Steps toward a digital twin for functional food production with increased health benefits

Lactobacillus rhamnosus (L. rhamnosus) is a commensal bacterium with health-promoting properties and with a wide range of applications within the food industry. To improve and optimize the control of L. rhamnosus biomass production in batch and fed-batch bioprocesses, this study proposes the application of artificial neural network (ANN) modelling to improve process control and monitoring, with potential future implementation as a basis for a digital twin. Three ANNs were developed using historical data from ten bioprocesses. These ANNs were designed to predict the biomass in batch bioprocesses with different media compositions, predict biomass in fed-batch bioprocesses, and predict the growth rate in fed-batch bioprocesses. The immunomodulatory effect of the L. rhamnosus samples was examined and found to elicit an anti-inflammatory response as evidenced by the inhibition of IL-6 and TNF-α secretion. Overall, the findings of this study reinforce the potential of ANN modelling for bioprocess optimization aimed at improved control for maximising the volumetric productivity of L. rhamnosus as an immunomodulatory agent with applications in the functional food industry.

• Publication year

  2023

• Venue

  Current Research in Food Science

• Publication date

  2023-09-01

• Fields of study

  Agricultural and Food Sciences, Medicine, Engineering

• Identifiers
  DOI 10.1016/j.crfs.2023.100593PMID 37790857PMCID 10543970
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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  2022influential reference
• Mechanistic and data-driven modeling of protein glycosylation

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• Bioprocess systems analysis, modeling, estimation, and control

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• Bioprocess Control: Current Progress and Future Perspectives

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  2020cited by this paper
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  2019influential reference
• Biotechnology and Bioengineering

  2019cited by this paper
• Accelerating Biologics Manufacturing by Upstream Process Modelling

  2019cited by this paper
• Fermentation

  2019cited by this paper
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  2018cited by this paper
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  2018cited by this paper
• Mechanistic Fermentation Models for Process Design, Monitoring, and Control.

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• A novel model‐based control strategy for aerobic filamentous fungal fed‐batch fermentation processes

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  2016cited by this paper
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  2014cited by this paper
• Antioxidant activity of an exopolysaccharide isolated from Lactobacillus plantarum C88.

  2013cited by this paper
• Development of a hybrid neural network model to predict feeding method in fed‐batch cultivation for enhanced recombinant streptokinase productivity in Escherichia coli

  2012cited by this paper
• Online monitoring of biomass accumulation in recombinant yeast cultures.

  2012cited by this paper
• Computer programs for modeling mammalian cell batch and fed-batch cultures using logistic equations

  2012cited by this paper
• Immunomodulatory and antioxidant potential of Lactobacillus exopolysaccharides.

  2011cited by this paper
• Strain engineering for improved expression of recombinant proteins in bacteria

  2011influential reference
• Evaluation of software sensors for on-line estimation of culture conditions in an Escherichia coli cultivation expressing a recombinant protein.

  2010cited by this paper
• Intermediate chains of exopolysaccharides from Lactobacillus rhamnosus RW‐9595M increase IL‐10 production by macrophages

  2010influential reference
• Review of the most common pre-processing techniques for near-infrared spectra

  2009cited by this paper
• Application of near‐infrared spectroscopy for monitoring and control of cell culture and fermentation

  2009cited by this paper
• Data reconciliation of concentration estimates from mid‐infrared and dielectric spectral measurements for improved on‐line monitoring of bioprocesses

  2009cited by this paper
• Control of continuous fed-batch fermentation process using neural network based model predictive controller

  2009cited by this paper
• Assessment of near infrared and “software sensor” for biomass monitoring and control

  2008cited by this paper
• Machine Learning and Its Applications to Biology

  2007cited by this paper
• Model based control of a yeast fermentation bioreactor using optimally designed artificial neural networks

  2007cited by this paper
• l-lactic acid production by Lactobacillus casei fermentation using different fed-batch feeding strategies

  2006cited by this paper
• G‐CSF‐mediated inhibition of JNK is a key mechanism for Lactobacillus rhamnosus‐induced suppression of TNF production in macrophages

  2006cited by this paper
• Effects of the oral administration of the exopolysaccharide produced by Lactobacillus kefiranofaciens on the gut mucosal immunity.

  2006cited by this paper
• Use of an artificial neural network in modeling yeast biomass and yield of β-glucan

  2005cited by this paper
• Artificial neural network model for transient crossflow microfiltration of polydispersed suspensions

  2005cited by this paper
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  2003cited by this paper
• Lactobacillus rhamnosus GG decreases TNF‐α production in lipopolysaccharide‐activated murine macrophages by a contact‐independent mechanism

  2003cited by this paper
• Effect of medium supplementation on exopolysaccharide production by Lactobacillus rhamnosus RW-9595M in whey permeate

  2002cited by this paper
• Combined Effects of Temperature and Medium Composition on Exopolysaccharide Production by Lactobacillusrhamnosus RW‐9595M in a Whey Permeate Based Medium

  2002cited by this paper
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  2002cited by this paper
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  2001cited by this paper
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  2000cited by this paper
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• Physiological approach to extracellular polysaccharide production by Lactobacillus rhamnosus strain C83

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• Optimization of Fed‐Batch Bioreactors Using Neural Network Parameter Function Models

  1996cited by this paper
• On‐line prediction of fermentation variables using neural networks

  1990cited by this paper
• Some mineral requirements of the lactic acid bacteria.

  1947cited by this paper

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