Trajectory-level dynamic validation of a phase-structured grey-box model for consolidated bioprocessing using literature-derived ethanol trajectories

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A data-driven benchmark model outperforms a phase-structured grey-box model in predictive accuracy for ethanol production trajectories during consolidated bioprocessing. Novelty: ClaimNovelty.METHODOLOGICAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

Mark Korang Yeboah; Nana Yaw Asiedu; Ahmad Addo

doi:10.1186/s13068-026-02805-y

August 11, 2026Biotechnology for Biofuels and BioproductsOpen Access

Trajectory-level dynamic validation of a phase-structured grey-box model for consolidated bioprocessing using literature-derived ethanol trajectories

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Key Points

This research aims to develop a dynamic modeling framework for validating ethanol production in consolidated bioprocessing based on literature-derived data.
Developed a time-series-informed framework for trajectory-level validation.
Curated 23 trajectories with 216 observations from secondary literature for model training.
Fitted a grey-box model to represent enzymatic and fermentation phases.
Achieved RMSE of 3.990 g/L and MAE of 1.869 g/L for the benchmark model.
Grey-box model transition times were 38.190 h and 63.397 h for two phases.
Data-driven approach outperformed the grey-box model in predictive accuracy across matched series.

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Implication

Validates ethanol production using a dynamic model, indicating improved modeling accuracy for bioprocessing.

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Yeboah et al. (2026) studied this question.

synapsesocial.com/papers/6a7d76d82b0e0cff3f64093d https://doi.org/10.1186/s13068-026-02805-y

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Trajectory-level dynamic validation of a phase-structured grey-box model for consolidated bioprocessing using literature-derived ethanol trajectories

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Trajectory-level dynamic validation of a phase-structured grey-box model for consolidated bioprocessing using literature-derived ethanol trajectories

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