The modeling of fermentation processes within botanical systems poses a significant challenge due to their inherent complexity and variability. The need for efficient, accurate, and cost-effective computational models is imperative across various environmental applications. This study employs a Takagi-Sugeno fuzzy technique to model lipase activity production, utilizing key variables such as temperature, pH, inoculum, time, and agitation across 26 experimental setups. The performance of the fuzzy model is evaluated against traditional regression models, demonstrating superior predictive capabilities and potential for broader applications in environmental and botanical bioprocessing.

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