The authors did not address my concerns. They still use a single study to calibrate their model--or, put more exactly, recalibrate one of their previous models. They still use the same data to calibrate and evaluate the model.  The authors made some minor changes to wording, but otherwise their work is the same.  My opinion remains that it is too preliminary.  

Muñoz-Tamayo et al. developed a mathematical model to explain how Asparagopsis taxiformis inhibits methane formation by rumen microbes in vitro. Previous work has found A. taxiformis inhibits methane formation by up to 80% or more. A mathematical model would be important for understanding at a mechanistic level how this inhibition occurs.

The model developed here could have been valuable, but unfortunately it is too preliminary. The model was calibrated with data from a single study (Chagas et al. 2019) (see L40-1). Further, it was evaluated with the same data as for calibration (see Fig. 3-4 and Table 2). It is not clear why the authors limited themselves to these data, given the number of in vitro and in vivo studies in the literature. To make the conclusions generalizable, more than one study needs to be used. Further, data for calibration and evaluation need to be independent.

This paper focus on the adaptation of a dynamic mechanistic model of ruminal fermentation to estimate in vitro effects of macroalgae (i.e. Asparagopsis Taxiformis) rich in natural bioactive compounds as rumen modifier to reduce methane emissions.
The paper is original and focus on two relevant topics for ruminant nutrition: i) optimization of rumen fermentations to mitigate enteric methane emissions and ii) modeling rumen fermentations to improve understanding of fermentation dynamics and to predict fermentation outputs. The paper can be considered of high quality, is clearly written, detailed and concise in terms of motivation and background, presentation of methodological details, and main findings.
The work is well planned and has strong methodological roots, being based on a published model already evaluated by scientific literature, which was in this work adapted and tested with data from a published experiment on the use of A. Taxiformis in vitro. The presented rumen model has high degree of innovation, since approaches the complex ruminal environment with high level of simplification. The core model assumption is the microbial group aggregation in respect to the use of glucose, aminoacid and Hydrogen influencing VFA and methane production, which were stoichiometrically modeled. Simplified model structure and assumptions do not limit excellent performance in VFA and methane predictions from in vitro fermentations. Model documentation is complete and exhaustive: model adaptations, in respect to original model versions, are reported in methods with detailed equations, and providing useful links to scripts, model codes and data for readers and users. Model assumptions are explicit and motivated. Origin of model parameters is clearly detailed and motivated (from calibration, literature or from experimental trial of Chagas et al., 2019).
The paper mainly focus on modeling but also biological aspects related with use and effects of A. Taxiformis (and presumably bromoform) as rumen modifier are deeply and concisely discussed referring to broad literature.
Data used to adapt and test the model proceed from a published paper on dose-response in vitro evaluation for the effect of the A. Taxiformis, Chagas et al., 2019. The reference paper is also clearly written and detailed in terms of methods and results. It represented a good basis for model testing and evaluation. The topic focused by Chagas et al., 2019 is highly relevant and the use of A. Taxiformis, and its related bio-active compounds seems highly promising for methane mitigation.
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Few comments are below highlighted following the sections of paper structure:
Background is mainly focused on biological effects of the Macroalgae and bromoform on ruminal environment explaining biological basis and implication of its use with proper quotes. Lines 25 and 26 might be integrated expliciting if negative long term effects can impair the algae use on animal diets (see also line 348).
A very little part of introduction is dedicated to importance of rumen modeling, which seems a not secondary focus of the paper, especially for microbiological based models. it could represent a frontier in ruminant nutrition. In this sense the paper objective might be integrated with the generic objective of enriching rumen modeling, adaptation and testing and especially accounting for effects of bioactive compounds (as further stated by the authors in line 272) on fermentation complexity.
Methods are well detailed, the model adaptation is justified with proper assumptions and references and documented for high degree of replicability. The model well resumes the rumen complexity. Statistics for model evaluation are adequate. Line 61 refers to four groups then in parenthesis and in Figure 1 only three groups are presented, it should be clarified.
Results of model predictions and sequent evaluations are noticeably presented with multiple figures, enhancing the satisfactory model performances. Discussions covered both biological and modeling aspects also proposing future model expansions. Among discussions of hydrogen control, an additional sentence can emphasize effects on energy harvesting. In fact, it is quite debated in literature the fact that methane reduction not always lead to higher energy efficiency use, by microbial groups at rumen level or for the animal, whit not significant difference in production performances. Model limitations are separately and exhaustively discussed by the authors both in terms of used data, model assumption and structure with respective proposals for model improvement, including applications for in vivo conditions.
In summary this paper represents a valuable example of valorization of experimental data for model testing and expansion. From these considerations the paper is highly recommended both for quality and findings.

This manuscript presents a model evaluating the impact of Asparagopsis taxiformis on rumen fermentation. The manuscript addresses a relevant topic for this journal. Overall, the manuscript is generally well written although the presentation is likely too specialized for many if not most readers. The authors provide a good introduction describing the background and rationale for their research. The materials and methods are written succinctly but leave out some important details that would help the readers more clearly understand and judge their work.

1) For instance, what was the diet of the two Swedish Red cows? Was it the same as used for the incubations? It is not clear.
2) Were the cows cannulated or was the rumen fluid collected via stomach tube or ruminocentesis? 3) What was the buffer used for the incubations and was it of sufficient buffering capacity to maintain the pH during incubation at or near your assumed pH 6.6 value?
4) How were gases, VFA, ammonia measured? Perhaps this info is in the Ramin and Huhtanen (2012) citation but if so please describe it that way.
5) On lines 109-110, did you really calculate numbers of hydrogen-utilizing microbes as mol/L? 6) Figure 1 presents the model as a closed system, is this true for your incubations or was there venting of gases? If truly a closed system I suspect increasing gas pressures would affect gas solubility.

The results are presented and discussed objectively. You do not need to address this but I am curious to know if you had foaming in your incubations which could potentially be an unaccounted electron sink? I am thinking most fermentation balances do not generally get such good agreement between reducing equivalents consumed and produced as presented here. If you buffer was sufficient to maintain pH at or near 6.6 then that is fine, otherwise I would have liked to see pH measurements.

Overall, this is a good piece of work but I think it would be better if the authors make the effort to make it more broadly readable.