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Updated: Jun 18, 2026

Design of Solid-State Fermentation Systems for Polymer Hydrolytic Extracellular Enzyme Production by Filamentous Fungi
Published on: June 6, 2025
Acid protease production by solid-state fermentation using Aspergillus oryzae MTCC 5341: optimization of process
K S Vishwanatha1, A G Appu Rao, Sridevi Annapurna Singh
1Department of Protein Chemistry and Technology, Central Food Technological Research Institute, Mysore, India.
This study optimized solid-state fermentation of Aspergillus oryzae to maximize acid protease production. The optimized conditions yielded the highest reported acid protease activity, significantly improving upon previous findings.
Area of Science:
- Biotechnology
- Enzyme Production
- Microbial Fermentation
Background:
- Aspergillus oryzae MTCC 5341 produces extracellular acid proteases on wheat bran.
- Solid-state fermentation (SSF) is a key method for enzyme production.
- Optimization of SSF is crucial for maximizing enzyme yields.
Purpose of the Study:
- To optimize the solid-state fermentation (SSF) of Aspergillus oryzae MTCC 5341 for enhanced acid protease production.
- To identify optimal operating conditions for maximizing acid protease yield.
- To develop a predictive model for acid protease production using response-surface methodology.
Main Methods:
- Solid-state fermentation (SSF) of Aspergillus oryzae on wheat bran.
- Optimization of fermentation parameters including pH, temperature, defatted soy flour addition, and fermentation time.
- Application of response-surface methodology (RSM) for modeling and optimization.
Main Results:
- Initial optimization identified conditions (pH 5, 30°C, 4% defatted soy flour, 120 h) yielding 8.64 x 10^5 U/g bran.
- RSM predicted optimal levels (pH 5.4, 31°C, 4.4% defatted soy flour, 123 h) for maximum activity of 8.93 x 10^5 U/g bran.
- Experimental verification achieved 8.47 x 10^5 U/g bran, 94.8% of the predicted value, representing a four-fold increase over previous reports.
Conclusions:
- Optimized SSF conditions significantly enhance acid protease production by Aspergillus oryzae.
- The developed predictive model accurately forecasts enzyme production levels.
- This research reports the highest acid protease activity achieved to date using this microbial strain and substrate.
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