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Related Experiment Videos

Model for on-line moisture-content control during solid-state fermentation.

F J Nagel1, J Tramper, M S Bakker

  • 1Wageningen University, Department of Food Technology and Nutritional Sciences, Food and Bioprocess Engineering Group, P.O. Box 8129, 6700 EV Wageningen, The Netherlands.

Biotechnology and Bioengineering
|December 15, 2000
PubMed
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This study presents a validated model for estimating water content in wheat grains during solid-state fermentation (SSF) using Aspergillus oryzae. The model accurately predicts water levels, aiding in bioreactor control for optimal fungal cultivation.

Area of Science:

  • Biotechnology
  • Biochemical Engineering
  • Food Science

Background:

  • Solid-state fermentation (SSF) is crucial for producing enzymes and metabolites using fungi like Aspergillus oryzae on solid substrates such as wheat.
  • Accurate monitoring and control of water content are essential for optimizing SSF processes, influencing fungal growth, metabolism, and product yield.
  • Existing methods for water content estimation in SSF are often indirect or require offline measurements, limiting real-time process control.

Purpose of the Study:

  • To develop and validate a novel model for estimating extracellular and overall water content in wheat grains during Aspergillus oryzae SSF.
  • To utilize on-line measurements of gas phase components (O2, CO2, water vapor) for real-time water content prediction.
  • To validate the model's performance in different bioreactor scales and assess its utility for process control.

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Main Methods:

  • Development of a model based on elemental balances and gas phase measurements (O2, CO2, water vapor).
  • Determination of model parameters using a membrane-based experimental system mimicking A. oryzae growth on wheat.
  • Validation of the model using on-line measurements during SSF in laboratory-scale (1.5-L) and pilot-scale (35-L) bioreactors.

Main Results:

  • The model accurately predicted the overall water content of the fermenting solid substrate in both tested bioreactors.
  • Fungal biomass water content was found to be dependent on substrate moisture and lower than previously reported values.
  • The model successfully estimated substrate dry matter losses, metabolic water production, and water incorporated into biomass.

Conclusions:

  • The developed model provides a validated, non-invasive method for estimating water content during Aspergillus oryzae SSF on wheat.
  • The model's ability to predict water dynamics supports its application in controlling water addition for optimized bioreactor operation.
  • This approach enhances the understanding and control of water status in SSF, crucial for efficient fungal cultivation and metabolite production.