Anti-Aging Potential of Illyrian Iris Rhizome Extract: Preliminary Chemical and Biological Profiling and Chemosensor Analysis via GC/MS and UHPLC-DAD-MS/MS Combined with HPTLC Bioautography

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

I was tasked to review the manuscript “Anti-Aging Potential of Illyrian Iris Rhizome Extract: Comprehensive Chemical and Biological Profiling and Chemosensor Analysis via GC/MS and UHPLC-DAD-MS/MS combined with HPTLC Bioautography” for the journal Chemosensors.

Authors performed an extensive multidisciplinary characterization of Illyrian Iris Rhizome extract which I really appreciated. However, I detected some relevant weaknesses in the sampling due to a very reduced number of aliquots. There is a discrepancy between the number of data and number of samples which affect negatively the impact of the paper which is, in this form, able to characterize only the limited population sampled, thus overfitting the natural variability. Authors are required to clarify this weakness and to reinforce the manuscript, even with supplementary sampling. Also, the feature annotation part is weak and a little bit superficial, worthing a more in-depth approach.

Some specific comments are reported below.

• Line 74. What cancer?
• Line 76. Specify the group of authors
• Section 2.2.1. The whole study is based on 2 samples collected in Montenegro despite the huge diffusion of this plant along the Balkan side of the Adriatic coast. How many independent collections were performed? How many replicates? Were the pedoclimatic conditions considered?
• Section 2.7. Any precolumn installed? The injection of 4 g/L extracts involves a huge amount of substances loaded onto the column. For the MS, as a tip, a few units (1-2) of sweep gas are useful to keep the transfer line clean with no relevant loss in sensitivity. What criteria were adopted for the identification of analytes? A numerical criterion is mandatory to assess the quality of matching. Why the authors decided to not using a DDA approach?
• Section 2.8. The injection volume must be reported as a number (1 instead of one). What ΔRI was adopted as criteria? What matching factor was used to identify compounds in the libraries?
• Line 442. Check for typos (demonstrated “A” radical scavenging).
• Table 1. Features annotation must be performed according to scientifically accepted and adopted standardized criteria. I invite the authors to annotate using the level scale annotation style like for this recent paper http://dx.doi.org/10.1016/j.foodchem.2025.144455. In addition, authors can investigate the effects of solvent with chemometric tools such as PCA: signal areas can be used as data matrix. PS: there are two Table 1.
• Section 3.4. Within the compounds detected, are the authors confident that only varietal ones are reported? Were features from the procedural blanks (if analyzed) excluded? Were compounds related to climate and plant stress detected?
• Line 711. What is the typical neutral loss for this class on compounds?
• Table 1 for GC analysis. This table must be renumbered as Table 2. Are the authors confident that the whole essential oil is made of only 4 compounds? I guess the MS can detect many more compounds... How many compounds were detected in similar literature studies?

Author Response

Reviewer 1:

I was tasked to review the manuscript “Anti-Aging Potential of Illyrian Iris Rhizome Extract: Comprehensive Chemical and Biological Profiling and Chemosensor Analysis via GC/MS and UHPLC-DAD-MS/MS combined with HPTLC Bioautography” for the journal Chemosensors.

Authors performed an extensive multidisciplinary characterization of Illyrian Iris Rhizome extract which I really appreciated. However, I detected some relevant weaknesses in the sampling due to a very reduced number of aliquots. There is a discrepancy between the number of data and number of samples which affect negatively the impact of the paper which is, in this form, able to characterize only the limited population sampled, thus overfitting the natural variability. Authors are required to clarify this weakness and to reinforce the manuscript, even with supplementary sampling. Also, the feature annotation part is weak and a little bit superficial, worthing a more in-depth approach.

Some specific comments are reported below.

Comment 1: Line 74. What cancer?

Response: Thank you for your observation. We have revised the sentence: “Preliminary research also suggests anticancer potential warranting further investigation into its efficacy as an adjunct in cancer therapy [10-12]” to “Preliminary research also suggests anticancer potential, as several Iris-derived compounds and extracts have shown cytotoxic or chemopreventive effects against a variety of cancer cell lines, including MCF-7 (breast) and MDA-MB-231 (triple-negative breast), HeLa (cervical), PC-3 (prostate), A549 (lung), HCT116 (colon), HL-60 (leukemia), IGR39 (melanoma), and COR-L23 (lung), warranting further investigation into its efficacy as an adjunct in cancer therapy [10-12]. ”

Comment 2: Line 76. Specify the group of authors

Response: Thank you very much for your kind and helpful suggestion. In this case, we referred to the study as “Saric Medic et al. (2024)” in accordance with MDPI referencing guidelines, which allow for narrative citations using “et al.” when there are multiple authors. The cited article includes ten authors, and we chose this format to preserve the clarity and readability of the sentence. The full list of authors is, of course, properly provided in the reference list. We would also like to kindly clarify that “Saric Medic” is the full surname of the first author, in case there was any confusion regarding that point.

Comment 3:  Section 2.2.1. The whole study is based on 2 samples collected in Montenegro despite the huge diffusion of this plant along the Balkan side of the Adriatic coast. How many independent collections were performed? How many replicates? Were the pedoclimatic conditions considered?

Response: Dear reviewer, we appreciate your careful review and constructive feedback. Regarding your concerns about the limited number of samples, we would like to clarify or strategy regarding the research of this species. This study represents the I (initial) phase of a broader research plan, aimed at assessing whether further investigation and wider sampling would be justified. Given that Iris illyrica is an endemic species, we were particularly cautious not to cause unnecessary harm to wild populations. In order to conduct large-scale sampling across its Mediterranean area, multiple permits and international coordination are a complex and time-consuming process. Our goal in this phase was to verify the relevance of further steps in research.

            As you noted, the first phase involved extensive, multidisciplinary analyses and a large set of measured variables. The second phase, which we are currently initiating, involves expanded sampling across multiple locations, along with soil analysis and environmental data, focusing on a reduced set of key variables identified during the initial study phase.

            The goal of this II phase is to identify habitat characteristics (e.g., soil properties, microclimate conditions, etc) that correlate with the production of high-quality essential oil compounds. These findings will allow us to define a reference habitat as a set of optimal ecological conditions for future cultivation recommendations.

            Therefore, the third phase of our project will focus on the domestication and cultivation potential of Iris illyrica under controlled and optimal conditions identified through the previous stages. As we mentioned in the manuscript, direct exploitation of wild populations is not a sustainable option due to the species’ rarity.

            We would also like to emphasize that our stepwise research design, starting from a limited number of samples with extensive parameterization, followed by expanded sampling with a more targeted analytical focus, is aligned with widely accepted practices in ecological and environmental monitoring.

            In research practice, it is often not financially feasible to conduct both a large number of analyses and extensive sampling simultaneously. Therefore, initial studies typically prioritize analytical depth over sample size to determine the most informative parameters for future investigations. For example, similar tiered approaches are used in frameworks such as the ICPF monitoring system, which distinguishes three levels (I, II, III) depending on the depth and scope of the investigation. Comparable strategies are applied in remote sensing, where researchers often choose between high temporal or spatial resolution. Following this logic, our study was designed to maximize the value of collected sample in the initial phase, while minimizing environmental impact, financial and logistical costs, and time investment. This allowed us to gain meaningful preliminary insights without excessive disturbance to natural populations or the need for complex international permitting procedures.

            We hope this explanation clarifies our rationale and long-term research strategy, and we sincerely thank you again for your valuable insights. Based on your question, we understand that a clarification of our strategy may be necessary in the text (Line 140-148).

Comment 4: Section 2.7. Any precolumn installed? The injection of 4 g/L extracts involves a huge amount of substances loaded onto the column. For the MS, as a tip, a few units (1-2) of sweep gas are useful to keep the transfer line clean with no relevant loss in sensitivity. What criteria were adopted for the identification of analytes? A numerical criterion is mandatory to assess the quality of matching. Why the authors decided to not using a DDA approach?

Response: Thank you very much for your observation and questions. A precolumn was not installed in the current setup. However, to minimize matrix-related contamination and protect the analytical column, we implemented strict sample preparation procedures, including filtration through a 0.22 μm PTFE membrane, and used a small injection volume (4 μL) despite the relatively high concentration (4 mg/mL). We routinely clean the transfer line between sample injections, allowing sufficient time for the system to flush and prevent carryover. These practices helped maintain column performance and minimize carryover. Nevertheless, we appreciate the reviewer’s suggestion and agree that the use of a precolumn would be beneficial, especially for long-term column protection, and it will be considered in future method optimization.

            Thanks for the suggestion. Sweep gas (1–2 units) was not used, but we acknowledge its potential benefit and will consider it in future method optimization.

            Due to the absence of authentic reference standards, compound identifications are considered putative (MSI Level 2) following the Metabolomics Standards Initiative. Identification was based on retention time and elution order comparison with literature data, UV-Vis spectra (both λ_max and spectral shape), and MS/MS fragmentation patterns in comparison with literature. Given the variability of ESI-MS ion intensities depending on matrix and instrument settings, the most representative and structurally informative ions were considered. PubChem Compound IDs (CIDs) have been included to support compound verification and enhance data transparency.

            As stated in lines 324-327, a data-dependent scan was used “Full range acquisition in (m/z 100–100) was performed with a data dependent scan: the collision-induced dissociation of detected molecular ions peaks ([M − H]^– and [M + H]⁺) was tuned at 30 eV in He collision gas, for both ionization modes”. The DDA scan considered the two most intense molecular ions, which were then subjected to further fragmentation to obtain MS/MS spectra. We acknowledge that the stated m/z range (100–100) is a typographical error. The correct range is m/z 100–1000, and we will correct this in the revised manuscript (Line 328).

 

Comment 5: Section 2.8. The injection volume must be reported as a number (1 instead of one). What ΔRI was adopted as criteria? What matching factor was used to identify compounds in the libraries?

Response: Thank you for your valuable comments and suggestions. Regarding the injection volume, we have updated the text to report the injection volume numerically as "1 μL" instead of "one μL" for clarity and consistency (Line 351).

            Regarding the retention index (RI) criteria, a ΔRI (difference between experimental and literature retention indices) within ±10 units was adopted as the threshold for compound identification. This criterion is commonly applied in gas chromatography to ensure reliable retention time matching. For mass spectral identification, a minimum matching factor of 80% was used to confirm compound identity. In cases where the match factor was below 80%, compound identification was further supported by manual inspection of characteristic fragment ions and retention index consistency.

            Moreover, our results demonstrated excellent agreement between experimental and literature retention indices, with ΔRI values ranging from 1 to 6 units. For example, α-irone was identified with an RI^exp of 1541 compared to an RI^lit of 1535, silphiperfol-5-en-3-one B with 1549 vs. 1550, and n-tetradecanoic acid with 1779 vs. 1780. This close correspondence validates the accuracy and reliability of our GC-MS identification method and we have revised the previous text into a more precise one: “The retention times (RT) of the compounds range from 29.32 to 38.96 minutes, reflecting a diversity of volatilities and polarities within the essential oil. Experimental retention indices (RI^exp) closely correspond to literature values (RI^lit) for each compound, with differences of 1–6 units or less, confirming accurate compound identification. This close match validates the reliability of the GC-MS method and supports the assignment of compounds such as α-irone (1541 vs. 1535), silphiperfol-5-en-3-one B (1549 vs. 1550), and n-tetradecanoic acid (1779 vs. 1780).”(Lines 822-828).

 

Comment 6: Line 442. Check for typos (demonstrated “A” radical scavenging).

Response: Thank you for your observation. We have revised the typing mistake.

Comment 7: Table 1. Features annotation must be performed according to scientifically accepted and adopted standardized criteria. I invite the authors to annotate using the level scale annotation style like for this recent paper http://dx.doi.org/10.1016/j.foodchem.2025.144455. In addition, authors can investigate the effects of solvent with chemometric tools such as PCA: signal areas can be used as data matrix. PS: there are two Table 1.

Response: Thank you for your valuable suggestion. Due to the absence of authentic reference standards, compound identifications in this study are considered putative, following the Metabolomics Standards Initiative (MSI Level 2 - Putatively annotated compounds). Identification was performed based on retention time and elution order comparison with literature data, UV-Vis spectra (both λ_max and spectral shape), and MS/MS fragmentation patterns matched with published data. Given the variability of ESI-MS ion intensities depending on matrix and instrument settings, the most representative and structurally informative ions were considered. We also included PubChem Compound IDs (CIDs) to support compound verification and enhance transparency of the data.We have revised section 2.7. LC-MS analysis it with your suggestions (Lines 333-338).

            Thank you for your observation. Upon review, we noticed a labeling error in the manuscript: the table presenting the GC-MS/GC-FID results of the essential oil was incorrectly marked as Table 1 instead of Table 2. This has now been corrected.

            Thank you for your suggestion regarding the use of PCA. Following your recommendation, we performed a preliminary Principal Component Analysis (PCA) to explore the distribution and potential grouping of the chemical data. The results provided some interesting initial insights.

            However, this study is still at a preliminary stage and lacks sufficient sample size and replicates to fully meet the technical requirements for reliable multivariate statistical analysis. We consider that the number of samples does not meet the technical requirements for PCA analysis. According to general guidelines for the ratio between the number of samples and variables, it is recommended to have at least 5 samples per variable (preferably 10), with an absolute minimum of 3 if the structure is clear. Additionally, PCA should ideally be based on at least 30 samples, with 50–100 being optimal.

            We consider that including the PCA results in the manuscript at this stage may be at this point may be too early given the limited sample size and technical constraints, which could affect the validity of the interpretation. In the next phase of the research, when we will have a larger number of samples from different locations and more replicates per location, that will enable us to apply multivariate statistical techniques and obtain more reliable and relevant results and conclusions.

                          

Comment 8: Section 3.4. Within the compounds detected, are the authors confident that only varietal ones are reported? Were features from the procedural blanks (if analyzed) excluded? Were compounds related to climate and plant stress detected?

Response: Regarding the procedural blanks, we did not include them in this study. Our focus was on the varietal compounds, as determined by retention times, UV-Vis spectra, and MS data, which were consistent with the literature. As for compounds related to climate or plant stress, this aspect was not specifically investigated in the current work. Detection of compounds related to climate conditions or plant stress represents a more advanced level of investigation, which was beyond the scope of the current study. However, we acknowledge the importance of this aspect and plan to address it in future research, including the influence of environmental factors such as soil and climate (Lines 140-148).

Comment 9: Line 711. What is the typical neutral loss for this class on compounds?

Response: We thank the reviewer for the valuable comment. Typical neutral losses observed for iridal-type triterpenoids include the loss of H₂O (–18 Da) or CO (–28 Da). In our spectra, the fragment ion at m/z 433 (from m/z 451) corresponds to a neutral loss of 18 Da. The sentence "The main MS/MS fragment at m/z 485 indicates typical neutral losses common for this class." is incorrect and will be removed from the manuscript.

Comment 10: Table 1 for GC analysis. This table must be renumbered as Table 2. Are the authors confident that the whole essential oil is made of only 4 compounds? I guess the MS can detect many more compounds... How many compounds were detected in similar literature studies?

Response: Thank you very much for your constructive and thoughtful comment regarding the number of compounds identified in the essential oil sample. We fully agree that, in most cases, gas chromatography–mass spectrometry (GC/MS) enables the detection of a broad range of volatile constituents, especially when analyzing essential oils. Your observation is absolutely valid and appreciated.

            Literature, however, has shown that the chemical composition of volatile compounds in Iris rhizomes changes significantly during the drying and aging process. In traditional orris oil production, rhizomes are harvested, thoroughly dried, and typically aged for 2–5 years [i]. During this period, the fatty acids and oils in the rhizomes undergo oxidation and degradation, resulting in the formation of unique aromatic compounds known as irones—key fragrance constituents of orris oil. In contrast, fresh rhizomes do not contain any irones [ii].

            For example, one study reported that fresh rhizomes of Iris florentina contained almost no irones, while in properly aged rhizomes, approximately 4.2% α-irone was detected [iii]. The aging process (2–5 years) induces major chemical transformations, with irones forming through oxidative degradation of triterpene precursors called iridals. Only (which were detected in our study, LCMS), such well-aged orris oil develops the full floral aroma, whereas young or insufficiently dried rhizomes mainly yield fatty acids and simpler volatiles such as aldehydes and alcohols (such as ours) [iii, iv].

            In terms of chemical profile, fresh rhizomes are dominated by fatty acids—particularly myristic acid [v]. Without sufficient aging, the GC/MS profile tends to show only a few compounds, primarily saturated fatty acids. In contrast, aged rhizomes display a much more complex profile with high levels of irones, norisoprenoids, and other volatile compounds [iii].

            In the study by Friščić et al., 2024 [i], rhizomes of the species Iris illyrica V. and Iris illyrica Z. were analyzed, collected during April 2019 from different natural populations in Croatia. The results of GC/MS analysis of EO obtained by hydrodistillation indicate that the rhizomes of Iris illyrica V. contain no iron, and Iris illyrica Z. contains only 0.03% cis-α-iron (about 2-month-old rhizome), while our results indicate that it contains 9.2% α-iron (about 1-year-old rhizome). From a commercial and biochemical standpoint, irones are the key economic and fragrance-related value of Iris rhizomes. Their sample also lacked other volatiles such as alcohols and ketones, or contained them in only trace amounts—similar to our results. Moreover, the plant material used in that study included species closely related to ours, such as Iris illyrica and Iris pseudopallida. In both their study and ours, the main component identified was myristic acid. What sets our sample apart, however, is that despite being relatively young, the rhizome already shows a high content of irones—highlighting the superior quality of our material. Therefore, detecting only three major components in our GC/MS analysis is fully in line with published research, particularly when dealing with young or not fully aged rhizomes. Our results are scientifically supported and reflect the natural evolution of chemical constituents in Iris rhizomes of this species, during aging.

            Consistently with the mentioned, we have added the corresponding text in the Revised Manuscript (lines 812-818).

[i]https://www.mdpi.com/14203049/29/17/4107#:~:text=by%20oxidative%20degradation%20from%20their,quality%20EO%20%5B3%20%2C%20148

[ii]https://www.mdpi.com/20734395/9/12/815#:~:text=was%20analyzed%20in%20this%20study,115

[iii] https://www.turkjps.org/articles/composition-of-volatile-oil-of-iiris-pallidai-lam-from-ukraine/doi/tjps.07379

[iv]https://www.mdpi.com/20734395/9/12/815#:~:text=was%20analyzed%20in%20this%20study,115

[v]https://scialert.net/fulltext/?doi=ajbmb.2013.38.49#:~:text=The%20findings%20here%20agreed%20with,mediate%20their%20membrane%20interaction%20and

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

1 There are some writing irregularities in the manuscript. For instance, plant Latin names should be italicized, and the full name should be used when the Latin name first appears in the text, while the abbreviated form should be used subsequently. Please carefully check and verify these points.

2 It is recommended to supplement the “LC-MS analysis” section with multivariate statistical analysis and an analysis of differential metabolites between different groups, And visualize the analysis results.

3 In the supplementary materials, please provide the raw LC-MS data, including peak area and other relevant information.

4 There are many abbreviations appearing in the text. It is recommended to provide an abbreviation comparison table before “References”.

5 I suppose that only testing the impact of the samples on the cell viability of HaCaT cells is insufficient to support the conclusion that it possesses anti-aging efficacy. More experiments are needed for verification. Alternatively, please revise the title of the manuscript.

Author Response

Reviewer 2:

Comment 1: There are some writing irregularities in the manuscript. For instance, plant Latin names should be italicized, and the full name should be used when the Latin name first appears in the text, while the abbreviated form should be used subsequently. Please carefully check and verify these points.

Response: Thank you for your observation. We have carefully reviewed the manuscript and made the necessary corrections regarding the formatting of Latin plant names. Full scientific names are now provided upon first mention, followed by the appropriate abbreviated forms throughout the rest of the text. All Latin names have also been italicized consistently, following scientific writing conventions.

Comment 2: It is recommended to supplement the “LC-MS analysis” section with multivariate statistical analysis and an analysis of differential metabolites between different groups, And visualize the analysis results.

Response: Dear Reviewer, thank you for your suggestion regarding the use of PCA. Following your recommendation, we performed a preliminary Principal Component Analysis (PCA) to explore the distribution and potential grouping of the chemical data. The results provided some interesting initial insights.

            However, this study is still at a preliminary stage and lacks sufficient sample size and replicates to fully meet the technical requirements for reliable multivariate statistical analysis. We consider that the number of samples does not meet the technical requirements for PCA analysis. According to general guidelines for the ratio between the number of samples and variables, it is recommended to have at least 5 samples per variable (preferably 10), with an absolute minimum of 3 if the structure is clear. Additionally, PCA should ideally be based on at least 30 samples, with 50–100 being optimal.

            We consider that including the PCA results in the manuscript at this stage may be at this point may be too early given the limited sample size and technical constraints, which could affect the validity of the interpretation. In the next phase of the research, when we will have a larger number of samples from different locations and more replicates per location, that will enable us to apply multivariate statistical techniques and obtain more reliable and relevant results and conclusions.

                          

Comment 3: In the supplementary materials, please provide the raw LC-MS data, including peak area and other relevant information.

Response: We appreciate your comment and fully understand the importance of providing the raw LC/MS data. At this moment, we are unable to upload the full dataset, as some of the co-authors responsible for the LC/MS analysis are currently on a collective annual leave. However, we assure you that, upon acceptance of the manuscript, we will provide all relevant raw data and supplementary information in a timely and transparent manner.

Comment 4:  There are many abbreviations appearing in the text. It is recommended to provide an abbreviation comparison table before “References”.

Response: Thank you for your helpful suggestion. In response, we have prepared a comprehensive abbreviation table, which has now been added before the “References” section in the revised manuscript, as recommended.

Comment 5:  I suppose that only testing the impact of the samples on the cell viability of HaCaT cells is insufficient to support the conclusion that it possesses anti-aging efficacy. More experiments are needed for verification. Alternatively, please revise the title of the manuscript.

Response: Thank you very much for your thoughtful and constructive comment. We fully agree that evaluating the impact of the samples solely on HaCaT cell viability is not sufficient to confirm anti-aging efficacy. We would like to respectfully clarify that the cytotoxicity assessment was conducted solely as a preliminary screening to evaluate the biocompatibility of the extracts for potential incorporation into cosmetic formulations. This experiment aimed to help identify a safe concentration range for further studies, and not to imply any direct correlation between cell viability and anti-aging activity. Nowhere in the manuscript do we suggest or interpret the results of the cytotoxicity assay as evidence of anti-aging potential. The parameters used to assess anti-aging and cosmetic potential were exclusively based on antioxidant capacity and tyrosinase inhibition.

To address your concern and to better reflect the scope and preliminary nature of the work, we have revised the manuscript title as follows: "Anti-Aging Potential of Illyrian Iris Rhizome Extract: Preliminary Chemical and Biological Profiling and Chemosensor Analysis via GC/MS and UHPLC-DAD-MS/MS Combined with HPTLC Bioautography." We believe this revised title more accurately conveys the exploratory nature of the study. Additionally, in the introduction, we have outlined that this research is part of a three-phase approach, and the current paper presents the initial phase aimed at assessing the potential of Iris illyrica through extensive multidisciplinary analyses. Importantly, the manuscript does not suggest that the cytotoxicity assay serves as a measure of anti-aging efficacy but rather as a supportive screening tool for biocompatibility.

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

• Please indicate botanical code of voucher of the plant.?
• After the Hydrodistillation, the oil was dried with some drying reagent.?
• Explain how you calculated the retention indices? They inject standard alkanes, what equation did they use?.
• I recommend using: Adams, R.P. Identification of Essential Oil Components by Gas Chromatography/Mass Spectrometry, 4th ed.; for the identification of the chemical composition of the essential oil.
• They describe the use of gas chromatography coupled with mass and FID, but do not write the results of the chemical composition of the same, please include it.
• Include gas chromatograms from the analyses performed.
• Improve the quality of graphics in the supplementary material.

Author Response

Reviewer 3:

Comment 1: Please indicate botanical code of voucher of the plant.?

Response: Thank you for your comment regarding the voucher specimens. The botanical voucher numbers (N^o 2-1513 and N^o 2-1514) of Iris pallida Lam. 1789 subsp. Illyrica (Tomm. ex Vis.) K. Richt. 1890 are indicated in the manuscript (Section 2.2.1. Plant material collection), along with detailed collection locations, dates, and the name of the identifier (Dr. Boris Radak). Additionally, these specimens are deposited at the BUNS Herbarium (Herbarium of the Department of Biology and Ecology, Faculty of Natural Sciences, University of Novi Sad), which holds the official herbarium code BUNS as listed in the Index Herbariorum. For clarity, we have emphasized this information again in the revised manuscript to ensure no ambiguity remains.

Comment 2: After the Hydrodistillation, the oil was dried with some drying reagent.?

Response: Thank you very much for kindly pointing out this important detail, which was unintentionally omitted from the manuscript. After hydrodistillation, the essential oil was dried over anhydrous sodium sulfate to remove residual moisture before storage and subsequent analysis. This step was performed to ensure the accuracy of the GC/MS and GC/FID results. We have now added this information to the revised manuscript for clarity (Lines 203-205).

Comment 3:  Explain how you calculated the retention indices? They inject standard alkanes, what equation did they use? I recommend using: Adams, R.P. Identification of Essential Oil Components by Gas Chromatography/Mass Spectrometry, 4th ed.; for the identification of the chemical composition of the essential oil.

Response: Thank you for your observation. The retention indices (RI_x) were automatically calculated in AMDIS (Automated Mass Spectral Deconvolution and Identification System) software by using Analysis Type - Use Retention Index Data. Namely, AMDIS can utilize an RI Calibration Data file that holds a correlation between retention time and retention index. The RI Calibration Data file is created by analyzing a clean mixture of known composition (homologous series of n-alkanes from C₈-C₂₀ as standards in our case). The Use Retention Index Data analysis type first identifies target compounds using spectral comparisons only, and then it utilizes the actual retention times of the identified targets to compute their retention index values by linear interpolation techniques utilizing the calibration data held in the RI Calibration Data file.

            The retention (arithmetic) indices are calculated by using the Van den Dool and Kratz (1963) formula for temperature programming as follows:

RI_x = 100n + 100(t_x-t_n) / (t_n+1 − t_n)

where RI_x denotes the retention index of compound “x”; n is the number of carbon atoms in the n-alkane eluting immediately before the compound “x”; t_n and t_n+1 are retention times of the reference n-alkane hydrocarbons eluting immediately before and after chemical compound “x” and t_x is the retention time of compound “x”.

            The experimentally determined retention indices are then compared with the ones given in Adams (2007).

Adams R.P. (2007). Identification of essential oil components by gas chromatography /mass spectrometry, 4^th ed., Carol Stream, Allured Publishing Co., Illinois, USA.

Comment 4: They describe the use of gas chromatography coupled with mass and FID, but do not write the results of the chemical composition of the same, please include it.

Response: Thank you for your observation. Upon review, we noticed a labeling error in the manuscript: the table presenting the GC-MS/GC-FID results of the essential oil was incorrectly marked as Table 1 instead of Table 2. This has now been corrected.

            The revised Table 2 clearly shows the essential oil composition, including retention times, experimental and literature RI values, compound identification, and relative contents (%). Identification was based on GC/MS spectral matching and RI comparison, while quantification was performed by GC/FID using peak area normalization. We have clarified this in both the manuscript text and the table legend.

            A new paragraph analyzing the retention times and retention indices was added to Section 3.5 (GC/MS and GC/FID analysis) to further discuss the match between experimental and literature values, supporting the confidence in compound identification (Lines 822-828).

 

Comment 5: Include gas chromatograms from the analyses performed.

Response: Thank you for your comment. The gas chromatograms from the analyses are included in the Supplementary Material as Figure S17, which presents the Total Ion Chromatogram (TIC) of the essential oil from Illyrian iris rhizome. We believe this provides a clear overview of the chromatographic separation and detected compounds.

Comment 6: Improve the quality of graphics in the supplementary material.

Response: Thank you for your valuable suggestion. We agree that the quality of graphics in the supplementary material is important for clarity and reproducibility. At the moment, we are unable to revise the figures due to the collective annual leave of the co-authors responsible for data visualization. However, we commit to improving the resolution and overall quality of all graphical materials in the supplementary section upon acceptance of the manuscript.

 

 

 

 

Author Response File: Author Response.pdf

Reviewer 4 Report

Comments and Suggestions for Authors

The manuscript presents a comprehensive phytochemical and bioactivity evaluation of Illyrian iris (Iris pallida subsp. illyrica) rhizome extracts using multiple analytical techniques (GC/MS, UHPLC-DAD-MS/MS, HPTLC, and spectrophotometric and cell viability assays). The study investigates both conventional and green extraction methods and explores potential applications in cosmetics, particularly for anti-aging and skin-whitening formulations. This work fills a notable gap in the literature regarding this rare, endemic plant.

Critical Comments

1. Overly descriptive in some sections; a more analytical comparison of results across methods would improve clarity.
2. Quantitative data on bioactivity is somewhat underinterpreted more discussion is needed on the implications of the observed bioactivities in relation to current benchmarks or commercial standards.
3. Limited discussion of in vivo applicability, safety, or formulation challenges.
4. Identification confidence levels for MS data (e.g., use of authentic standards vs database matches) are not clearly stated.
5. Potential data overload in some figures/tables summary graphics or PCA may improve accessibility.
6. Some minor grammatical and formatting inconsistencies persist throughout the manuscript.
7. Why were the selected green solvents (e.g., glycerol, 1,3-propanediol) chosen over others? Were toxicity or dermal compatibility factors considered?
8. Could you clarify whether the extraction parameters (temperature, duration) were optimized for each solvent?
9. How were the UHPLC-MS/MS compound identifications validated were authentic standards used, or only spectral databases?
10. Have you considered using multivariate statistics (e.g., PCA, HCA) to better visualize differences in extract profiles?
11. What are the implications of the relatively low tyrosinase inhibition values compared to kojic acid?
12. The essential oil showed low bioactivity what role, if any, could its components play in cosmetic applications?
13. How do the yields and energy requirements of green solvents compare to conventional ones in this study?
14. How do your antioxidant values compare to commonly used botanical antioxidants in cosmetics (e.g., green tea, grape seed)?
15. What are the primary limitations for using Illyrian iris rhizome extracts commercially (e.g., regulatory, supply chain)?
16. Did you evaluate the stability of extracts or compounds post-extraction?

Author Response

Reviewer 4:

The manuscript presents a comprehensive phytochemical and bioactivity evaluation of Illyrian iris (Iris pallida subsp. illyrica) rhizome extracts using multiple analytical techniques (GC/MS, UHPLC-DAD-MS/MS, HPTLC, and spectrophotometric and cell viability assays). The study investigates both conventional and green extraction methods and explores potential applications in cosmetics, particularly for anti-aging and skin-whitening formulations. This work fills a notable gap in the literature regarding this rare, endemic plant.

Critical Comments

Comment 1:  Overly descriptive in some sections; a more analytical comparison of results across methods would improve clarity.

Response: Thank you for your valuable feedback. We agree that analytical comparison is essential for clarity. In our revised manuscript, we have made efforts to highlight the correlation between the results obtained from different analytical techniques. Specifically, we emphasized the agreement between the HPTLC profiles and the bioautographic assays, as well as the consistency between the bioautographic findings and the results of spectrophotometric assays (lines 541-542). While the LC/MS section may appear more detailed, this is primarily due to the high number of detected compounds. Nevertheless, we aimed to present the data as concisely as possible without omitting key information. Additionally, we have now included a note on the consistency between HPTLC and LC/MS results (lines 745-749; 804-806) to further strengthen the analytical link between the methods. We hope that these revisions address your concerns and improve the overall clarity and coherence of the discussion.

Comment 2: Quantitative data on bioactivity is somewhat underinterpreted more discussion is needed on the implications of the observed bioactivities in relation to current benchmarks or commercial standards.

Response: Thank you for this valuable comment. We fully agree that a clearer interpretation of the quantitative bioactivity data can enhance the overall impact of the study. In the TLC section, co-applied reference standards were used primarily for preliminary screening to tentatively identify phenolic compounds frequently encountered in plant extracts—an approach that is commonly accepted in phytochemical analysis. For the bioactivity assays, DPPH radical scavenging was quantified relative to the standard compound Trolox, while tyrosinase inhibition was benchmarked against kojic acid, a widely recognized gold standard. As already noted in the manuscript, some phenolic compounds were quantified tentatively based on spectral library matching, which is a well-documented and frequently used strategy in the absence of authentic standards. In line with your suggestion, we will revise the manuscript to express this more clearly and precisely, to avoid ambiguity. Due to the absence of authentic reference standards, compound identifications are considered putative (MSI Level 2) following the Metabolomics Standards Initiative. Identification was based on retention time and elution order comparison with literature data, UV-Vis spectra (both λ_max and spectral shape), and MS/MS fragmentation patterns in comparison with literature. Given the variability of ESI-MS ion intensities depending on matrix and instrument settings, the most representative and structurally informative ions were considered. PubChem Compound IDs (CIDs) have been included to support compound verification and enhance data transparency.

            We would also like to emphasize that the primary aim of our study was not to establish absolute quantitative bioactivity rankings, but rather to compare the chemical and biological profiles of green versus conventional extracts, with a particular focus on their relevance and potential application in cosmetic formulations. Unlike kojic acid, which is routinely used as a reference compound in tyrosinase inhibition assays at well-defined concentrations, literature data for green tea extracts—despite being a well-known antioxidant—show considerable variability in reported antioxidant activities. This inconsistency stems from multiple factors, including differences in the type and nature of the sample (fresh leaves, dried tea, powdered form), the extraction method (solvent type, temperature, time, solid-to-solvent ratio), and geographical origin. As such, direct comparison of our results with previously published data is challenging. For instance, while we identified a study reporting DPPH activity of an ethanolic green tea extract as 73 ± 2.55%, the extraction was performed for 7 hours at 60 °C, and the tested extract concentration was not clearly defined, rendering the data difficult to compare to ours (30 minutes, room temperature, known dilution of extract) [v]. Furthermore, most available studies rely on conventional extraction protocols, frequently involving methanol and elevated temperatures, which differ significantly from our experimental conditions [vi, vii]. Therefore, caution is warranted when interpreting inter-study comparisons, and our focus remains on the relative assessment of extraction solvents under standardized, green, and reproducible conditions. For these reasons, we intentionally avoided referencing absolute antioxidant values from the literature in the context of green tea extracts. Instead, based on Trolox-equivalent quantification, we concluded that our best-performing sample exhibited a moderate DPPH radical scavenging capacity, which was sufficient for relative comparison among the tested extracts under standardized and environmentally friendly conditions.

[v] https://doi.org/10.1080/10942912.2021.1953524

[vi] http://dx.doi.org/10.5530/pj.2019.11.122

[vii]https://pubs.acs.org/doi/full/10.1021/jf8022782?casa_token=14uVpLsxVC0AAAAA%3A4ahJ_AhbhyPSrbvJ9dukiu9t2uKSlO__3LzmyUqS6ORdbslYi5lk1Bmc59DznViwtZ1eZrLwZjkTF1HB

Comment 3: Limited discussion of in vivo applicability, safety, or formulation challenges.

Response: Thank you for your observation. We have now included a detailed section about in vivo applicability, safety, and cosmetic challenges: “Although glycerol extract demonstrated limited tyrosinase inhibition and DPPH radical scavenging activity, the development of glycerol-based natural deep eutectic solvents (NADES) offers a promising strategy to enhance bioactivity while maintaining low cytotoxicity by modifying the co-component within the eutectic mixture. Such eutectic systems are known to stabilize extracts and can exhibit physicochemical and biological properties distinct from pure components (glycerol, in our case), potentially improving extract stability and functionality [iv]. Additionally, nonpolar eutectic solvents may be explored as alternative extraction media to selectively isolate the nonpolar bioactive compounds present in the rhizome, potentially combining high extraction efficiency with favorable safety profiles, given their origin from natural metabolites [iv]. Building upon these findings, further in vivo studies aimed at defining the safe concentration range of rhizome extracts, also focusing on skin penetration, irritancy, and comprehensive in vivo safety assessments, are essential to translate these findings into effective and safe dermatological formulations.”

[iv]           https://www.frontiersin.org/journals/chemistry/articles/10.3389/fchem.2022.954835/full

Comment 4: Identification confidence levels for MS data (e.g., use of authentic standards vs database matches) are not clearly stated.

Response: As shown in Table 1, compound identification was based on retention time, UV-Vis spectra, molecular ion mass ([M–H]⁻), and MS/MS fragmentation patterns. These data were compared with published literature and public spectral databases.

            Since authentic standards were not available in our laboratory, all identifications are considered putative and correspond to Metabolomics Standards Initiative (MSI) Level 2. PubChem CIDs are provided to facilitate structural cross-referencing but do not replace direct validation by standards. We have clarified this point in the Materials and Methods section (Lines 336-341).

Comment 5: Potential data overload in some figures/tables summary graphics or PCA may improve accessibility.

Response: Thank you very much for this constructive and insightful suggestion. Multivariate techniques are most effective when working with complex datasets containing numerous intercorrelated variables, as is the case with our metabolite profiles. However, regarding the experimental datasets, e.g., DPPH radical scavenging activity, cytotoxicity assays, tyrosinase inhibition, and TLC-based bioautography, the number of measured variables is relatively small—typically 7 to 8 per experiment. In such cases, the application of PCA may not be appropriate, as the limited dimensionality of the dataset does not allow for meaningful extraction of latent structures, and the results can be interpreted through direct comparison. Additionally, applying PCA on such low-dimensional datasets might lead to overfitting, artificial clustering, or misrepresentation of the actual variability.

Comment 6: Some minor grammatical and formatting inconsistencies persist throughout the manuscript.

Response: Thank you for your observation. We acknowledge that minor grammatical and formatting inconsistencies were present in the initial submission. The manuscript has been carefully revised.

Comment 7: Why were the selected green solvents (e.g., glycerol, 1,3-propanediol) chosen over others? Were toxicity or dermal compatibility factors considered?

Response: Thank you for your relevant and valuable question. The selected green solvents, such as glycerol and 1,3-propanediol, were chosen due to their widespread acceptance and compatibility within the cosmetic applications (https://www.sciencedirect.com/science/article/abs/pii/S0065229620300525). Both solvents are already used as excipients or humectants in various skincare formulations and are considered safe, non-toxic, and skin-friendly. Their established safety for topical use was a key factor in their selection, as our goal was to explore extraction systems that are not only effective but also suitable for incorporation into cosmetic products. Additionally, from an analytical perspective, we aimed to compare the chemical profiles and biological activities of greener solvent systems with conventional organic solvents. This allowed us to assess not only their extraction efficiency, but also their practical applicability and safety potential in cosmetic formulations. In that manner, we highlight the reason for the selection of the mentioned solvents (Lines 170-171).

Comment 8: Could you clarify whether the extraction parameters (temperature, duration) were optimized for each solvent?

Response: Thank you for your insightful question. In this study, the extraction parameters (such as temperature and duration) were not individually optimized for each solvent, as the primary focus was not on maximizing extraction efficiency. Instead, we applied a uniform ultrasound-assisted extraction (UAE) protocol at room temperature for all solvents. This standardized approach was deliberately chosen to ensure that the extraction process itself remains environmentally responsible, in line with the principles of Green Analytical Chemistry (GAC). https://www.sciencedirect.com/science/article/pii/S016599361500148X?casa_token=4cDczzoeSnwAAAAA:maFXWlJDj8TquqhLbFPESheu7ptqznpelZWIuHqDTz-UQnE0T6SJlYg9_KzS5E2shzy6k3ZMjGk

                        Our primary goal was to compare the chemical profiles and biological activities of extracts obtained using different solvent systems, rather than to maximize yield. By using consistent conditions, we aimed to better understand the correlation between solvent polarity, phytochemical composition, and biological activity across green and conventional solvents. We fully agree that optimizing extraction conditions for each solvent system could be valuable in future studies, particularly for obtaining more efficient or enriched extracts depending on the intended application. Thus, we incorporated the following text “Future studies could focus on alternative green extraction techniques employing nonpolar solvents such as supercritical CO₂, alongside the optimization of key parameters—including sample-to-solvent ratio, extraction time, and solvent volume—within the framework of green chemistry, to improve the yield of tyrosinase inhibitors and enhance extract potency for cosmetic applications.” (Lines 564-572).

 

Comment 9: How were the UHPLC-MS/MS compound identifications validated were authentic standards used, or only spectral databases?

Response: In our study, compound identification was based primarily on high-resolution chromatographic separation, UV-Vis detection, and tandem mass spectrometry (MS/MS) using a 3D ion trap with electrospray ionization (ESI) in both positive and negative modes. The identification process relied on the integration of multiple data types: retention time, UV spectra, molecular ion peaks ([M − H]⁻ and [M + H]⁺), and characteristic MS/MS fragmentation patterns. Due to the unavailability of authentic reference standards in our laboratory (While authentic standards were not used in this phase of the study), compound identification was performed by comparing our data with spectral information and fragmentation behavior reported in peer-reviewed literature and public databases.

Comment 10: Have you considered using multivariate statistics (e.g., PCA, HCA) to better visualize differences in extract profiles?

Response: We agree that multivariate statistical tools such as PCA or HCA can provide useful insights, particularly when the aim is to classify or cluster samples based on complex chemical data. However, in the context of the DPPH assay, tyrosinase inhibition, cytotoxicity, and TLC assays, our objective was not to group or discriminate between samples, but rather to track how the chemical or biological profiles change depending on the extraction solvent. In the case of TLC profiles, the visual differences between solvent systems were sufficiently distinguishable and could be interpreted without the need for dimensionality reduction. The bands were distinct enough to allow comparative assessment. Since no large matrix of image-derived variables was generated (as would be required for proper chemometric treatment), applying PCA in this case was not appropriate, in our opinion. Similarly, bioactivity assays included only a small number of test conditions and variables, which does not justify the application of multivariate statistics such as PCA. These techniques are most informative when applied to high-dimensional datasets where hidden variance structures exist. Nevertheless, we fully acknowledge the value of PCA and HCA, and we intend to explore such approaches in future studies involving larger datasets or more complex experimental designs.

Comment 11: What are the implications of the relatively low tyrosinase inhibition values compared to kojic acid?

Response: Thank you for your observation. We agree that kojic acid, as a known gold standard inhibitor, exhibits stronger tyrosinase inhibition than our extracts. However, our goal was to explore the relative activity of Iris rhizome extracts obtained under mild extraction conditions, rather than to match synthetic inhibitors. The moderate activity observed may be due to the extraction method (ultrasound at room temperature) and solvent polarity. Likely, reflux extraction or less polar solvents (e.g., dichloromethane, chloroform, or supercritical CO₂) could yield higher concentrations of active nonpolar compounds. Indeed, in our study, less polar extracts (e.g., hexane, ethyl acetate) as well as essential oil showed stronger inhibition, suggesting that nonpolar constituents play an important role. Additionally, rhizome age may influence bioactivity. Studies suggest that older rhizomes (stored 2–5 years) accumulate more bioactive irones and oxidation products, which may enhance tyrosinase inhibition. Our sample was stored for 12 months, and longer maturation could improve activity. Additionally, as you suggested earlier, and we agreed, the optimization of extraction parameters could be the choice for enhancing the extract potency. We included this clarification in the revised manuscript (Lines 564-572; “Future studies could focus on alternative green extraction techniques employing nonpolar solvents such as supercritical CO₂, alongside the optimization of key parameters—including sample-to-solvent ratio, extraction time, and solvent volume—within the framework of green chemistry, to improve the yield of tyrosinase inhibitors and enhance extract potency for cosmetic applications. It has been observed that, in addition to the gradual formation of irones, the ageing of Iris rhizomes also leads to the presence of other oxidized derivatives, suggesting that storage-induced oxidative processes significantly alter the chemical profile of the rhizome and may, consequently, influence its biological activity.”)

Comment 12: The essential oil showed low bioactivity what role, if any, could its components play in cosmetic applications?

Response: Thank you for your valuable comment. The essential oil (EO) demonstrated low to moderate tyrosinase inhibitory activity, which nonetheless indicates the presence of compounds with inhibitory potential. Although the overall activity was not strong, it is important to consider that the oil yield was relatively low and that only a limited quantity of rhizome material (10 g) was used, with a short hydrodistillation duration. Given the 23 ± 3% inhibition at the tested concentration, and considering the small amount of extractable material, we believe this result is encouraging. It suggests that, under optimized conditions—such as increased raw material quantity, extended distillation time, or use of pre-treated or aged rhizomes—the inhibitory activity could be enhanced. However, our results indicate that EO could only serve as an anti-pigmentation candidate, but not an anti-wrinkle candidate for the industry.

Comment 13: How do the yields and energy requirements of green solvents compare to conventional ones in this study?

Response: Thank you for this valuable comment. While the use of green solvents such as glycerol and 1,3-propanediol required an additional SPE clean-up step due to their low volatility, it's important to note that no evaporation step was needed for solvent removal. In contrast, conventional solvents were evaporated before analysis, requiring electricity and additional processing time. However, this extra step (SPE) does not outweigh the long-term benefits of using green solvents compared to conventional organic solvents. Although organic solvents simplified sample handling, they come with long-term environmental costs—including toxic emissions, flammability, waste storage, and a higher carbon footprint. Green solvents, by comparison, are non-volatile, biodegradable, and renewable, offering reduced energy demand, improved laboratory safety, and better alignment with green chemistry principles.

            The extraction yields varied notably depending on the solvent used: among green solvents, glycerol achieved the highest yield (10.0%), surpassing even the best performed conventional solvent, ethyl acetate (9.7%). 1,3-propanediol (5.2%) also outperformed hexane (3.2%) and acetone (5.0%), demonstrating strong extraction efficiency within the green solvent group, while water gave the lowest yield (2.6%). Among conventional solvents, ethyl acetate showed the highest yield (9.7%), followed by acetone (5.0%), ethanol (4.8%), and hexane (3.2%). These results indicate that green solvents can match or exceed conventional ones in extraction efficiency, with glycerol (10.0%) and propanediol (5.2%) showing particular promise. However, despite its highest yield, glycerol (10.0%) performed poorly in tyrosinase inhibition and DPPH radical scavenging assays, suggesting it extracts compounds with limited antioxidant and anti-tyrosinase activity but possibly other biological functions. This underscores the need for further investigation into the biofunctional potential of glycerol-soluble constituents.

 

Comment 14: How do your antioxidant values compare to commonly used botanical antioxidants in cosmetics (e.g., green tea, grape seed)?

Response: Unlike kojic acid, which is routinely used as a reference compound in tyrosinase inhibition assays at well-defined concentrations, literature data for green tea extracts—despite being a well-known antioxidant—show considerable variability in reported antioxidant activities. This inconsistency stems from multiple factors, including differences in the type and nature of the sample (fresh leaves, dried tea, powdered form), the extraction method (solvent type, temperature, time, solid-to-solvent ratio), and geographical origin. As such, direct comparison of our results with previously published data is challenging. For instance, while we identified a study reporting DPPH activity of an ethanolic green tea extract as 73 ± 2.55%, the extraction was performed for 7 hours at 60 °C, and the tested extract concentration was not clearly defined, rendering the data difficult to compare to ours (30 minutes, room temperature, known dilution of extract) [v]. Furthermore, most available studies rely on conventional extraction protocols, frequently involving methanol and elevated temperatures, which differ significantly from our experimental conditions [vi, vii]. Therefore, caution is warranted when interpreting inter-study comparisons, and our focus remains on the relative assessment of extraction solvents under standardized, green, and reproducible conditions. For these reasons, we intentionally avoided referencing absolute antioxidant values from the literature in the context of green tea extracts. Instead, based on Trolox-equivalent quantification, we concluded that our best-performing sample exhibited a moderate DPPH radical scavenging capacity, which was sufficient for relative comparison among the tested extracts under standardized and environmentally friendly conditions.

[v]https://www.tandfonline.com/doi/full/10.1080/10942912.2021.1953524?utm_source=chatgpt.com#d1e595

[vi] https://phcogj.com/article/921?utm_source=chatgpt.com

[vii]https://pubs.acs.org/doi/full/10.1021/jf8022782?casa_token=14uVpLsxVC0AAAAA%3A4ahJ_AhbhyPSrbvJ9dukiu9t2uKSlO__3LzmyUqS6ORdbslYi5lk1Bmc59DznViwtZ1eZrLwZjkTF1HB

While we acknowledge that a direct numerical comparison with antioxidants like green tea or grape seed was not performed, the detection of strong radical scavenging zones—particularly those attributed to quercetin and lipophilic constituents—suggests that I. pallida subsp. illyrica rhizomes contain potent antioxidant compounds. This positions the species as a promising, though currently underexplored, source of antioxidant agents for cosmetic applications.

Comment 15: What are the primary limitations for using Illyrian iris rhizome extracts commercially (e.g., regulatory, supply chain)?

Response: Thank you for your valuable question. The main barriers for using Illyrian iris rhizome extracts commercially are regulatory and supply chain issues. From this perspective, more toxicological and safety studies are needed for regulatory approval as this is the first multidisciplinary chemical and functional characterization of the endemic subspecies. These studies are especially crucial for new ingredient regulatory cosmetic or pharmaceutical frameworks. Also, more in vivo studies are needed to confirm safety and efficacy for the in vitro results.

            From the perspective of supply, the sparse natural distribution of Iris pallida subsp. illyrica along the eastern Adriatic coast raises sustainability issues. As an endemic species, extensive wild harvesting could impact population sustainability without the development of cultivation and conservation frameworks. Additionally, issues related to consistency may arise from different forming extracts using various extraction techniques due to their in't chemical composition. The above underscores the need for more defined controlled practices, balancing governance frameworks, and more rigorous safety validation before progressive commercialization can be pursued. Accordingly, we have further clarified the research phases in section 2.2.1. Plant material collection (Lines 140-148).

 

Comment 16: Did you evaluate the stability of extracts or compounds post-extraction?

Response: In this study, we did not assess the stability of the extracts or individual compounds to post-extraction exposure. We focused on initial functional screening alongside chemical profiling. We do note, however, that stability will be a concern for any further development work, particularly with regard to commercial or cosmetic applications. Future work will focus on designing stability studies to measure the longevity and uniformity of bioactive compounds over time under various controlled storage conditions. All extracts were stored in dark glass vials in a refrigerator during the entire time of the experiment and no visible changes such as precipitation or discoloration were noted even though no formal stability analysis was performed.

 

 

 

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

Comments and Suggestions for Authors

The manuscript has been improved based on the feedback, and it is recommended for acceptance. However, the author is reminded to add the original data in the supplementary materials before publication.

Reviewer 3 Report

Comments and Suggestions for Authors

Thanks for your reply, now your article is better.

Reviewer 4 Report

Comments and Suggestions for Authors

The authors responded and made all requested modifications, therefore, the revised manuscript can be accepted for publication.