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Plant Science Today (PST)

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Early Access

Maximizing enzyme production by standardizing process parameters through one factor at a time approach (OFAT) subjected to a statistical technique: Response surface methodology (RSM)

DOI
https://doi.org/10.14719/pst.8516
Submitted
26 March 2025
Published
05-11-2025
Versions

Abstract

Enzymes play an important role in many industrial processes such as biofuel production, paper and pulp processing, food processing and waste management. Due to their multiple significant applications, there is growing need for maximizing their production. Trichoderma sp. is known for its potent enzyme-producing capabilities, making it an attractive candidate for enzyme production through solid-state fermentation (SSF). This study aimed to enhance enzyme production by employing a two-phase optimization strategy.The initial phase employed the one factor at a time (OFAT) approach to identify key process parameters (pH, temperature and incubation time) influencing enzyme activity. In the subsequent phase, response surface methodology (RSM) was used for further optimization, involving 20 experiments to assess the combined effects of multiple factors. OFAT analysis revealed that the concentration of substrate and incubation period were the most influential factors affecting enzyme production. In contrast, pH and temperature had a moderate yet still significant impact. RSM was used to fine-tune these parameters, resulting in optimized pH 5.5, 30 °C temperature and 7 days of incubation. Under these optimized conditions, enzyme production was approximately doubled compared to the baseline levels achieved without optimization. The findings are particularly relevant for industries such as biofuel, paper and pulp and waste management, where efficient enzymatic processes are essential for operational success and environmental sustainability. The methodology demonstrated in this study offers a practical and efficient framework for process optimization in enzyme production, potentially applicable to a broad range of microbial and enzymatic systems.

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