Wheat-Surface Microbiota as a Key Driver of Daqu Quality: Evidence from Microbial Diversity and Volatile Flavor Analysis

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The manuscript is interesting but some aspect should be improved:

• Abstract should be rewritten to clearly indicate the novelty of the research.
• Introduction should be improved, strongly indicate the importance of the research
• section 3.3. „Higher Nm = greater dispersal” - it's worth toning down. Nm is a model parameter and not a direct measurement of migration.
• section 3.3. Lower Nm = weaker dispersal - such a conclusion should not be drawn directly, especially with different sizes of communities.
• Clarify the analytical basis and identification confidence of the volatile compounds. The manuscript states that 110 compounds were identified, but it is unclear how compound identities were confirmed. 
• Clarify the interpretation of “flavor succession” and “metabolic transformation.” The terms “flavor succession” and “metabolic transformation” appear to be used interchangeably with changes in metabolite abundance. However, changes in abundance do not necessarily demonstrate metabolic conversion. 
• Reconsider the interpretation of ROAV values. The use of ROAV ≥ 1 to identify 21 core aroma-active compounds is appropriate as a screening approach, but the manuscript should acknowledge that ROAV is an estimate of potential aroma contribution rather than a direct measurement of sensory importance. 
• Reconsider the conclusion that the absence of wheat-derived microorganisms “fundamentally altered the metabolic flux.” This is a strong mechanistic conclusion that may not be fully supported by the data presented. The results demonstrate differences in volatile profiles and microbial communities, but they do not directly establish changes in metabolic flux.
• The manuscript does not indicate the relevant PICRUSt2 quality metrics, such as NSTI values or other indicators of prediction reliability. This is particularly important for Daqu, where the microbial community may contain relatively unusual or poorly represented taxa
• Statements such as “alcohol dehydrogenase increased during fermentation” and “some pathway-level differences were observed during early fermentation” require statistical support
• The conclusion that functional differences are “consistent with the distinct microbial succession patterns and volatile profiles” is reasonable as an observation, but the manuscript would be stronger if the authors performed an integrated analysis, such as correlation/network analysis, constrained ordination, or another multivariate approach linking microbial communities, predicted functions, and volatile metabolites.

Comments on the Quality of English Language

The quality of English is good. 

Author Response

Reviewer 1:

General Comment: The manuscript is interesting but some aspect should be improved:

Response: We thank the reviewer for the positive overall assessment of the manuscript and for pointing out the aspects that require improvement. We have carefully revised the manuscript in accordance with all specific suggestions. Our point-by-point responses are provided below.

Specific Comment 1: Abstract should be rewritten to clearly indicate the novelty of the research.

Response and revision: We thank the reviewer for this suggestion. We have rewritten the abstract, and the revised abstract highlights the main findings and novelty. The revised abstract is as follows:

Page 1 Lines 13-17: “… In this study, traditional Daqu (T) and surface-disinfected Daqu (S) were used as paired controls to decouple the contribution of raw material-associated microorganisms. By integrating community, flavor, and functional analyses, we revealed their ecological roles in driving deterministic assembly, reshaping fungal interactions, and associating with characteristic flavors. …”

Page 1 Lines 30-32: “…This study deepens the understanding of the ecological roles of raw material-associated microorganisms and provides a scientific basis for process optimization and microbial community regulation in traditional fermented foods.”

Specific Comment 2: Introduction should be improved, strongly indicate the importance of the research.

Response and revision: We have revised the Introduction as suggested. The specific revisions are as follows:

Page 2, Lines 39-48: “…High-temperature Daqu is a typical type, usually using wheat as the main raw material. Its production includes wheat moistening, crushing, water addition, pressing into blocks, and controlled fermentation. After molding, the product temperature rises rapidly, reaching a maximum of about 60 °C, and then gradually decreases until the end of fer-mentation. This high-temperature stage imposes strong selective pressure on the microbiota: many mesophilic veg-etative cells and non-thermotolerant fungi associated with wheat may be inhibited or inactivated, whereas thermo-tolerant spore-forming bacteria and thermophilic fungi may survive and even proliferate. Traditionally, Daqu mi-croorganisms have been considered to originate mainly from the production environment, including workshop air and equipment-associated microorganisms [4,5]. In comparison, the microbial community carried by wheat raw materials may be an important source of the early-stage community in high-temperature Daqu fermentation.”

Page 2, Lines 61-64: “Therefore, controlled comparison by reducing raw-material microorganisms is an effective strategy to separate their contributions; however, whether these early microbial differences can persistently affect key functional taxa and the formation of characteristic flavor compounds still needs to be verified by controlled experiments. In high-temperature Daqu fermentation, clarifying this issue is important for moving from natural inoculation to precise microbial regulation.”

Page 2, Lines 65-67: “In this study, we established two high-temperature Daqu fermentation systems using untreated and surface-disinfected wheat, thereby decoupling the contribution of raw-material-associated microorganisms from the environmental background through a controlled comparison.”

Page 2, Lines 72-76: “These findings not only deepen our understanding of the role of raw-material microbiota in high-temperature Daqu fermentation but also provide a basis for raw material pretreatment, targeted supplementation of key functional microorganisms, development of fortified starters, and optimization of the Daqu-making process, thereby improving the quality stability of Daqu and the consistency of Baijiu production.”

Specific Comment 3: section 3.3. Higher Nm = greater dispersal” - it's worth toning down. Nm is a model parameter and not a direct measurement of migration.

Response: We thank the reviewer for this comment. We agree that Nm is a model parameter and cannot be interpreted as a direct measurement of migration or dispersal. We have therefore deleted the statement “The higher Nm value in group S suggested greater dispersal potential” from Section 3.3. In the revised manuscript, Nm is reported only as a parameter of the Sloan neutral model together with R², and no inference about dispersal ability is made.

Specific Comment 4: section 3.3. Lower Nm = weaker dispersal - such a conclusion should not be drawn directly, especially with different sizes of communities.

Response: Similarly, we have also removed any statements comparing dispersal ability based on Nm values. In the revised manuscript, Nm values are reported solely as model parameters and are no longer used to infer weaker or stronger dispersal.

Specific Comment 5: Clarify the analytical basis and identification confidence of the volatile compounds. The manuscript states that 110 compounds were identified, but it is unclear how compound identities were confirmed.

Response and revision: We thank the reviewer for pointing out this inconsistency. In the revised manuscript, we have added the identification workflow in Section 2.3, including the NIST library match threshold, comparison with literature RI values, and confidence level classification. We have also changed “identified” to “preliminarily identified” in the Results and Discussion section. The specific revisions are as follows:

Page 4, Lines 151-161: “Volatile compounds were preliminarily identified by matching their mass spectra against the NIST mass spectral library, with a similarity threshold of ≥80%. Retention indices (RIs) were calculated using n-alkane homologues (C8-C40) analyzed under the same chromatographic conditions, and compared with reference RI values reported in the NIST WebBook and in the literature on DB-WAX or equivalent polar columns. Compounds with a NIST match of ≥80% and calculated RIs consistent with literature RI values were retained. All preliminarily identified compounds in this study met the Level 2 criteria, which indicates identification based on literature or database matching rather than confirmation with authentic standards. After identification, volatile compounds were semi-quantified using the internal standard method, and their relative concentrations were calculated according to the following formula:”

Page 10, Lines 353: “A total of 110 volatile compounds were preliminarily identified…”

Specific Comment 6: Clarify the interpretation of “flavor succession” and “metabolic transformation.” The terms “flavor succession” and “metabolic transformation” appear to be used interchangeably with changes in metabolite abundance. However, changes in abundance do not necessarily demonstrate metabolic conversion.

Response and revision：We thank the reviewer for this comment. We have removed any wording that implied metabolic conversion and have revised the text to describe only changes in the accumulation patterns and relative contributions of volatile metabolites. The specific revisions are as follows:

Page 10, Lines 359-363: “Composition analysis (Figure 4A) showed that different treatments significantly altered the ac-cumulation patterns of volatile metabolites. In group T, pyrazines, esters, and acids were more prominent during the mid-to-late fermentation stages, and the relative contributions of acids and aldehydes changed between days 10 and 20.”

Specific Comment 7: Reconsider the interpretation of ROAV values. The use of ROAV ≥ 1 to identify 21 core aroma-active compounds is appropriate as a screening approach, but the manuscript should acknowledge that ROAV is an estimate of potential aroma contribution rather than a direct measurement of sensory importance.

Response and revision: We thank the reviewer for this comment. Indeed, ROAV is an estimate of potential aroma contribution rather than a direct measurement of sensory importance. After reviewing the manuscript, we have changed “core aroma-active compounds” to “potential contributing compounds,” changed “sensory contribution” to “aroma contribution,” and changed “sensory dimension” to “aroma dimension.” The specific revisions are as follows:

Page 1, Lines 21-23: “…A total of 110 flavor compounds were identified, from which 21 potential contributing compounds and 25 differential markers were screened. …”

Page 5, Line 166: “To evaluate the potential contributions of volatile compounds to Daqu, we calculated the relative odor activity values (ROAVs) according to the method of Zhang et al. [14]. …”

Page 10, Lines 374-389: “By applying a threshold of ROAV ≥ 1, a total of 21 potential aroma-contributing compounds were identified (Figure 4C and Table S2), further revealing the essential differences between the two types of Daqu in characteristic aroma dimensions. In group T, the turning period (10-20 d) was characterized by significant enrichment of aldehydes, phenols, and sulfur-containing compounds, which had high aroma contributions. For example, benzaldehyde and phenylacetaldehyde, which impart caramel-like and sweet floral aromas, had ROAVs as high as 90.35 and 39.03 at 10 d, respectively; 2-methoxyphenol (guaiacol) and 4-vinylguaiacol, which contribute smoky and clove-like odors, and dimethyl trisulfide, which presents sulfurous and roasted aromas, showed extremely high aroma contributions in the mid-to-late period of group T. These compounds collectively constitute the typical roasted, sauce-like, and sweet floral composite flavor profile of traditional high-temperature Daqu [8]. In contrast, the key aroma compounds in group S exhibited a completely different aroma dimension. Among them, 1-octen-3-ol has a typical mushroom and earthy note and maintained a high ROAV throughout the whole stage of group S (up to 100); together with 2-nonanone, which contributes fruity and floral aromas, it conferred obvious fungal-like and delicate aroma characteristics to group S. …”

Page 11, Line 407: Figure 4.“… (C) Dynamic changes in the relative abundances of potential aroma-contributing compounds with relative odor activity values (ROAV) > 1 in different Daqu samples. …”

Specific Comment 8: Reconsider the conclusion that the absence of wheat-derived microorganisms “fundamentally altered the metabolic flux.” This is a strong mechanistic conclusion that may not be fully supported by the data presented. The results demonstrate differences in volatile profiles and microbial communities, but they do not directly establish changes in metabolic flux.

Response and revision: We thank the reviewer for this comment. We have removed this statement and changed “metabolic flux” to “aroma compound characteristics.” The detailed revisions are as follows:

Page 11, Lines 399-401: “This indicates that the absence of wheat-derived microorganisms not only simplified the flavor profile but also fundamentally altered the aroma compound characteristics in Daqu [14,15].”

Specific Comment 9: The manuscript does not indicate the relevant PICRUSt2 quality metrics, such as NSTI values or other indicators of prediction reliability. This is particularly important for Daqu, where the microbial community may contain relatively unusual or poorly represented taxa.

Response and revision: We thank the reviewer for this suggestion. In fact, we had already calculated NSTI values in this study and have now added a detailed description in the revised manuscript. Specifically, we used PICRUSt2 v2.2.2-b for functional prediction: first, 16S rRNA and ITS feature sequences were aligned against reference sequences and a new phylogenetic tree was constructed; then, based on the gene family copy numbers corresponding to the reference sequences, the Castor hidden-state prediction algorithm was used to infer the nearest sequenced taxon and its gene family copy numbers for each feature sequence, and the NSTI value of each feature sequence was calculated simultaneously. Feature sequences with NSTI > 2.0 were removed by default in subsequent analyses. Subsequently, combined with the abundance of feature sequences in each sample, the gene family copy numbers of each sample were calculated, and a stratified strategy was used to retain the correspondence between functions and species. Finally, gene families were mapped to the MetaCyc database, and metabolic pathways were inferred using MinPath to obtain enzyme abundance data. To avoid misunderstanding, we have added this description in the Data Analysis section. The detailed revisions are as follows:

Page 5, Lines 193-203：“For bacterial and fungal communities, we used PICRUSt2 v2.2.2-b to perform functional prediction based on 16S rRNA and ITS feature sequences: feature sequences were aligned against reference sequences and a phylogenetic tree was constructed; the Castor hidden-state prediction algorithm was used to infer gene family copy numbers, and NSTI was calculated simultaneously; feature sequences with NSTI > 2.0 were removed. Subsequently, combined with the abundance of feature sequences in each sample, the gene family copy numbers of each sample were calculated, and a stratified strategy was used to retain the correspondence between functions and species. Finally, gene families were mapped to the MetaCyc database, and metabolic pathways were inferred using MinPath to obtain enzyme abundance data.”

Specific Comment 10: Statements such as “alcohol dehydrogenase increased during fermentation” and “some pathway-level differences were observed during early fermentation” require statistical support.

Response and revision: We thank the reviewer for pointing out that the relevant statements lacked statistical support. To address this, we used fermentation time (0, 10, 20, and 40 d) as a continuous variable and performed linear regression analysis on the predicted abundance of each enzyme to evaluate the temporal trends in groups T and S separately, and added Table S6. All p values were corrected for FDR using the Benjamini-Hochberg method, with significance thresholds set at p < 0.05 and FDR < 0.05. In the revised manuscript, the relevant descriptions have been revised. The detailed revisions are as follows:

Page 15, Lines 505-536: “Based on PICRUSt2 functional prediction, both groups were enriched in functions related to carbohydrate metabolism (Figure S2). Among these, predicted functions associated with starch and polysaccharide degradation included α-amylase (EC 3.2.1.1) and glucan 1,4-α-glucosidase (EC 3.2.1.3). Sample-level temporal slope analysis showed that the mean temporal slopes of the α-amylase-associated function were negative in both groups T and S, whereas those of the glucan 1,4-α-glucosidase-associated function were positive in both groups (Table S6). These results reflect the overall direction of change over the study period; because the relevant changes deviated from linear trajectories, they cannot be used to infer those adjacent stages all changed in the same direction [29, 35]. Both groups also harbored some predicted functions related to glycolysis, indicating partial overlap in their predicted functional composition.

The predicted results for both groups also included functions potentially related to flavor precursor metabolism. The alcohol dehydrogenase (EC 1.1.1.1) associated function showed an overall increasing trend in group T, whereas no significant linear temporal trend was detected in group S. The mean temporal slope of the acetolactate synthase (EC 2.2.1.6) associated function was positive in group T, but did not reach statistical significance in group S (Table S6). The predicted results also included functions related to 2,3-butanediol dehydrogenase. Carboxylesterase (EC 3.1.1.1) and triacylglycerol lipase (EC 3.1.1.3), which are related to lipid and ester metabolism [32], had significantly positive mean temporal slopes in both groups, but their changes deviated from linear trajectories and should therefore be interpreted as overall directions of change (Table S6).

In addition, the predicted results included functions potentially involved in the transformation of aromatic compounds, namely aromatic L-amino acid decarboxylase (EC 4.1.1.28) and monoamine oxidase (EC 1.4.3.4). The mean temporal slopes of both functions were significantly positive in groups T and S, but both exhibited non-linear changes (Table S6). The catechol O-methyltransferase (EC 2.1.1.6)-associated function was excluded because it did not meet the requirement for the proportion of non-zero samples. These predicted results provide clues for exploring the potential transformation of aromatic precursors, but they cannot be used to confirm the actual production of phenols, aromatic alcohols, or other flavor compounds [36,37]. Notably, the above analysis represents an exploratory assessment of functional potential and should not be interpreted as a direct measurement of functional gene abundance, enzyme expression, or enzyme activity.”

Specific Comment 11: The conclusion that functional differences are “consistent with the distinct microbial succession patterns and volatile profiles” is reasonable as an observation, but the manuscript would be stronger if the authors performed an integrated analysis, such as correlation/network analysis, constrained ordination, or another multivariate approach linking microbial communities, predicted functions, and volatile metabolites.

Response and revision: Thank you for this valuable suggestion. We agree that Figure 7 presents only an exploratory correlation analysis between microorganisms and volatile compounds, and does not constitute an integrated analysis of the microbial community, predicted functions, and volatile flavor profiles. In addition, PICRUSt2 predictions are derived from microbial community data and are not independent functional measurements; therefore, they cannot serve as direct evidence to validate the associations among the three. We also appreciate the reviewer’s suggestion for integrated analysis. In future studies, we will experimentally monitor the key enzymes obtained from the predictions to further improve the related research. Meanwhile, we have added the above limitations to the Conclusion section. The specific revision is as follows:

Page 17, Lines 589-593: “…However, this study is only an exploratory correlation analysis and did not integrate the microbial community, PICRUSt2-predicted functions, and volatile profiles; the predicted functions are not independent measurements, and the conclusions still require validation by metatranscriptomics, metaproteomics, or targeted metabolomics.”

This concludes our point-by-point response to Reviewer 1.

Reviewer 2 Report

Comments and Suggestions for Authors

Dear Editor and dear Authors,

I have carefully read the paper entitled “Wheat-surface microbiota as a key driver of Daqu quality: Evidence from microbial diversity and volatile flavor analysis”.

The topic of studying is very interesting and important. The identification of microbiota, the impact of various treatments, and the identification of different flavors are significant for regulating the Daqu fermentation process.

Article is well written, it is readable, the concept is easy to follow and the scope of work is defined properly.

However, there are some technical issues through the text that need revision. Overall, my suggestion is that the paper requires minor revisions listed bellow:

Material and Methods

2.1. Line 82

The term "sterilized" is not appropriate. Sterilization generally implies heat treatment at 120°C in an autoclave, whereas in this paper samples are immersed in ethanol irradiated by UV radiation treatment. I suggest that the authors revise the designation for sample group “S” in this section and throughout the paper.

Results and Discussion

Comment for all figures

It is not possible to read the labels and the data from the figures. The authors need to increase the font size or split Image 1 into two separate images.

Author Response

Reviewer 2

General Comment: Dear Editor and dear Authors, I have carefully read the paper entitled “Wheat-surface microbiota as a key driver of Daqu quality: Evidence from microbial diversity and volatile flavor analysis”. The topic of studying is very interesting and important. The identification of microbiota, the impact of various treatments, and the identification of different flavors are significant for regulating the Daqu fermentation process. Article is well written, it is readable, the concept is easy to follow and the scope of work is defined properly. However, there are some technical issues through the text that need revision. Overall, my suggestion is that the paper requires minor revisions listed bellow:

Response：We thank you for your positive comments on the research topic, organization, and readability of our manuscript. Your suggestions have helped improve the accuracy of the experimental treatment description and the readability of the figures. Below are our point-by-point responses and revisions to each comment.

Material and Methods

Specific Comment 1: 2.1. Line 82

The term "sterilized" is not appropriate. Sterilization generally implies heat treatment at 120°C in an autoclave, whereas in this paper samples are immersed in ethanol irradiated by UV radiation treatment. I suggest that the authors revise the designation for sample group “S” in this section and throughout the paper.

Response: We thank the reviewer for pointing out this issue. In this study, the wheat was indeed treated by ethanol immersion and ultraviolet irradiation, which was intended to reduce surface microorganisms and is not equivalent to autoclaving. Therefore, we have changed the treatment description to “surface-disinfected group (S),” while retaining the abbreviation S. The relevant descriptions throughout the manuscript, figures, figure legends, and Supplementary Material have been updated accordingly.

Comment for all figures

Specific Comment 2: It is not possible to read the labels and the data from the figures. The authors need to increase the font size or split Image 1 into two separate images.

Response and revision：We thank the reviewer for this suggestion. We have re-examined all figures and increased the font sizes of the axis labels, legends, facet titles, and statistical annotations. Because the original Figure 1 contained 12 subpanels and was highly information-dense, we retained only the rarefaction curves and principal component analysis in the main manuscript, and moved the alpha-diversity indices to the Supplementary Material. All figures have been updated in the revised manuscript.

This concludes our point-by-point response to Reviewer 2.

Reviewer 3 Report

Comments and Suggestions for Authors

The manuscript approaches in a high throughput methodological approach (amplicon sequencing, headspace solid-phase microextraction gas chromatography mass spectrometr, co-occurrence network analysis, functional prediction) the contribution of  raw material (wheat) associated microorganisms to a traditional fermenting starter (Daqu) sued for a traditional Chinese spirit (Baiiju). The level of novelty is high due to the methodological approach; however, the practical application of the findings are moderate.  

Introduction section. Generally, the provided information cover satisfactorily the context of the research, supported with relevant updated references. In addition, the drawbacks of the knowledge are sufficiently clear addressed. However, it is recommended to provide some more information related to the Daqu production and to define values of high-temperature Daqu fermentation systems (e.g. how much can be affected the raw material microbiota by such temperatures).

Methodology section. Generally, the employed methods are presented in sufficient details and are appropriate in relation to the research objectives. However, some issues is recommended to be addressed, as written below.

Page 3, line 76: please quantify the portion

Page 3, line 80: please be very specific on the temperature

Page 3, line 83: please explain why the fermentation process was designed for 45 days, while the sampling ended on day 40

Page 3, line 84: what was the size of the batch?

Results section. Generally, the results are well supported with data and images and are clearly presented and in analysed by comparison. Some issues supports more explanations, as follows.

Page 11, line 388: please explain why did you consider that the performance of the PLS-DA model was „excellent”, especially in the case of R²Y(cum) = 0.662 and Q²(cum) = 0.51)

General observation: discussions in realtionto other reports are relatively poor, as well as the critical analysis of the results. Especially, it is expected to correlate the findings with practicalities in the Daqu fermentation and further, in Baijiu production.

Conclusions section. The conclusions are satisfactorily supported by the results. How the findings will lead to further investigations, especially toward practical application, needs improvements.

Author Response

Reviewer 3

General Comment: The manuscript approaches in a high throughput methodological approach (amplicon sequencing, headspace solid-phase microextraction gas chromatography mass spectrometr, co-occurrence network analysis, functional prediction) the contribution of raw material (wheat) associated microorganisms to a traditional fermenting starter (Daqu) sued for a traditional Chinese spirit (Baiiju). The level of novelty is high due to the methodological approach; however, the practical application of the findings are moderate.

Response：We thank you for your positive comments on our methodological framework and the value of this study. Your suggestions have helped improve the manuscript and enhance its quality. We have now indicated future directions for practical application in the Conclusion section.

Introduction section.

Specific Comment 1: Generally, the provided information cover satisfactorily the context of the research, supported with relevant updated references. In addition, the drawbacks of the knowledge are sufficiently clear addressed. However, it is recommended to provide some more information related to the Daqu production and to define values of high-temperature Daqu fermentation systems (e.g. how much can be affected the raw material microbiota by such temperatures).

Response and revision：We thank the reviewer for the positive comments and constructive suggestions. We have added relevant information on Daqu production and the parameters of the high-temperature Daqu fermentation system. The specific revisions are as follows:

Pages 1-2, Lines 39-48：“High-temperature Daqu is a typical type, usually made from wheat as the main raw material. Its production includes wheat moistening, crushing, water addition, pressing into blocks, and controlled fermentation. After molding, the product temperature rises rapidly, reaching a maximum of about 60 °C, and then gradually decreases until the end of fermentation. This high-temperature stage imposes strong selective pressure on the microbiota. Many mesophilic vegetative cells and non-thermotolerant fungi associated with wheat may be inhibited or inactivated, whereas thermotolerant spore-forming bacteria and thermophilic fungi may survive and even proliferate. Therefore, the microbial community carried by wheat may be an important source of the early-stage community in high-temperature Daqu fermentation.”

Methodology section. Generally, the employed methods are presented in sufficient details and are appropriate in relation to the research objectives. However, some issues is recommended to be addressed, as written below.

Specific Comment 2: Page 3, line 76: please quantify the portion.

Response and revision: Thank you for this helpful comment. We have now quantified the ratio in the revised manuscript. A total of 100 kg of wheat was divided equally by mass into two portions (50 kg each; 1:1 ratio), which were used for the untreated traditional group (T) and the surface-disinfected group (S), respectively. The specific revisions are as follows:

Page 3, Lines 79-85: “Wheat used for high-temperature Daqu production was obtained from a sauce-flavor Baijiu manufacturer. A total of 100 kg of wheat was divided equally by mass into two portions (50 kg each; 1:1 ratio). One portion was treated to reduce wheat-associated microorganisms by immersion in 75% ethanol for 15 s, followed by three rinses with sterile distilled water and ultraviolet irradiation for 30 min; this portion was used for the sur-face-disinfected group (S). The other portion (50 kg) was left untreated and used for traditional Daqu production (traditional group, T).”

Specific Comment 3: Page 3, line 80: please be very specific on the temperature.

Response and revision: Thank you for this comment. We have now specified the temperature in detail. Both wheat treatments were independently processed under identical high-temperature Daqu production conditions for 40 days. The product temperature was monitored at the center of the Daqu blocks and reached a maximum of 60 °C. The specific revisions are as follows:

Page 3, Lines 85-88: “Both wheat treatments were independently processed under identical high-temperature Daqu production conditions for 40 days. The product temperature was monitored at the center of the Daqu blocks and reached a maximum of 60 °C.”

Specific Comment 4: Page 3, line 83: please explain why the fermentation process was designed for 45 days, while the sampling ended on day 40.

Response and revision: We apologize for this typographical error. In fact, the fermentation process lasted 40 days, and we have corrected this in the revised manuscript. The specific revision is as follows:

Page 3, Line 86: Both wheat treatments were independently processed under identical high-temperature Daqu production conditions for 40 days.

Specific Comment 5: Page 3, line 84: what was the size of the batch?

Response and revision：Thank you for this comment. We have now specified the batch scale. A total of 50 Daqu blocks were prepared, comprising 25 blocks in the traditional group (T) and 25 blocks in the sterilized-wheat group (S). Each group was processed as one independent fermentation batch containing 25 blocks. At each sampling point (days 0, 10, 20, and 40), four blocks were randomly selected from each group. Each block was thoroughly crushed and homogenized and treated as one representative sample. Thus, four block-level samples were obtained per group at each sampling time, giving a total of 32 representative samples (2 groups × 4 time points × 4 blocks = 32). The independent experimental unit was the Daqu block. The specific revision is as follows:

Page 3, Lines 89-94: “A total of 50 Daqu blocks were prepared: 25 blocks in the traditional group (T) and 25 blocks in the sterilized-wheat group (S). Each group was processed as one independent fermentation batch containing 25 blocks. At each sampling point (days 0, 10, 20, and 40), four blocks were randomly selected from each group. Each block was thoroughly crushed and homogenized, and each block served as one representative sample. In total, 32 representative samples were obtained (2 groups × 4 time points × 4 blocks).”

Results section. Generally, the results are well supported with data and images and are clearly presented and in analysed by comparison. Some issues supports more explanations, as follows.

Specific Comment 6: Page 11, line 388: please explain why did you consider that the performance of the PLS-DA model was „excellent”, especially in the case of R²Y(cum) = 0.662 and Q²(cum) = 0.51)

Response and revision: We thank the reviewer for this correction. After reviewing the literature, we agree that describing R²Y(cum) = 0.662 and Q²(cum) = 0.51 as “excellent” in the previous version was indeed not accurate enough. Specifically, R²Y(cum) = 0.662 indicates that the model explains approximately 66.2% of the variance in the Y matrix, which is a moderate level; Q²(cum) = 0.51 indicates that the cross-validated predictive ability is approximately 51%, only slightly above the commonly used acceptable threshold of 0.5, representing acceptable but not strong prediction. Therefore, we have changed “excellent explanatory and predictive performance” to “acceptable explanatory and predictive performance” in the manuscript to avoid overstating the model performance. The specific revisions are as follows:

Page 11, Lines 412-415: “The model exhibited acceptable explanatory and predictive performance (R²X(cum) = 0.878, R²Y(cum) = 0.662, Q²(cum) = 0.51), and its statistical robustness was validated by 200 permutation tests with no overfitting observed (Figure 5A). ”

Specific Comment 7: General observation: discussions in realtionto other reports are relatively poor, as well as the critical analysis of the results. Especially, it is expected to correlate the findings with practicalities in the Daqu fermentation and further, in Baijiu production.

Response and revision: We thank the reviewer for pointing this out. To address this, we have added relevant discussion in the Discussion section of the revised manuscript. The specific revisions are as follows:

Page 8, Lines 290-294: “The enrichment of Thermoascus in group T was consistent with the reports of Zhang et al. [6] and Steindorff et al. [24], whereas the dominant bacterial genera differed between the two groups, suggesting that the subsequent succession of wheat-associated microbiota may depend on specific raw materials and Daqu-making conditions.”

Page 9, Lines 334-341: “This stronger deterministic signal in group T during the mid-to-late stages was generally consistent with the environmental filtering effect reported for Daqu by Ma et al. [5]. However, the present analysis cannot distinguish the specific contributions of temperature, moisture, and acidity. In future practical Daqu production, these process parameters could be monitored together with community succession to further evaluate the effects of turning and ventilation regulation on batch stability. Nevertheless, stronger deterministic assembly should not be directly equated with better Daqu quality.”

Page 10, Lines 391-396: “The enrichment of phenolic compounds and pyrazines in group T was consistent with the lignin and ferulic acid-degrading capacity of thermophilic actinomycetes and thermo-philic fungi and with the typical high-temperature microenvironment. It also agreed with the report by Luo et al. [27] that temperature-related microbiota promote tetra-methylpyrazine formation, suggesting that precursor supply and the fermentation environment may jointly drive flavor formation.”

Conclusions section.

Specific Comment 8: The conclusions are satisfactorily supported by the results. How the findings will lead to further investigations, especially toward practical application, needs improvements.

Response and revision：We thank the reviewer for this suggestion. We have added specific directions for future research toward practical application in the Conclusion section. The specific revisions are as follows:

Page 16, Lines 585-589: “… In the future, key functional microorganisms could be isolated and screened, directed supplementation or fortified starters could be developed, and process regulation could be combined to construct a controllable initial community, thereby stabilizing the fermen-tation process and flavor and promoting standardized production applications. …”

This concludes our point-by-point response to Reviewer 3.

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

The reviewer's suggestion was implemented in the manuscript. 

Comments on the Quality of English Language

The quality of English is good. 

Reviewer 3 Report

Comments and Suggestions for Authors

No further comments