comment and the opportunity to clarify this point. Figures 6 and 7 present the contents of individual phenolic compounds within coumaroylquinic acid derivatives, total caffeoylquinic acid derivatives, quercetin glycoside derivatives, and total kaempferol glycoside derivatives, together with their statistical comparison across mesoregions. In contrast, Table 3 summarizes these results by presenting the total amounts for each derivative group.We chose this approach because the manuscript to focus on the amount of phenolic derivatives groups. However, we considered it important to also illustrate the distribution of individual phenolic compounds within each derivative group, which is why these data are shown in Figures 6 and 7. To avoid duplication of result presentation, we revised Table 3 to Suppl. Table 4.

COMMENT 5: The discussion section is very long, the subtitles are suggested to be added for good structural hierarchy.

RESPONSE 5: Thank you, we agree with this comment. To improve readability and provide a clearer structure, we have added subheadings to the Discussion section.

COMMENT 6: as discussed in line 817-829 about the nutritional profile of mulberry leaves, which are the important and main nutritional components? Why only protein content was considered?

RESPONSE 6: We appreciate the reviewer’s insightful comment. In this study, we focused specifically on total protein content for several reasons. Protein is one of the principal nutritional components of mulberry leaves and plays a key role in their value as both functional food and animal feed. As discussed in lines 817–829, white mulberry leaves are particularly rich in protein (up to 31%), with a favorable amino acid composition that includes glutamic acid, aspartic acid, and leucine. Moreover, protein levels are known to respond strongly to environmental conditions such as pruning and climate, making them especially relevant for evaluating ecological and agronomic variability. While we did not include other nutritional indicators such as fiber, minerals, or vitamins due to the scope and methodological limitations of this study, we fully agree that these components are also important. Their inclusion would represent a valuable direction for future research aimed at providing a more comprehensive characterization of the nutritional potential of mulberry leaves.

COMMENT 7: Although Ward’s hierarchical clustering analysis using Euclidean distance was conducted, are the any correlations between total content and phenolic levels (total and individual phenolics) of mulberry leaves?

RESPONSE 7: To address your question regarding the correlation between total content and phenolic levels (total and individual phenolics) in mulberry leaves, we conducted a Spearman’s rank correlation analysis. The analysis revealed several noteworthy relationships. Total phenolic content (TPC), exhibited multiple significant positive correlations with individual phenolic compounds. Moderate positive correlations were observed with total caffeoylquinic acid derivatives (0.46**) and total coumaroylquinic acid derivatives (0.45**), indicating these two groups as key contributors to overall phenolic content. Among individual compounds, TPC was moderately correlated with chlorogenic acid (0.47**) and quercetin-3-glucoside (0.53**), as well as with quercetin malonyl hexoside (0.53**). Weaker, yet statistically significant, correlations were also found between TPC and 5-caffeoylquinic acid (0.27*), the cis-5-p-coumaroylquinic acid (0.28*), and p-coumaric acid hexoside (0.24*). Among quercetin- glycoside derivatives, positive associations were recorded with quercetin dirhamnosyl glycoside (0.24*), quercetin acetyl-rhamnosyl-hexoside (0.30**), and quercetin acetyl hexoside (0.36**). Regarding kaempferol derivatives, a moderate correlation was found with kaempferol acetyl-hexoside (0.55**), and a weaker one with kaempferol dirhamnosyl-hexoside (0.21*). We have now included a correlation table (see Supplementary Table 3) and referenced this analysis in the Results chapter 3.1, focused on corelations between total protein and phenolic contents and individual phenolics. This additional analysis complements the findings from the hierarchical clustering analysis.

COMMENT 8: the conclusion section is suggested to be simplified

RESPONSE 8: We have revised and simplified the Conclusion section to ensure it communicates the main findings more clearly and concisely. The updated version emphasizes key insights on the influence of climate and cultivation on mulberry leaf composition, while reducing analytic details to improve readability.

We thank the reviewers for valuable comments that have significanlty improved the quality of the article.

Authors of the manuscript:

Špela Jelen, Martin Kozmos, Jan Senekovič, Danijel Ivajnšič, Silvia Cappellozza and Andreja Urbanek Krajnc

 

Reviewer 3 Report

Comments and Suggestions for Authors

Please refer to the attachment.

Comments for author File: Comments.pdf

Author Response

RESPONSE TO REVIEWER 3

Thank you very much for taking the time to review our manuscript and for your thoughtful and constructive comments. We have carefully considered all suggestions and have made the corresponding revisions, which are detailed in the point-by-point responses below.

To facilitate the review of the revised manuscript, we have prepared three versions of the file:

• Track_changes_marked_JELEN_Climate affects mulberry biochemical composition.docx: This version includes all modifications with tracked changes, and new or revised sections are additionally highlighted in yellow for clarity.
• Yellow_marked_JELEN_Climate affects mulberry biochemical composition_REVISED.docx: This version includes only yellow highlights to indicate newly added or modified content, without track changes.
• JELEN_Climate affects mulberry biochemical composition_REVISED.docx: This is the clean version of the revised manuscript, with all changes incorporated and no markings.

 

Abstract

COMMENT 1: The abstract has a clear structure, logical coherence, prominent key findings, and provides supporting quantitative data.

RESPONSE 1: We appreciate the reviewer’s positive evaluation of the abstract.

COMMENT 2: The background sentence is slightly broad: Although the first sentence's description of the wide range of uses and ecological functions of mulberry trees is correct, it is not closely related to the title and specific focus of the research. It can be considered more refined or focused on the biochemical characteristics of leaves and their response to the environment and management.

RESPONSE 2: We thank the reviewer for this constructive suggestion. We revised the opening of the abstract to place more emphasis on the biochemical characteristics of mulberry leaves and their responsiveness to environmental conditions and management, ensuring closer alignment with the title and research focus.

Introduction

COMMENT 3:  The taxonomic details of the genus Morus can be simplified, which is weakly related to the main line that "biochemical components are influenced by climate/cultivation".

RESPONSE 3: In accordance with the comment, we simplified the taxonomic and morphologic details of the genus Morus and deleted text related to sexual expression and reproductive structures that are only weakly related to the main focus of the article. However, we retained a brief description of the morphological characteristics of the leaves of white and black mulberry, as the leaves of these twospecies are the main focus of our study.

COMMENT 4: The definition of "chemical typing" and its significance in mulberry research were not explained in advance.

RESPONSE 4: We added a clear definition of chemotype (chemical variety) and their significance in mulberry research into the Introduction section. This provides readers with a better understanding of why chemical typing is relevant for our study.

COMMENT 5: It is necessary to supplement literature support on the potential biochemical impact mechanisms of pruning measures, such as how pruning alters protein/phenolic synthesis.

RESPONSE 5: We thank the reviewer for this valuable suggestion. In accordance with the comment, we supplemented the Introduction with additional literature support on the biochemical impact mechanisms of pruning. Specifically, we briefly explain how pruning acts as an abiotic stress that upregulates pathways related to protein synthesis (Arkorful et al., 2020; Zhang et al., 2023; Torrent et al., 2018), while downregulating phenolic and flavonoid biosynthesis through the phenylpropanoid pathway (Zhang et al., 2023; Liu et al., 2024). Importantly, we also note that similar effects have been reported in mulberry itself, where Šelih et al. 2020 observed increased protein levels in pruned mulberry trees and decreased phenolic content in unpruned trees. This addition provides a clearer biological rationale for including pruning as one of the factors assessed in our study.

Materials and Methods

COMMENT 6: Pruning measures only record "frequency" without defining specific criteria such as pruning intensity and cycle, and do not explain how to convert them into statistical variables.

RESPONSE 6: We added more detailed description of pruning and conversion into statistical variable in chapter 2.1.

We classified the sampled mulberry trees into three categories according to pruning frequency and type: (1) unpruned trees, (2) frequently pruned trees, and (3) yearly pruned trees. Frequently pruned trees (2) included those pruned at least once within the last three years for crown maintenance and reduction. Yearly pruned trees (3) were subjected to traditional pollarding, in which all branches are cut back to a framework to promote a dense crown of new shoots. For statistical analysis, pruning categories were treated as categorical variables.

 

COMMENT 7:The sampling time window was selected from June to August, but it was not explained how this time period reflects the maximum impact of climate on biochemical components.

RESPONSE 7: Thank you for this observation. Samplings were conducted on clear days, predominantly between 10:00 and 14:00, in order to minimize the influence of diurnal fluctuations in leaf metabolism and water status. The sampling period—mid-June to mid-August—was deliberately chosen because, at this stage, mulberry leaves are fully developed and physiologically mature. This ensures that the collected material represents a stable metabolic state, unaffected by the rapid developmental changes that occur earlier in the season. By standardising the sampling window, environmental conditions, and time of day, we aimed to reduce variability linked to phenological stage, microclimatic fluctuations, and circadian rhythms. Such consistency provides reliable and comparable biochemical profiles across sites and genotypes, reflecting peak photosynthetic and metabolic activity of mulberry leaves. We have clarified the standardisation of the sampling procedure in the revised Materials and Methods section, in chapter 2.1.

 

COMMENT 8: It is necessary to supplement the source of trees, and the regional sample size is imbalanced. Although statistical correction is mentioned, it is not stated whether the impact of small samples on regional comparison conclusions has been evaluated.

RESPONSE 8: The mulberry trees used in our study were sampled from local genetic pool mainlypropagated by seeds in the past. We focused on trees with a circumference greater than 250 cm, which were planted during the sericultural era prior to the Second World War. We have detailed this information in Chapter 2.2, below Figure 1. In Supplementary Table 1, we added a column “Accessibility,” which provides more detailed descriptions of the locations from which leaf samples were collected. We acknowledge that the regional sample sizes are not balanced, reflecting historical cultivation patterns in relation to traditional land use, sericultural activity, topography, and favorable environmental conditions.  Additionally, logistical limitations—including land ownership, site accessibility, and fieldwork feasibility—further contributed to uneven sampling. In regions with a higher tree density, targeted sampling was conducted to capture broader environmental and genetic variability. Although this resulted in an unbalanced dataset, appropriate statistical methods [e.g., standardization, non-parametric tests using the median and median absolute deviation (MAD), and principal component analysis (PCA)] were applied to account for these differences and enable robust comparisons across environmental gradients.

In addition to emphasize this, we highlighted the two regions with low number of mulberries and added a small sample size superscript. To minimize the effect of unequal sample sizes, we applied nonparametric statistical tests and appropriate corrections, which are robust to sample size imbalances. While we recognize that limited sample sizes in some regions may restrict the generalizability of the results, the consistency across statistical approaches gives us confidence that the regional comparisons remain valid. We have added clarifications of tree sources and sample size limitations in the revised manuscript.

COMMENT 9: The quantification of phenols requires an explanation of the detection limit and fragment matching threshold. The TCA precipitation method may co precipitate phenolic substances. Please describe how to eliminate interference.

RESPONSE 9: We appreciate this valuable comment. The limit of detection (LOD) and limit of quantification (LOQ) were determined according to signal-to-noise ratios of 3:1 and 10:1, respectively. We added this information in chapter 2.6. For p-coumaroylquinic acid derivatives, the LOD was 0.0005 mg p-coumaric acid equivalents/g DW. The LOQ values were 0.00053 mg/g DW for p-coumaric acid hexoside₁, 0.00051 mg/g DW for trans-5-p-coumaroylquinic acid, 0.0027 mg/g DW for cis-5-p-coumaroylquinic acid, and 0.00066 mg/g DW for 3-p-coumaroylquinic acid. For quercetin glycoside derivatives, the LOD was 0.0005 mg quercetin equivalents/g DW, with LOQ values of 0.0008 mg/g DW for kaempferol rhamnosyl-hexoside and 0.0024 mg/g DW for kaempferol acetyl-rhamnosyl-hexoside. For kaempferol derivatives, the LOD was 0.0005 mg kaempferol equivalents/g DW, with LOQ values of 0.0007 mg/g DW for kaempferol rhamnosyl-hexoside and 0.0014 mg/g DW for kaempferol acetyl-rhamnosyl-hexoside. Table 1was revised by adding relative abundance of each ion in a fragment. Compound identification was performed by comparison with previously established MS fragmentation profiles as shown in Table 1 based on alignment of UV spectrum, retention time and MS fragmentation. The accuracy of assigning chromatographic peaks, their identification and quantification was verified based on twenty diagnostic sample profiles.

Regerding the TCA precipitation we fully agree that both the Bradford and the Lowry methods are prone to interferences from phenolic compounds and ascorbic acid, and that calibration with BSA standards may not represent the absolute protein content of plant extracts. In the revised version of the manuscript in chapter 2.3 we have clarified that proteins were precipitated with TCA and subjected to repeated washing steps in order to remove interfering compounds, following the procedure described by Kumar et al. [24] and in agreement with the approach presented in reference [46]. Specifically, we emphasized that the washing step eliminates free amino acids, phenolic compounds (including kaempferol derivatives), and ascorbic acid. Additionally, to further improve the reliability of the assay, we performed the incubation of the protein samples with Lowry reagent in the dark to prevent photosensitive degradation of the reagents, and absorbance measurements were carried out within 10 minutes after the completion of the incubation. These precautions ensured more accurate and reproducible results. We believe that these clarifications improve the methodological transparency and address the reviewer’s concerns.

COMMENT 10: Only using climate data from a single year in 2023, without considering the cumulative effect of interannual climate fluctuations on the biochemical composition of perennial trees, it necessary to explain how to integrate multiple indicators such as "average/minimum/maximum temperature" and whether lag effects are considered.

RESPONSE 10: Thank you for this valuable comment. We agree that the biochemical composition of perennial trees may be influenced by cumulative climatic effects and not solely by conditions during the 2023 sampling year. To address this, we have now included historical long-term climate data in our analysis. Specifically, we added 30-year averages (1970–2000) for mean, minimum, and maximum air temperature, precipitation, and solar radiation from the WorldClim database (Flick and Hijmans, 2017). Additionally, we integrated light-related parameters—Growing Degree Days above 10 °C and Growing Season Length—based on data from the CHELSA Climate database (1980–2010) (Karger at al., 2017), as ARSO does not provide corresponding data for the 2023 season. The long-term averages are now presented in Table 2, and maps illustrating the long-term trends are shown in Figure 4. Importantly, average, minimum, and maximum air temperatures were treated as separate variables and integrated individually into both the ArcGIS spatial analysis (Figure 4) and the PCA analysis (Figure 9). We had clarified this in the 2.7 chapter. By including long-term climate indicators, we also partially account for lag effects—the cumulative influence of environmental conditions across the lifespan of these perennial trees. While our study does not explicitly model year-to-year lagged responses (e.g., the effect of specific prior years), these long-term variables serve as proxies for multi-annual environmental exposure.

Results

COMMENT 11:  Can sections 3.3 and 3.4 be combined for analysis, both of which focus on the analysis of protein and phenolic content in white mulberry leaves.

RESPONSE 11: Thank you for this thoughtful suggestion. We agree that both sections focus on the analysis of protein and phenolic content in white mulberry leaves. However, Section 3.3 is already quite extensive, as it covers variability across mesoregions and includes multiple biochemical parameters. To improve clarity and avoid overloading a single section, we opted to present the influence of pruning in a separate section (3.4). Moreover, pruning is a key cultivation practice and an important focus of our study, deserving dedicated attention and interpretation. Keeping these sections separate ensures better readability and emphasizes the significance of both regional and agronomic factors.

COMMENT 12: Please provide a significance analysis for Fig5. B, Fig8. A, and Fig8. B.

RESPONSE 12: We have revised the clarity of the interpretation of the results of the statistical significance analysis for Figure 5B, Figure 8A, and Figure 8B. For Figure 5B (Total phenolic content), although variation was observed among mesoregions, the Kruskal–Wallis test revealed no statistically significant differences (p = 0.625). Therefore, no group letters are shown for this panel. Figure 8A and 8B (Effects of pruning and mesoregion on total protein and phenolic content): We applied Quade’s method, a rank-based nonparametric ANCOVA, to evaluate the effect of pruning frequency and mesoregion, while controlling for covariates. The null hypothesis was tested at a significance level of α = 0.05. Statistically significant effects are marked with letters (a–d) in Figure 8A, which were determined using the post hoc Dunn-Bonferroni test. For Figure 8B, the result was not significant (p = 0.399), and no group letters are shown. All relevant figures and captions have been updated accordingly, and these results are also reflected in the Results section of the manuscript.

Discussion

COMMENT 13: Supplement the discussion on chemical types, explain the metabolic characteristics of the three types of chemical types, and relate historical germplasm resources to the distribution of chemical types

RESPONSE 13: In the revised version, we have expanded the discussion of chemotypes by more clearly describing the metabolic characteristics of the three main clusters (A, B, and C), including differences in total protein, total phenolic content, and key phenolic subclasses such as caffeoylquinic acids and flavonol glycosides. To the extent possible, we have also contextualized these chemical profiles within environmental and historical frameworks. However, due to the limited availability of detailed historical records and the broad geographical distribution of chemotypes across regions, direct links to specific germplasm origins remain partly speculative. Nevertheless, we incorporated relevant literature and historical practices—such as the grafting of high-yielding Italian varieties—to better illustrate how environmental conditions and cultivation history may have contributed to the current distribution of chemotypes.

COMMENT 14: Deepen the analysis of pruning mechanisms, explain the promotion of protein synthesis by pruning combined with nitrogen metabolism pathways, and discuss the statistical evidence of pruning climate interaction

RESPONSE 14: We appreciate the reviewer’s thoughtful comment. In the revised manuscript, we have expanded Section 4.5 to deepen the discussion on the physiological mechanisms through which pruning affects protein synthesis in mulberry leaves. Specifically, we discuss how pruning, by altering source–sink dynamics and hormonal signaling, enhances nitrogen uptake and assimilation, leading to increased protein content. We integrated findings from recent multi-omics studies in crop plants that highlight the role of key nitrogen-assimilating enzymes such as glutamine synthetase and glutamate synthase, as well as transcriptional networks that regulate amino acid biosynthesis and protein accumulation.Furthermore, we addressed the interaction between pruning and bioclimatic factors in shaping phenolic composition.

COMMENT 15:  Integrate PCA findings and clearly label driving factors

RESPONSE 15: We thank the reviewer for this valuable suggestion. In the revised manuscript, we have integrated the Principal Component Analysis (PCA) findings more explicitly within the discussion. Specifically, we describe the major driving factors of the first two principal components (PC1 and PC2), which together account for 67.55% of the total variance. For PC1, we highlight air temperature (current and historical), precipitation, and their positive associations with protein content and kaempferol glycosides, suggesting a relationship between thermal accumulation and both primary and secondary metabolism. For PC2, we emphasize the role of total insolation and solar radiation in shaping the synthesis of coumaroylquinic acids and influencing traits such as pruning response and canopy structure. These improvements clarify how environmental gradients and management practices interact to shape biochemical traits in mulberry leaves and enhance the interpretation of multivariate patterns presented in the PCA. In addition, the main phenolic derivatives were abbreviated to provide clearer labeling in the PCA diagram.

COMMENT 16: Representative demonstration of single year climate data and uncertainty explanation of conclusions in small sample areas

RESPONSE 16: We appreciate the reviewer’s comment and fully acknowledge the limitations inherent in drawing conclusions from a single-year dataset, especially when working within relatively small and regionally diverse sample areas. To address this, we have included climate observations and long-term climatic averages (1970–2000 or 1981–2010), in the revised manuscript, which show aligned trends in temperature, precipitation, and insolation patterns. We have added a chapter in the discussion (Section 4.4) to acknowledge this uncertainty and emphasize that while our 2023 dataset reflects an unusually warm and wet summer, the climatic trends observed are consistent with broader multi-decadal regional patterns reported in the literature. Thus, we present our findings as regionally representative but interpret them cautiously within the context of interannual variability. Additionally, we ensured that the use of climatic data is always contextualized alongside historical trends, and we refrain from overgeneralizing site-specific responses. Where applicable, we point out that the findings are preliminary and would benefit from future multi-year or time-series studies to validate and expand upon the observed patterns. To emphasize the uncertainty of conclusions in small sample areas, we highlighted the two regions and added a small sample size superscript throuht the manuscript.

COMMENT 17: Verify the sorting of climate parameters

RESPONSE 17: We carefully rechecked the sorting, consistency, and interpretation of all climatic parameters presented in both the results table and the discussion. Clarifications were added to clearly distinguish between short-term (2023) and historical climatic data (1970–2000 or 1980–2010), where applicable. To improve readability and coherence, we also revised the structure of the discussion paragraphs. Specifically, we reorganized the content to first address air temperature, light duration, and insolation, before discussing precipitation effects. However, we acknowledge that in some cases the environmental drivers are interdependent, and their effects on biochemical traits are intertwined. As such, a perfectly linear or isolated treatment of each factor is not always possible. Nonetheless, we have aimed to present the findings in the clearest logical order while maintaining scientific accuracy. Additionally, we ensured that the order of climatic parameters in the discussion now aligns more closely with the structure of results.

COMMENT 18: Add subheadings to the discussion section to make it easier for readers to understand the writing structure of the discussion section clearly.

RESPONSE 18: To improve readability and provide a clearer structure, we have added subheadings to the Discussion section.

 We thank the reviewers for valuable comments that have significanlty improved the quality of the article.

Authors of the manuscript:

Špela Jelen, Martin Kozmos, Jan Senekovič, Danijel Ivajnšič, Silvia Cappellozza and Andreja Urbanek Krajnc

Author Response File: Author Response.docx

Round 2

Reviewer 2 Report

Comments and Suggestions for Authors

The authors have addressed all my comments, and the manuscript has been improved for acceptance.

Reviewer 3 Report

Comments and Suggestions for Authors

Thank you for your reply, which has resolved all my doubts. I think it has reached the publication standard. Congratulations!