Parameter Estimation and Model Comparison for Mixed Substrate Biomass Fermentation

Most industrial fermentations in food and drink use a single, high purity sugar as a substrate. These pure substrates are more expensive and less sustainable than mixed substrates, that can be derived from agricultural byproducts such as straw. However, use of mixed substrates in fermentation leads to challenging modelling and parameter estimation problems, particularly when much academic research, intended to inform industrial applications, uses batch fermentations, while large-scale fermentation is usually continuous, thanks to its cost and productivity advantages. Our findings highlight key challenges in using batch-derived experimental data to inform models of the continuous fermentation processes used at industrial scale. Extrapolating from data obtained in batch to continuous fermentation is risky, as models with near-equivalent data-fit and predictions in a batch context give very different predictions for continuous culture. For continuous fermentations to switch to mixed substrates, we need to improve understanding of dual substrate growth in continuous fermentation, to allow for optimised process design and operation.

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Publication Details

Journal
Systems and Control Transactions
Published
2025-06-30
DOI
https://doi.org/10.69997/sct.162971
Primary Topic
Biofuel production and bioconversion
Type
article
Field-Weighted Citation Impact
0.00

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article

Parameter Estimation and Model Comparison for Mixed Substrate Biomass Fermentation

Miao Guo, Tom Vinestock
Systems and Control Transactions
Biofuel production and bioconversion
article

Parameter Estimation and Model Comparison for Mixed Substrate Biomass Fermentation

Miao Guo, Tom Vinestock
article en

Abstract

Most industrial fermentations in food and drink use a single, high purity sugar as a substrate. These pure substrates are more expensive and less sustainable than mixed substrates, that can be derived from agricultural byproducts such as straw. However, use of mixed substrates in fermentation leads to challenging modelling and parameter estimation problems, particularly when much academic research, intended to inform industrial applications, uses batch fermentations, while large-scale fermentation is usually continuous, thanks to its cost and productivity advantages. Our findings highlight key challenges in using batch-derived experimental data to inform models of the continuous fermentation processes used at industrial scale. Extrapolating from data obtained in batch to continuous fermentation is risky, as models with near-equivalent data-fit and predictions in a batch context give very different predictions for continuous culture. For continuous fermentations to switch to mixed substrates, we need to improve understanding of dual substrate growth in continuous fermentation, to allow for optimised process design and operation.

Systems and Control TransactionsVol. 4
King's College London (GB)
Biotechnology and Biological Sciences Research Council
Openalex Percentile: Top 86%
Biofuel production and bioconversion
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