This is a well-written and interesting paper that expands the T&C model to simulate crop growth based on physiological crop attributes. The T&C model is a well-established and validated biosphere model and T&C-crop enhances its capabilities. Its performance is comparable to other similar models, but T&C-crop has notable advantages of requiring few parameters, being able to simulate multiple crop cycles (contrary to other models that need to be re-initialized for each cycle), and carrying soil legacy information, which influences crop growth, thanks to its integration within T&C model. I recommend publication after the following comments are considered.

1. It would be useful to include a simple schematic of the T&C-CROP model that particularly emphasizes the new contributions introduced here. T&C is well established, so there is no need of a full model diagram. I leave it to the authors to find the right balance in providing the details needed to highlight the new aspects.

2. During model evaluation, the parameters were adjusted within a +-30% range, following a manual trial and error calibration. While I understand that a systematic calibration is beyond the scope of this work, I wonder if the authors foresee incorporating calibration techniques, particularly Bayesian techniques (Markov Chain Monte Carlo calibration, for example), into the modeling framework.

3. In the introduction, I appreciated the discussion regarding the importance of further developing physics-based models, despite having sometimes lower performance than machine-learning approaches. As more data becomes available, probably an integration of data-driven and process-based approaches could help significantly improve our prediction capability.

4. In the model intercomparison, providing additional details on how the other models were set up for simulations would be helpful. For example, were they calibrated to improve performance? If so, what method was used? Including more details would allow for a fairer comparison I believe.

5. In the discussion, I am curious whether the authors plan to further develop T&C-CROP. In an agricultural context, other processes such as soil erosion, pesticide applications, as well as other agricultural practices, especially those that are becoming more common with climate-smart agriculture. While this model represents a step forward from from other biosphere models mentioned in the manuscript (ORCHIDEE, JULES, etc.), other models specifically developed for agricultural ecosystems (APEX, DNDC, etc.) have made significant advancements in parameterizing ag practices, even though they may be less physically-based in approaching other biosphere processes.

I would like to begin by commending the authors for their excellent work on this paper. It is very well-written, with clear language and a logical structure that makes the content easy to follow. The study introduces the crop representation into the T&C model. The methodology is presented in a highly organized manner, and the evaluation is thorough, providing convincing evidence for the effectiveness of the proposed approach. One aspect I particularly appreciated was the detailed explanation of the experimental setup and the comprehensive evaluation of the model results.

However, I encountered some challenges in fully grasping the distinction between the T&C model and the T&C-Crop model. While the paper briefly touches on the enhancements made in the code and methodology, it would benefit from a more explicit description of these new contributions.

General Comments:

What does T&C stand for?

You provide extensive detail in the supplement regarding fertilizer application, planting, and harvest dates. Could you extend this level of detail to include the crop-specific parameters as well? Important variables are evaluated, but I would further appreciate a comparison to net ecosystem exchange (NEE) data, as this is one of the most important variables for the carbon balance in terrestrial biosphere models (TBMs).

Minor Comments:

Line 175: Could you clarify what is meant by "vegetation-specific approach where the model user defines the vegetation/crop in question"? This statement could benefit from further explanation.

Line 180: What is the difference between the plot-scale version and the spatially explicit version? Does the spatially explicit version involve dividing the grid into smaller sub-parts, or is there another distinction?

Figure S1: If I understand correctly, the blue line is not part of the T&C-Crop model and has been replaced by the sigmoidal function. If this is the case, please indicate this clearly in the plot. Alternatively, if I’ve misunderstood, please improve the caption and corresponding explanation in the article. My understanding was that the linear function was completely replaced.

Line 395: What is meant by "PTFs"? Please define this abbreviation for clarity.

Figures 1 & 2: It would be helpful to include the R² values directly on the plots, and perhaps also the RMSE values. RMSE could even be color-coded for additional visual clarity.

Line 535: I don’t fully understand the purpose of comparing T&C-Crop to JULES-CROP, especially since only LAI and AGB are compared. Comparisons with observed data would be more convincing. The same applies to the comparison with CLM-CROP on the following page.

Discussion Section:

Could you clarify whether the model needs to be re-parameterized for each location? If so, how is this addressed? This point would benefit from more detail.

Additionally, could you elaborate on the three new crop-specific parameters? Which parameters are these?

I would have appreciated a global application for crop yields, even if not in direct comparison to observed data. Perhaps a comparison to other models would fit well here.