Review Reports

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

This manuscript compared meat quality, free amino acids (FAAs), free fatty acids (FFAs), and volatile organic compounds (VOCs) in longissimus thoracis muscle from three sheep genotypes: Cele Black sheep (CLH), Australian White × Hu crossbred sheep (AH), and Hotan sheep (BDT). The authors applied LCMS/MS, GCMSSPME, multivariate statistics, relative odor activity value (rOAV) and Spearman correlation to characterise breeddependent flavourrelated chemical variation. The dataset is valuable for understanding flavour chemistry of indigenous Chinese sheep breeds. The topic fits within the scope of Foods. However, there are several issues should be addressed.

Major Comments

1. The water-loss rate method is not specified or cited. If a pressure-based (filter-paper press) protocol was used, a reference should be provided, as variants differ in pressure, time, and filter paper and yield different values.
2. The subsection numbering in the Materials and Methods is incorrect. Please check and correct the numbering throughout.
3. Spearman correlation identified significant associations between Tyr, C20:3n-6, C22:4n-6 and multiple VOCs. Although the authors acknowledge these are covariation patterns rather than proof of conversion, some passages still imply a precursor–product relationship. The authors should state consistently across the Abstract, Results, and Discussion that these are co-variation patterns, potentially reflecting shared upstream metabolic or oxidative pathways, rather than evidence of direct conversion. In addition, they should briefly describe the experiments needed to verify true precursor–product links (e.g., model heating systems, stable-isotope labelling, aroma recombination/omission assays).
4. The manuscript reports headspace SPME equilibration/extraction at 60°C applied to raw muscle samples. At this temperature, partial thermal generation of artefactual VOCscannot be excluded, which may affect the interpretation of the raw-meat VOC profile. The authors should acknowledge this as a methodological limitation and, where possible, indicate whether control experiments were performed to assess the extent of thermally induced artefact formation.
5. All VOC measurements were performed on raw frozen muscle. Lamb flavour is largely generated upon thermal processing. Rawmeat VOC profiles do not directly represent cookedmeat aroma. Meanwhile, no descriptive sensory analysis was conducted to verify perceived tastearoma differences between breeds.
6. The caption for Figure 1 states that "different letters indicate significant differences among groups," but the panels use asterisks rather than letters to denote significance, and some panels (A, B, F) carry no significance markers at all. In addition, the caption does not explain what the asterisks denote or which groups are being compared. The caption should be revised to match the actual annotation system used in the figure, or the figure should be re-annotated with letters as described.
7. Remove duplicate references (7 and 9) and verify all citations.

Author Response

Response to Reviewer 1

Dear Reviewer,

Thank you for your thorough and constructive comments concerning our manuscript entitled “Comparative profiling of free amino acids, free fatty acids, and volatile organic compounds in the longissimus thoracis muscle of three sheep breed groups”. These comments are very valuable for improving the quality of our paper, and we have carefully studied each point and made corresponding revisions. Below we provide our point-by-point responses. All modifications in the manuscript have been highlighted in red.

Comment 1. The water-loss rate method is not specified or cited. If a pressure-based (filter-paper press) protocol was used, a reference should be provided, as variants differ in pressure, time, and filter paper and yield different values.

Response 1: Thank you for this valuable suggestion. We agree that providing a methodological reference and a detailed description of the experimental procedure is essential for ensuring reproducibility and comparability. In the present study, the water loss rate was determined using a modified filter-paper press-loss method rather than a conventional drip-loss method. In response to your comment, we have added a methodological reference for the filter-paper press-loss approach [14] and clarified the sample dimensions, number of filter-paper layers, applied load, compression duration, and calculation procedure. We have also defined W1 and W2 as the sample weights before and after compression, respectively. These revisions have been incorporated into Section 2.2 (Meat quality measurements) and provide a more complete and reproducible description of the experimental procedure. The specific revisions are highlighted in red in Section 2.2 (Meat quality measurements) of the Materials and Methods.

Comment 2. The subsection numbering in the Materials and Methods is incorrect. Please check and correct the numbering throughout.

Response 2: Thank you for identifying the inconsistency in the subsection numbering. We have carefully reviewed and corrected the numbering throughout the Materials and Methods section. Specifically, the section on free fatty acid determination has been renumbered from Section 2.5 to Section 2.4, the section on volatile organic compound analysis from Section 2.6 to Section 2.5, and the statistical analysis section from Section 2.7 to Section 2.6. The corresponding subsection numbers have also been updated. In addition, we have checked the section headings and cross-references throughout the manuscript to ensure consistency and clarity.

Comment 3. Spearman correlation identified significant associations between Tyr, C20:3n-6, C22:4n-6 and multiple VOCs. Although the authors acknowledge these are covariation patterns rather than proof of conversion, some passages still imply a precursor–product relationship. The authors should state consistently across the Abstract, Results, and Discussion that these are co-variation patterns, potentially reflecting shared upstream metabolic or oxidative pathways, rather than evidence of direct conversion. In addition, they should briefly describe the experiments needed to verify true precursor–product links (e.g., model heating systems, stable-isotope labelling, aroma recombination/omission assays).

Response 3: We sincerely appreciate this important and constructive comment. We fully agree that statistically significant correlations do not establish direct biochemical precursor–product relationships. Although the present study identified associations between Tyr, C20:3n-6, C22:4n-6, and several VOCs in the unadjusted analysis, these associations did not remain significant after FDR correction and should therefore be interpreted as exploratory co-variation patterns rather than evidence of direct conversion. Such associations may reflect shared upstream metabolic or oxidative pathways, or breed-related differences in chemical composition. In response to your suggestion, we have systematically revised the relevant statements in the Abstract, Results, Discussion, and Conclusions to ensure that the interpretation of these associations is consistent and appropriately cautious. The specific revisions are as follows:

Abstract: “Correlation analysis followed by false discovery rate (FDR) correction showed that only Ile and Lys were significantly negatively correlated with o-Xylene, whereas the associations of Tyr, C20:3n-6, and C22:4n-6 with VOCs were exploratory and did not remain significant. These co-variation patterns may reflect shared upstream metabolic or oxidative pathways rather than direct precursor–product conversion. These findings characterize breed-related differences in the flavor-associated chemical profiles of raw lamb muscle; however, their implications for cooked-meat aroma and perceived flavor require further validation through descriptive sensory analysis and cooked-meat VOC measurements.”.

Section 3.6: “Spearman correlation analysis was performed to investigate potential associations among free amino acids, free fatty acids, and key VOCs. To control for multiple testing, P values were adjusted using the false discovery rate (FDR) method, and only associations that remained significant after FDR correction were reported. After FDR correction, only Ile and Lys were significantly negatively correlated with o-Xylene (P < 0.05). The other correlations observed in the unadjusted analysis, including those between Tyr, C20:3n-6, C22:4n-6 and various VOCs, did not remain statistically significant after FDR correction and should therefore be regarded as exploratory findings.”.

Section 4.4: We further clarified that the associations remaining after FDR correction should be interpreted as statistical co-variation rather than evidence of direct precursor–product conversion. We also explicitly stated that Tyr, C20:3n-6, and C22:4n-6 should be regarded as candidate flavor-associated compounds that co-varied with VOC profiles in the unadjusted analyses, whereas Ile and Lys showed more robust statistical co-variation with o-xylene after FDR correction. Nevertheless, none of these associations establishes direct biochemical conversion.

Conclusions: “This study demonstrated that CLH, AH, and BDT exhibited generally similar basic meat quality characteristics but differed in meat color and the profiles of free amino acids, free fatty acids, and VOCs. CLH and BDT showed higher Glu and total UAA contents than AH, whereas CLH had the highest total SAA content. BDT also exhibited relatively high Cys and C18:0 contents, while AH showed higher levels of C20:3n-6 and C22:4n-6. The rOAV analysis and odor attribute annotation further suggested that breed-related aroma differences were mainly associated with specific potentially aroma-active VOCs. However, no sensory or commercial validation was conducted in this study. Therefore, these findings are limited to the observed chemical differences, and their sensory relevance and potential commercial application require further validation through descriptive sensory analysis, cooked-meat VOC analysis, and larger-scale evaluation.”.

Furthermore, we have expanded the Discussion to describe the experimental approaches required to establish potential precursor–product relationships. Specifically, controlled model heating systems and stable-isotope labeling could help determine whether individual amino acids or fatty acids are directly involved in the formation of specific VOCs. In contrast, GC–O and aroma recombination and omission experiments would be valuable for evaluating the sensory relevance of these compounds. These revisions clarify the distinction between statistical association and biochemical causation and strengthen the scientific interpretation of our findings. The specific revisions are highlighted in red in the manuscript.

Comment 4. The manuscript reports headspace SPME equilibration/extraction at 60°C applied to raw muscle samples. At this temperature, partial thermal generation of artefactual VOCs cannot be excluded, which may affect the interpretation of the raw-meat VOC profile. The authors should acknowledge this as a methodological limitation and, where possible, indicate whether control experiments were performed to assess the extent of thermally induced artefact formation.

Response 4: Thank you for highlighting this important methodological consideration. We agree that the elevated temperature used during HS-SPME analysis may influence the detected VOC profiles. Although the muscle samples were not subjected to a separate cooking treatment before analysis, equilibration and extraction at 60 °C may facilitate VOC release and potentially promote temperature-dependent chemical reactions, including lipid oxidation and the formation of additional volatile compounds. In response to your comment, we have clarified the HS-SPME conditions in Section 2.5.1 (Headspace solid-phase microextraction). The revised text is as follows: “Muscle samples were ground in liquid nitrogen and homogenized. Approximately 0.20 g of homogenized raw muscle was placed in a headspace vial containing 0.20 g of NaCl and 20 μL of 3-hexanone-2,2,4,4-d₄ internal standard solution (10 μg/mL in n-hexane). After equilibration at 60 °C for 5 min with agitation, headspace VOCs were extracted at 60 °C for 15 min using a 120 μm divinylbenzene/carbon wide range/polydimethylsiloxane (DVB/CWR/PDMS) fiber. No separate cooking treatment was applied to the muscle samples before HS-SPME analysis.” We have also added a discussion of this potential limitation in Section 4.3. The revised text is as follows: “HS-SPME was performed at 60 °C on uncooked muscle, and no extraction-temperature or time-course control experiments were conducted. Thermally induced artifacts (e.g., lipid oxidation) cannot therefore be excluded, and the detected VOCs should be interpreted as headspace compounds obtained under these analytical conditions rather than as the native volatile profile of raw muscle. Because no cooked samples or sensory evaluation were included, the annotated odor attributes do not directly establish the perceived aroma of cooked lamb; future studies should compare raw and cooked samples and integrate targeted quantification, GC–O, and sensory evaluation.” The specific revisions are highlighted in red in the manuscript.

Because the current study does not provide independent extraction-temperature or time-course control data, the extent of possible thermally induced artifact formation cannot be determined. Accordingly, we have revised the interpretation of the VOC results to emphasize that they represent headspace volatile profiles obtained under the specified analytical conditions rather than an unaltered representation of the native volatile composition of raw muscle. We believe that explicitly acknowledging this limitation provides a more accurate and balanced interpretation of the analytical results.

Comment 5. All VOC measurements were performed on raw frozen muscle. Lamb flavour is largely generated upon thermal processing. Raw meat VOC profiles do not directly represent cooked meat aroma. Meanwhile, no descriptive sensory analysis was conducted to verify perceived taste-aroma differences between breeds.

Response 5: We sincerely thank you for this insightful comment. We agree that the volatile composition of raw muscle does not directly represent the aroma of cooked lamb, as thermal processing substantially influences flavor formation through reactions such as the Maillard reaction, Strecker degradation, and lipid oxidation. We also acknowledge that no descriptive sensory evaluation was conducted in the present study. Therefore, the odor attributes assigned to individual VOCs were based on published compound descriptions and should be interpreted as potential sensory characteristics rather than experimentally verified differences in perceived flavor among breeds. In response to your suggestion, we have revised Section 3.5, Section 4.3, and the Conclusions to distinguish chemical profiling results from sensory interpretations. The specific revision in Section 3.5 is as follows:

Section 3.5: “It should be noted that odor attributes were assigned based on database and literature descriptions, and VOCs were measured in raw frozen muscle. Therefore, these results should be interpreted as potential odor characteristics under the specified analytical conditions rather than cooked-meat aroma or experimentally verified sensory perceptions. Their sensory relevance requires further validation through descriptive sensory analysis and cooked-meat VOC measurements.”.

In addition, the Abstract and Conclusions have been revised accordingly to clarify that VOCs were measured in raw frozen muscle and that their implications for cooked-meat aroma and perceived flavor require further validation. These revised texts are provided in Response 3 to avoid repetition.

We have also explicitly acknowledged the absence of cooked-meat VOC analysis and descriptive sensory evaluation as limitations of the present study. Furthermore, we have highlighted the need for future investigations combining standardized cooking treatments, quantitative VOC analysis, GC–O, and trained sensory evaluation to determine the actual contributions of the identified compounds to breed-related differences in lamb aroma. These revisions provide a more cautious and scientifically appropriate interpretation of the potential flavor implications of our findings. The specific revisions are highlighted in red in the manuscript.

Comment 6. The caption for Figure 1 states that "different letters indicate significant differences among groups," but the panels use asterisks rather than letters to denote significance, and some panels (A, B, F) carry no significance markers at all. In addition, the caption does not explain what the asterisks denote or which groups are being compared. The caption should be revised to match the actual annotation system used in the figure, or the figure should be re-annotated with letters as described.

Response 6: Thank you for carefully identifying the inconsistency between the significance annotations in Figure 1 and the corresponding figure caption. We agree that the caption should accurately describe the statistical annotation system used in the figure. Accordingly, we have revised the caption to clarify that horizontal brackets indicate pairwise comparisons between the connected groups and that asterisks represent different levels of statistical significance (P < 0.05 and P < 0.01). We have also clarified the interpretation of panels without significance markers. In addition, we have re-examined the statistical comparisons underlying Figure 1, particularly the water loss rate and redness results, and reconciled the significance annotations with the corresponding descriptions in Section 3.1. The specific revisions are highlighted in red in the manuscript.

Comment 7. Remove duplicate references (7 and 9) and verify all citations.

Response 7: Thank you for identifying the duplicate references and for recommending a comprehensive review of the citations. We have confirmed that the original References 7 and 9 refer to the same publication. Accordingly, we have removed the duplicate entry and updated the corresponding in-text citations and reference numbering. In addition, we have reviewed the reference list and checked the consistency of the bibliographic information and in-text citations throughout the manuscript. These revisions improve the accuracy and consistency of the references.

We sincerely appreciate the reviewer's thoughtful and constructive suggestions. The comments have helped us improve the clarity of the experimental methods, strengthen the interpretation of the results, explicitly acknowledge the methodological limitations, and enhance the overall consistency of the manuscript.

We hope that the revisions have adequately addressed your concerns and have improved the scientific quality of the manuscript.

Thank you again for your valuable time and consideration.

Sincerely,

Mingxuan Guan

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

This manuscript addresses a relevant topic and provides potentially valuable information on the meat quality and flavor-related compounds of different sheep breed groups. However, several methodological, statistical, and interpretative aspects should be clarified or strengthened before the manuscript can be considered for publication.

Comments

Section: Title

The title adequately reflects the variables analyzed; however, it does not indicate that this is a comparative experimental study. It is suggested that wording such as “comparative experimental study” be incorporated, or that the title specify that the study compares three sheep breed groups, to better define its scope.

Section: Abstract, Lines 11–27

The abstract does not report the number of animals used or provide relevant quantitative results. Please indicate that 18 animals were evaluated, with six animals per group, and include representative values, percentage differences, or significance values for the main findings.

Section: Abstract, Lines 20–25

Associations between non-volatile precursors and volatile compounds are presented; however, it is not clarified that these associations are correlational. It is recommended that the authors explicitly state that the results demonstrate statistical covariation rather than direct precursor–product relationships.

Section: Introduction, Lines 42–57

The general effect of breed is explained, but the scientific rationale for specifically selecting CLH, AH, and BDT is not sufficiently clear. Please provide a brief description of the productive, genetic, or commercial relevance of each breed group and explain why their comparison represents a novel contribution.

Section: Materials and Methods, Section 2.1, Lines 89–93

The manuscript only states that the animals were approximately one-year-old rams with similar body weights. Please provide the animals’ exact age or age range and describe their previous production or rearing system.

Section: Materials and Methods, Section 2.1

The manuscript indicates that feed and water were provided ad libitum; however, feed intake is not reported. Please provide these data to demonstrate that the nutritional conditions were comparable among the groups.

Section: Materials and Methods, Section 2.1, Lines 97–102

The expression “standardized procedure” does not provide sufficient information to reproduce the slaughter conditions. Please describe the stunning and slaughter methods, processing order, time elapsed before sampling, and carcass chilling conditions.

Section: Materials and Methods

Section 2.3 is followed directly by Section 2.5; Section 2.4 is missing. Please correct the numbering of the subsections.

Section: Materials and Methods, Section 2.2, Lines 103–106

Please include the ultimate pH, preferably measured 24 h postmortem, or justify why only the initial pH was evaluated. The calibration procedure for the equipment should also be described.

Section: Materials and Methods, Section 2.2

The manuscript does not report the oxygen exposure conditions, illuminant, standard observer, instrument aperture, or number of readings per sample. Please provide a complete description of the color measurement protocol and indicate whether the reported values represent the average of multiple technical measurements.

Section: Materials and Methods, Section 2.2, Lines 106–109

The cooking time, cooling procedure, sample dimensions, and number of replicates are not specified. Please report the sample dimensions, cutting speed, number of cores evaluated per animal, and the cooling procedure used before measurement.

Section: Materials and Methods, Sections 2.3.1 and 2.3.2

It is not explained whether the amino acids were quantified using calibration curves, and no analytical validation parameters are provided. Please report the internal and external standards, calibration ranges, linearity, recovery, precision, limit of detection, and limit of quantification.

Section: Materials and Methods, Section 2.3.2

The manuscript indicates that the MRM parameters were established using standards or optimized conditions; however, it does not identify which compounds were confirmed using authentic standards. Please provide a supplementary table containing the MRM transitions, retention times, standards used, and confirmation criteria for each analyte.

Section: Materials and Methods, Section 2.5

The internal standard is not identified, and the calibration curves and identification criteria are not described. Please provide the name and concentration of the internal standard, response factors, calibration ranges, recovery values, and analytical precision parameters.

Section: Materials and Methods, Section 2.6.3, Lines 186–193

The equations used to calculate relative concentrations and relative odor activity values (rOAVs) appear incomplete or are not clearly formatted, and the variables are not defined. Please correct the equations and define each symbol, unit, conversion factor, volume, sample mass, and ion intensity used in the calculations.

Section: Results, Sections 3.2–3.4

The supervised models were developed using only six animals per group and show group separation even though the PCA did not reveal clear natural clustering. Please provide complete model-validation metrics and consider additional validation methods to reduce the risk of overfitting.

Section: Results, Section 3.4, Lines 323–327

PLS-DA and OPLS-DA are used interchangeably without explaining why different models were selected for the comparisons. Please justify the use of each model and apply a consistent statistical strategy, or clearly explain the specific research question addressed by each analysis.

Section: Results, Section 3.4

The manuscript states that 201 volatile organic compounds (VOCs) were identified; however, the supplementary material does not include a complete table reporting their identities and abundances. Please add a supplementary table containing the compound name, CAS number, retention time and retention index, identification ions, identification confidence level, abundance in each group, and statistical results.

Section: Results 3.6 and Discussion 4.4

Numerous correlation analyses were performed without reporting a correction for multiple testing. Please apply a false discovery rate (FDR) adjustment and display only the associations that remain statistically significant after correction.

Section: Discussion

AH is a crossbred group, whereas CLH and BDT are local breeds; however, this genetic difference is not discussed in sufficient depth. Please discuss how heterosis, genetic composition, and selection for productive traits in the crossbred group may have influenced muscle metabolism and the compounds evaluated.

Section: Conclusions, Lines 541–552

The conclusions state that the findings support breed differentiation and their quality-oriented utilization; however, no sensory or commercial validation was conducted. The conclusions should be limited to the observed chemical differences, and the authors should acknowledge that their sensory relevance and commercial application require further validation.

Section: References

References 7 and 9 apparently correspond to the same article. Please remove the duplicate reference, renumber the reference list, and verify that all in-text citations correspond correctly to the final reference list.

 

Comments on the Quality of English Language

The paper is generally understandable; however, the English language should be carefully revised to improve grammar, sentence structure, scientific terminology, and overall readability. Professional English-language editing by a native speaker or a qualified scientific editor is recommended.

Author Response

Response to Reviewer 2

Dear Reviewer,

We sincerely thank you for your careful evaluation of our manuscript entitled “Comparative profiling of free amino acids, free fatty acids, and volatile organic compounds in the longissimus thoracis muscle of three sheep breed groups” Your comments have helped us identify important aspects of the study that require clarification, particularly experimental reproducibility, analytical validation, statistical robustness, and the interpretation of flavor-related findings. We have carefully considered each comment and provide our point-by-point responses below. Changes made specifically in response to Reviewer 2 are highlighted in blue in the revised manuscript, whereas changes that also address comments raised by Reviewer 1 are highlighted in red.

Comment 1. The title adequately reflects the variables analyzed; however, it does not indicate that this is a comparative experimental study. It is suggested that wording such as “comparative experimental study” be incorporated, or that the title specify that the study compares three sheep breed groups, to better define its scope.

Response 1: Thank you for this helpful suggestion. We agree that explicitly specifying the number of breed groups would better define the scope of the study. We have revised the title to “Comparative profiling of free amino acids, free fatty acids, and volatile organic compounds in the longissimus thoracis muscle of three sheep breed groups” We prefer the term “comparative” rather than “comparative experimental” because breed-group membership was not experimentally assigned. This wording more accurately reflects the design and avoids implying a randomized genetic intervention. The revised title is highlighted in blue in the revised manuscript.

Comment 2. Abstract, Lines 11–27. The abstract does not report the number of animals used or provide relevant quantitative results. Please indicate that 18 animals were evaluated, with six animals per group, and include representative values, percentage differences, or significance values for the main findings.

Response 2: Thank you for this valuable comment. We agree that the Abstract should report the number of animals and representative quantitative results. We have revised the Abstract accordingly. The number of animals (eighteen yearling rams, six per group) is now stated, and representative values with significance levels are included for the main findings. Redundant statements on correlation analysis were removed, and the consolidated co-variation statement was retained. The relevant revised portion of the Abstract is shown below: “This study investigated breed-related differences in the flavor chemistry of the longissimus thoracis muscle from Cele Black sheep (CLH), Australian White × Hu crossbred sheep (AH), and Hotan sheep (BDT). Eighteen yearling rams (six animals per group) were evaluated. Free amino acids (FAAs) were quantified by LC–MS/MS, and free fatty acids (FFAs) and volatile organic compounds (VOCs) were analyzed by GC–MS, followed by multivariate analysis, relative odor activity value (rOAV) analysis, and correlation analysis. Muscle samples from the three breeds showed comparable pH, lightness, and shear force values, whereas BDT exhibited higher redness and yellowness values. Breed-related differences were mainly observed in specific flavor-related compounds. Glutamic acid was higher in CLH (27.77 μg/g) and BDT (27.11 μg/g) than in AH (21.21 μg/g; P < 0.05). Stearic acid (C18:0) was higher in BDT (63.72 μg/g) than in CLH (41.10 μg/g) and AH (36.37 μg/g; P < 0.01). Docosatetraenoic acid (C22:4n-6) was higher in AH (9.33 μg/g) than in CLH (7.31 μg/g) and BDT (7.29 μg/g; P < 0.01). A total of 201 VOCs were annotated in raw-muscle headspace. ”.The revised Abstract is highlighted in blue in the revised manuscript.

Comment 3. Abstract, Lines 20–25. Associations between non-volatile precursors and volatile compounds are presented; however, it is not clarified that these associations are correlational. It is recommended that the authors explicitly state that the results demonstrate statistical covariation rather than direct precursor–product relationships.

Response 3: We sincerely thank the reviewer for this important comment. We fully agree that the Abstract should explicitly clarify that the observed associations are correlational rather than evidence of direct precursor–product conversion. This point is also consistent with a related concern raised by Reviewer 1, and we have revised the Abstract, Results, Discussion, and Conclusions to ensure consistent and appropriately cautious wording. The revised Abstract states: “Correlation analysis followed by false discovery rate (FDR) correction showed that only Ile and Lys were significantly negatively correlated with o-xylene, whereas the associations of Tyr, C20:3n-6, and C22:4n-6 with VOCs were exploratory and did not remain significant. These co-variation patterns may reflect shared upstream metabolic or oxidative pathways rather than direct precursor–product conversion.” To further clarify how true precursor–product relationships could be established, we also added the following statement to the Discussion: “To verify true precursor–product relationships, future studies should employ controlled model heating systems combined with stable-isotope labelling to trace the formation of specific VOCs from defined precursors. In parallel, GC–O and aroma recombination/omission experiments would be valuable for evaluating the sensory relevance of the identified VOCs.”. These changes are highlighted in red in the revised manuscript (because this comment is shared with Reviewer 1).

Comment 4. Introduction, Lines 42–57. The general effect of breed is explained, but the scientific rationale for specifically selecting CLH, AH, and BDT is not sufficiently clear. Please provide a brief description of the productive, genetic, or commercial relevance of each breed group and explain why their comparison represents a novel contribution.

Response 4: We sincerely thank the reviewer for this helpful comment. We agree that the rationale for selecting CLH, AH, and BDT needed to be clarified. We have revised the Introduction to describe the genetic, production, and commercial relevance of the three groups. CLH and BDT are now described as indigenous sheep genetic resources adapted to local environments and important for local lamb production and genetic diversity, whereas AH is described as a commercially relevant crossbred group combining the growth and carcass characteristics of Australian White sheep with the reproductive and adaptive traits of Hu sheep. We also clarified that integrated comparisons of FAAs, FFAs, headspace VOCs, and rOAVs among these three groups remain limited, which represents the novel contribution of this study. The specific revised text is as follows:”However, systematic comparisons of flavor-related chemical profiles among indigenous sheep breeds and crossbreds remain relatively limited, especially when FAAs, FFAs, and headspace VOCs are integrated. The three breed groups compared here were selected because of their distinct genetic and production backgrounds. Cele Black sheep (CLH) and Hotan sheep (BDT) are indigenous sheep genetic resources in China that are adapted to local environments and contribute to local lamb production and genetic diversity. In contrast, Australian White × Hu crossbred sheep (AH) represent a crossbred group that combines the growth and carcass characteristics of Australian White sheep with the reproductive and adaptive traits of Hu sheep, and is therefore of commercial interest for lamb production. Comparing these groups under a common feeding and management regimen provides a comparable basis for evaluating breed-related differences in flavor-related chemical profiles. To our knowledge, integrated comparisons of FAAs, FFAs, headspace VOCs, and relative odor activity values (rOAVs) among CLH, AH, and BDT remain limited. The present study therefore aimed to characterize their flavor-related chemical differences and to provide information relevant to the quality-oriented utilization of indigenous and crossbred sheep resources.”. The revised text is highlighted in blue in the revised manuscript.

Comment 5. Materials and Methods, Section 2.1, Lines 89–93. The manuscript only states that the animals were approximately one-year-old rams with similar body weights. Please provide the animals’ exact age or age range and describe their previous production or rearing system.

Response 5: Thank you for this helpful comment. We have revised Section 2.1 to provide the exact age of the animals and to describe their previous rearing system. The animals were 12.0 ± 0.5 months of age at the start of the trial. In addition, we have clarified that before the 52-day trial, all animals were reared under the same conventional indoor feeding and management system at the same farm, with ad libitum access to water, and no breed-specific differences in feeding or management were applied. The specific revised text is as follows:“A total of 18 healthy rams (12.0 ± 0.5 months of age) were used, comprising six CLH (38.55 ± 1.73 kg), six AH (39.08 ± 2.11 kg), and six BDT (38.19 ± 1.92 kg) sheep. Before the 52-day trial, all animals were reared under the same conventional indoor feeding and management system at the same farm, with ad libitum access to water, and no breed-specific differences in feeding or management were applied. During the 52-day trial, including a 7-day adaptation period and a 45-day experimental period, all animals were raised under identical environmental and management conditions at Xinjiang Jinken Aokun Agricultural and Animal Husbandry Technology Co., Ltd. (Xinjiang, China). ”.The revised text is highlighted in blue in Section 2.1 of the revised manuscript.

Comment 6. Materials and Methods, Section 2.1. The manuscript indicates that feed and water were provided ad libitum; however, feed intake is not reported. Please provide these data to demonstrate that the nutritional conditions were comparable among the groups.

Response 6: Thank you for this helpful comment. We agree that feed intake data are important for demonstrating comparable nutritional conditions among groups. We have therefore added feed intake data to Section 2.1. Feed offered and refusals were recorded daily during the 45-day experimental period, and average daily feed intake (ADFI) was calculated on a dry matter basis. The ADFI was comparable among the three groups (CLH: 1.60 ± 0.12 kg/d; AH: 1.77±0.36 kg/d; BDT: 1.81±0.55 kg/d). These data indicate that the three groups were maintained under comparable nutritional conditions. The revised text has been highlighted in blue in the manuscript.

Comment 7. Materials and Methods, Section 2.1, Lines 97–102. The expression “standardized procedure” does not provide sufficient information to reproduce the slaughter conditions. Please describe the stunning and slaughter methods, processing order, time elapsed before sampling, and carcass chilling conditions.

Response 7: Thank you for this helpful comment. We agree that the slaughter and sampling procedures should be described in sufficient detail for reproducibility. We have therefore revised Section 2.1 to specify the stunning and slaughter methods, processing order, time elapsed before sampling, and carcass chilling conditions. The revised text is as follows: “At the end of the feeding trial, all animals were fasted for 12 h and deprived of water for 2 h before slaughter. Animals were stunned by electrical stunning and immediately slaughtered by exsanguination via severing the carotid arteries and jugular veins. Slaughter was performed in a randomized order across the three breed groups to minimize batch effects. After exsanguination, carcasses were immediately transferred to a chilling room at 4 °C. Within 30 min postmortem and before complete chilling, longissimus thoracis samples were collected between the 11th and 12th thoracic vertebrae.” The revised text is highlighted in blue in the revised manuscript.

Comment 8. Materials and Methods. Section 2.3 is followed directly by Section 2.5; Section 2.4 is missing. Please correct the numbering of the subsections.

Response 8: We thank the reviewer for identifying this numbering error, which is consistent with a similar comment raised by Reviewer 1 (Comment 2). We apologize for this oversight. We have carefully checked and corrected all subsection numbers in the Materials and Methods. Specifically, the free fatty acid determination section, previously numbered Section 2.5, has been renumbered as Section 2.4, so that Section 2.3 is now followed directly by Section 2.4. Accordingly, the volatile organic compound analysis section has been renumbered as Section 2.5, and the statistical analysis section as Section 2.6. All corresponding subsection headings and cross-references have also been updated to ensure continuous and consistent numbering throughout the manuscript. These revisions are highlighted in red in the revised manuscript (because this comment is shared with Reviewer 1).

Comment 9. Materials and Methods, Section 2.2, Lines 103–106. Please include the ultimate pH, preferably measured 24 h postmortem, or justify why only the initial pH was evaluated. The calibration procedure for the equipment should also be described.

Response 9: We sincerely thank the reviewer for this valuable comment. We agree that ultimate pH measured at approximately 24 h postmortem is an important indicator of postmortem acidification. In the original experimental design, however, only pH at 45 min postmortem was measured, and ultimate pH at 24 h postmortem was not determined. Following the early postmortem measurements, the samples entered the predefined freezing and storage procedure, and no continuously chilled, unfrozen muscle samples were retained for pH measurement at 24 h postmortem. Therefore, measuring pH after subsequent freezing and thawing would not have been equivalent to determining ultimate pH in fresh/chilled muscle at 24 h postmortem. We have therefore retained the pH value measured at 45 min postmortem and now explicitly refer to it as early postmortem pH (pH45) rather than ultimate pH. We have also acknowledged the absence of pH24 data as a limitation of the present study.

In addition, the calibration procedure for the pH meter has been added to Section 2.2. The pH meter was calibrated before each measurement session using standard buffer solutions of pH 4.00, 6.86, and 9.18 at room temperature, with automatic temperature compensation. The electrode was rinsed with deionized water and blotted dry between measurements. These revisions have been incorporated into Section 2.2 (Meat quality measurements) of the revised manuscript and are highlighted in blue.

Comment 10. Materials and Methods, Section 2.2. The manuscript does not report the oxygen exposure conditions, illuminant, standard observer, instrument aperture, or number of readings per sample. Please provide a complete description of the color measurement protocol and indicate whether the reported values represent the average of multiple technical measurements.

Response 10: We sincerely thank the reviewer for this valuable comment. We agree that a complete description of the color measurement protocol is necessary for reproducibility. We have therefore revised Section 2.2 to include the oxygen exposure conditions, illuminant, standard observer, instrument aperture, and number of readings per sample. Specifically, the colorimeter was calibrated using the supplied white reference plates according to the manufacturer’s instructions before each measurement session. Color measurements were performed on freshly cut muscle surfaces that were exposed to ambient air, and excess surface moisture was gently blotted with filter paper before measurement. The instrument was set to the CIE L*a*b color space with a D65 illuminant, an 8°/d measurement geometry, a Φ4-mm measuring aperture, and a 10° standard observer. For each sample, three read-ings were taken at different locations on the muscle surface, and the average L*, a*, and b* values were reported. These revisions have been highlighted in blue in the revised manuscript.

Comment 11. Materials and Methods, Section 2.2, Lines 106–109. The cooking time, cooling procedure, sample dimensions, and number of replicates are not specified. Please report the sample dimensions, cutting speed, number of cores evaluated per animal, and the cooling procedure used before measurement.

Response 11: We sincerely thank the reviewer for this valuable and constructive comment. We agree that a complete description of the cooking and shear force measurement protocol is essential for reproducibility. We have therefore revised Section 2.2 to include the sample dimensions, cooking time and holding condition, cooling procedure before measurement, core dimensions, number of cores evaluated per animal, and the cutting speed. The revised text is as follows:“Fresh longissimus thoracis muscle samples (approximately 6 cm × 4 cm × 3 cm) were heated in an 80 °C water bath until the internal temperature reached 70 °C and held at 70 °C for 0 min (i.e., removed immediately upon reaching 70 °C). After cooking, the samples were cooled at room temperature for approximately 30 min and then refrigerated at 4 °C overnight (approximately 14 h) before measurement. Cylindrical cores (diameter: 1.3 cm, length: approximately 1.5 cm) were then removed parallel to the muscle fiber direction to obtain standardized samples. A minimum of 6 cores were evaluated per animal, and the average value was used for statistical analysis. Shear force was measured using a C-LM3B digital meat tenderness meter (Tenovo, China) at a cutting speed of 5 mm/s.”. These revisions have been highlighted in red in the revised manuscript. We believe this added detail substantially improves the reproducibility of the shear force measurement.

Comment 12. Materials and Methods, Sections 2.3.1 and 2.3.2. It is not explained whether the amino acids were quantified using calibration curves, and no analytical validation parameters are provided. Please report the internal and external standards, calibration ranges, linearity, recovery, precision, limit of detection, and limit of quantification.

Response 12: We sincerely thank the reviewer for this important comment. We agree that the quantification and analytical validation should be described more clearly. We have therefore added a new subsection 2.3.3. Quantification and analytical validation to the Materials and Methods. The revised text is as follows:“Amino acids and related metabolites were identified using authentic standards (purity > 99%) and quantified using calibration curves. Calibration standards were prepared at 1–20000 ng/mL. Calibration curves were constructed by plotting the peak area ratio of each analyte to the internal standard against the concentration ratio of the external standard to the internal standard. The internal standard was added at 1 μg/mL. The LLOQ and ULOQ corresponded to the lowest and highest calibration concentrations (1 and 20000 ng/mL, respectively). QC samples were injected every 10 samples, and more than 80% of metabolites had CV < 0.3. These revisions have been highlighted in blue in the revised manuscript.

Comment 13. Materials and Methods, Section 2.3.2. The manuscript indicates that the MRM parameters were established using standards or optimized conditions; however, it does not identify which compounds were confirmed using authentic standards. Please provide a supplementary table containing the MRM transitions, retention times, standards used, and confirmation criteria for each analyte.

Response 13: We sincerely thank the reviewer for this important suggestion. We agree that compound-specific MRM information and identification evidence are necessary to improve the transparency and reproducibility of the LC–MS/MS analysis. We therefore re-examined the original analytical records and prepared a new Supplementary Table S3 containing the precursor-to-product MRM transitions, ionization modes, ion species, and retention times for all targeted amino acids and related metabolites. All target compounds were identified using authentic standards (purity > 99%) by matching retention times and MRM transitions. Confirmation criteria included a retention time deviation within ±0.1 min and the presence of two MRM transitions (quantifier and qualifier) with ion ratios within ±20% of those of the authentic standards. The MRM transitions and retention times were cross-checked among the original analytical data files to ensure consistency. These revisions are highlighted in blue in the revised manuscript.

Comment 14. Materials and Methods, Section 2.5. The internal standard is not identified, and the calibration curves and identification criteria are not described. Please provide the name and concentration of the internal standard, response factors, calibration ranges, recovery values, and analytical precision parameters.

Response 14: We sincerely thank the reviewer for this valuable comment. We have revised Section 2.4 to provide the missing information. The specific revisions are as follows:“

1. 1. Internal standards: Five isotope-labeled internal standards were used: C8:0-d15 (2 μg/mL), C11:0-d21 (2 μg/mL), C17:0-d33 (2 μg/mL), 13C18:2n6c (5 μg/mL), and C22:0-d43 (5 μg/mL). The names and concentrations are now stated in Section 2.4.1.”.
2. 2. Identification criteria: Free fatty acids were identified in SIM mode using one quantitative ion and two to three qualitative ions per compound. Identification was based on matching retention times and ion abundance ratios with reference standards. This is now described in Section 2.4.2.
3. 3. Free fatty acids were quantified using calibration curves. Calibration standards were prepared at 0.004, 0.01, 0.02, 0.04, 0.1, 0.2, 0.4, 1, 2, 4, 10, 15, and 20 μg/mL, each containing the same isotope-labeled internal standards as the samples. Calibration curves were constructed by plotting the peak area ratio of each analyte to the internal standard against the concentration ratio of the external standard to the internal standard. The LLOQ and ULOQ corresponded to the lowest and highest calibration concentrations (0.004 and 20 μg/mL, respectively), within which accurate quantification was achieved. Sample concentrations were calculated as: content (μg/g) = c × v3 × v1 / v2 / m / 1000, where c is the concentration obtained from the calibration curve (μg/mL), v1 is the extraction volume (μL), v2 is the supernatant volume collected (μL), v3 is the redissolution volume (μL), and m is the sample weight (g). Quality control (QC) samples were prepared from a pooled mixture and injected every 10 samples. The QC CV distribution showed that more than 80% of metabolites had CV < 0.3, indicating acceptable analytical stability.The quantification formula is now provided in Section 2.4.3.These revisions have been highlighted in blue in the revised manuscript.

Comment 15. Materials and Methods, Section 2.6.3, Lines 186–193. The equations used to calculate relative concentrations and relative odor activity values (rOAVs) appear incomplete or are not clearly formatted, and the variables are not defined. Please correct the equations and define each symbol, unit, conversion factor, volume, sample mass, and ion intensity used in the calculations.

Response 15: We sincerely thank the reviewer for this valuable comment. We agree that the equations and variable definitions required clarification. We have carefully revised Section 2.5.3 (formerly Section 2.6.3) to present the equations in a clearer format and to define all symbols, units, conversion factors, volumes, sample masses, and ion intensities used in the calculations.

The revised equations and definitions are now as follows:

Analytical precision was assessed using quality control (QC) samples prepared from a pooled mixture and injected every 10 samples. The CV distribution showed that more than 85% of metabolites had CV < 0.5 and more than 75% had CV < 0.3, indicating acceptable analytical stability.

VOCs were semiquantified using the internal standard method [15], as absolute calibration curves were not established for all compounds. The relative concentration of each compound was calculated as follows:

 

Where  is the relative concentration of compound (μg/g),  is the volume of internal standard added (20 μL),  is the concentration of the internal standard (10 μg/mL),  is the sample weight (g),  is the peak area of compound , and  is the peak area of the internal standard.

For the rOAV:

 

Where  is relative odor activity value of compound (dimensionless),  is relative concentration of compound (μg/g),  is odor threshold of compound  in the corresponding matrix (μg/g)[16]. Compounds with were considered potential contributors to the overall aroma.

These revisions have been highlighted in blue in the revised manuscript. We believe the equations and variable definitions are now complete, clearly formatted, and reproducible.

Comment 16. Results, Sections 3.2–3.4. The supervised models were developed using only six animals per group and show group separation even though the PCA did not reveal clear natural clustering. Please provide complete model-validation metrics and consider additional validation methods to reduce the risk of overfitting.

Response 16: Thank you for this important comment. We agree that the limited biological sample size (n = 6 per group), together with the absence of clear natural clustering in the PCA analyses, requires cautious interpretation of the supervised multivariate models.

In response to this concern, we have expanded the model-validation information in Sections 3.2–3.4 by reporting R²X, R²Y, Q², and the results of 200-permutation tests for the supervised models. More importantly, we revised the interpretation of each model according to its validation performance rather than relying on the visual separation observed in the supervised score plots. Models that were not supported by permutation validation are no longer described as providing reliable discrimination and are instead presented as exploratory patterns.

For the free amino acid data, the OPLS-DA model yielded R²X = 0.276, R²Y = 0.890, and Q² = 0.592, and the 200-permutation test provided support for the supervised separation (P < 0.05). Nevertheless, because the PCA did not show clear natural clustering and the biological sample size was limited, this supervised pattern was interpreted as exploratory rather than as evidence of definitive breed classification. For the free fatty acid data, the OPLS-DA model yielded R²X = 0.546, R²Y = 0.828, and Q² = 0.393. In the 200-permutation test, the permutation P value for Q² was 0.020 (4/200), whereas that for R²Y was 0.165 (33/200) (Figure 3D). Because the validation results were mixed and the sample size was limited, this model is interpreted conservatively as exploratory rather than as evidence of robust breed classification. The three pairwise VOC models showed markedly different validation performances. For AH vs BDT, the model yielded R²X = 0.705, R²Y = 0.515, and Q² = 0.130, and the permutation test was not significant (P > 0.05); therefore, the apparent supervised separation was not considered adequately supported by permutation validation. In contrast, the AH vs CLH model yielded R²X = 0.683, R²Y = 0.830, and Q² = 0.511, with a significant permutation test (P < 0.05), providing comparatively stronger support for this supervised separation. For BDT vs CLH, R²X = 0.861, R²Y = 0.992, and Q² = 0.455; however, the permutation test was not significant (P > 0.05). Overall, only the AH vs CLH VOC comparison met the permutation-validation criterion used in this study, whereas the AH vs BDT and BDT vs CLH models were retained only as exploratory analyses.

We also considered the need for additional validation. Because no independent cohort was available in the present study, external validation could not be performed. Moreover, with only six biological samples per group, further partitioning the dataset into separate training and test sets would substantially reduce the sample size available for model development and evaluation. We have therefore avoided claims regarding predictive classification or model generalizability and explicitly acknowledge that independent validation in a larger cohort will be required to establish the reproducibility of these supervised patterns.

Accordingly, the relevant descriptions in Sections 3.2–3.4 have been revised to distinguish models supported by permutation validation from those that were not, and statements implying robust breed discrimination have been removed or moderated where appropriate. The corresponding changes are highlighted in blue in the revised manuscript.

Comment 17. Results, Section 3.4, Lines 323–327. PLS-DA and OPLS-DA are used interchangeably without explaining why different models were selected for the comparisons. Please justify the use of each model and apply a consistent statistical strategy, or clearly explain the specific research question addressed by each analysis.

Response 17: Thank you for identifying this inconsistency. We agree that the original manuscript did not provide a sufficient rationale for the concurrent use of PLS-DA and OPLS-DA in the VOC analysis. Because both approaches are supervised methods and were used to address largely overlapping questions regarding breed-group separation, their parallel use was unnecessary and could lead to ambiguity in the interpretation of the results.

To address this concern, we have revised the multivariate analysis to apply a consistent statistical strategy across the manuscript. PCA was retained as the unsupervised approach for evaluating the overall structure and natural variation of the chemical profiles without using class information. OPLS-DA was used consistently as the supervised approach for the predefined pairwise breed comparisons. This strategy is also consistent with the analyses of the free amino acid and fatty acid datasets in Sections 3.2 and 3.3. OPLS-DA was selected to facilitate interpretation by separating class-related predictive variation from variation in the X matrix that is orthogonal to class membership. Importantly, its use was not intended to provide independent confirmation of the PCA results or to imply robust breed classification. Accordingly, we evaluated each pairwise OPLS-DA model using R²X, R²Y, Q², and 200-permutation testing and interpreted the results according to their respective validation performance. Specifically, the AH vs CLH model showed comparatively stronger support (R²X = 0.683, R²Y = 0.830, Q² = 0.511, permutation P < 0.05), whereas the AH vs BDT and BDT vs CLH models were not supported by significant permutation tests (P > 0.05). Therefore, the supervised VOC analyses are now presented as exploratory assessments of potential breed-related variation rather than evidence of robust classification. The PLS-DA results have consequently been removed from Section 3.4, and the corresponding text, figures, figure captions, and supplementary materials have been revised to ensure consistency between the analytical strategy and its interpretation.

Comment 18. Results, Section 3.4. The manuscript states that 201 volatile organic compounds (VOCs) were identified; however, the supplementary material does not include a complete table reporting their identities and abundances. Please add a supplementary table containing the compound name, CAS number, retention time and retention index, identification ions, identification confidence level, abundance in each group, and statistical results.

Response 18: Thank you for this helpful suggestion. In response to the reviewer’s comment, we have added Supplementary Table S4, entitled “Identification, abundance, and statistical summary of 201 VOCs,” to provide a transparent record of all 201 VOCs annotated in this study. The table reports the compound name, CAS number, chemical class, retention time, retention index where available, diagnostic/identification ions, identification confidence level, group-specific relative abundance, and statistical results. For compounds lacking an experimentally determined retention index or authentic-standard confirmation, the corresponding identification information is reported according to the level of evidence available rather than being presented as unequivocally confirmed. These additions provide a more complete and traceable summary of VOC identification, abundance, and statistical characteristics.

Comment 19. Results 3.6 and Discussion 4.4. Numerous correlation analyses were performed without reporting a correction for multiple testing. Please apply a false discovery rate (FDR) adjustment and display only the associations that remain statistically significant after correction.

Response 19: We sincerely thank the reviewer for this important comment. We fully agree that correction for multiple testing is necessary when numerous correlation analyses are performed. In the revised analysis, all 1,296 predefined Spearman tests (48 non-volatile compounds × 27 VOCs) were included in a single Benjamini–Hochberg false discovery rate (FDR) correction. We report the FDR-adjusted P values (P values) and retain only associations with P < 0.05 as statistically significant.

After FDR correction, only Ile and Lys remained significantly negatively correlated with o-xylene (P < 0.05). The other correlations observed in the unadjusted analysis, including those between Tyr, C20:3n-6, C22:4n-6, and various VOCs, did not remain statistically significant after FDR correction. Therefore, these non-significant associations were removed from the main set of statistically significant results and are discussed only as exploratory co-variation patterns.

The revised Results 3.6 now reads: “Spearman correlation analysis was performed to investigate potential associations among FAAs, FFAs, and key VOCs. To control for multiple testing, all predefined correlation tests were adjusted using the Benjamini–Hochberg false discovery rate (FDR) procedure, and only associations with P < 0.05 were considered statistically significant. After FDR correction, only Ile and Lys were significantly negatively correlated with o-xylene. The other correlations observed in the unadjusted analysis, including those between Tyr, C20:3n-6, C22:4n-6, and various VOCs, did not remain statistically significant after FDR correction and should therefore be regarded as exploratory findings. These results indicate that Ile and Lys showed the most robust statistical co-variation with o-xylene among the non-volatile compounds analyzed, although the underlying mechanisms require further investigation.”

The revised Discussion 4.4 now emphasizes that the FDR-retained associations represent statistical co-variation rather than direct biochemical conversion. It states that only Ile and Lys remained significantly negatively correlated with o-xylene after FDR correction, whereas the unadjusted associations involving Tyr, C20:3n-6, and C22:4n-6 are exploratory. The Discussion further notes that these patterns may reflect shared upstream metabolic or oxidative pathways and that direct precursor–product relationships cannot be established from correlation analysis alone.

We have also updated the Abstract and Conclusions to be consistent with these FDR-corrected results. The overlapping revisions are highlighted in red in the revised manuscript because this issue is also related to Reviewer 1’s comment on the interpretation of correlation results.

Comment 20. Discussion. AH is a crossbred group, whereas CLH and BDT are local breeds; however, this genetic difference is not discussed in sufficient depth. Please discuss how heterosis, genetic composition, and selection for productive traits in the crossbred group may have influenced muscle metabolism and the compounds evaluated.

Response 20: We sincerely thank the reviewer for this important comment. We agree that the genetic background of the three breed groups should be discussed more explicitly. We have therefore added a paragraph at the end of Discussion 4.2 to address this point. The revised text is as follows: “The three breed groups also differed in genetic background: CLH and BDT are local breeds that may possess unique metabolic characteristics, whereas AH is a crossbred group that may exhibit heterosis. This distinction is important because the phenotype of a crossbred population may reflect not only the additive genetic contributions of the parental breeds but also heterosis and complementary effects between parental genetic backgrounds. Studies of crossbred sheep populations have revealed differences in muscle growth, lipid metabolism, and metabolite profiles, with transcriptomic and metabolomic alterations involving fatty acid and lipid metabolic pathways, PPAR signaling, AMPK signaling, and glycerophospholipid metabolism[33]. However, as no genetic, transcriptomic, or enzymatic analyses were performed in this study, these interpretations remain speculative and warrant further investigation using transcriptomic, genomic, or metabolic flux analyses.”. These revisions have been highlighted in blue in the revised manuscript. We believe this addition provides a more balanced discussion of the potential genetic and metabolic factors underlying the observed breed-related differences.

Comment 21. Conclusions, Lines 541–552. The conclusions state that the findings support breed differentiation and their quality-oriented utilization; however, no sensory or commercial validation was conducted. The conclusions should be limited to the observed chemical differences, and the authors should acknowledge that their sensory relevance and commercial application require further validation.

Response 21: We sincerely thank the reviewer for this important comment. We fully agree that the conclusions should be limited to the observed chemical differences and should not imply that sensory or commercial validation was performed. We have therefore revised the Conclusions to remove the implication that the findings directly support breed differentiation or quality-oriented utilization. The revised Conclusions now focus on the chemical differences observed among breeds and explicitly acknowledge the lack of sensory and commercial validation. The revised text is as follows: “However, no sensory or commercial validation was conducted in this study. Therefore, these findings are limited to the observed chemical differences, and their sensory relevance and potential commercial application require further validation through descriptive sensory analysis, cooked-meat VOC analysis, and larger-scale evaluation.”. These revisions have been highlighted in blue in the revised manuscript.

Comment 22. References: References 7 and 9 apparently correspond to the same article. Please remove the duplicate reference, renumber the reference list, and verify that all in-text citations correspond correctly to the final reference list.

Response 22: We sincerely thank the reviewer for identifying this issue, which is consistent with a similar comment raised by Reviewer 1 (Comment 7). We have confirmed that the original References 7 and 9 refer to the same publication. Accordingly, we have removed the duplicate entry and renumbered the entire reference list. In addition, we have carefully checked all in-text citations to ensure that they correspond correctly to the final reference list. The bibliographic information and citation numbering have been verified throughout the manuscript. These revisions improve the accuracy and consistency of the references and have been highlighted in red in the revised manuscript (because this comment is shared with Reviewer 1).

We sincerely appreciate the reviewer’s detailed and constructive recommendations. In response, we have revised the manuscript to improve methodological transparency, analytical traceability, statistical rigor, and the accuracy of the interpretation and conclusions. We believe that these revisions have substantially strengthened the manuscript, and we thank the reviewer again for helping us improve the work.

Sincerely,

The Authors

Mingxuan Guan

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

Comments and Suggestions for Authors

The authors responded to each of the comments provided and improved the manuscript, indicating the changes in the document by highlighting them in a different color. These changes significantly improved the manuscript.