Adsorbed Carrier Solid-State Fermentation of Beauveria bassiana: Process Optimization and Growth Dynamics Modelization Based on an Improved Biomass Determination Method

To optimize and model the fermentation process of Beauveria bassiana, adsorbed carrier solid-state fermentation (ACSSF) was used with rice husk as the inert support. The sample pretreating method was improved by combining homogenization and ultrasonic treatment after dry crushing; the large particles (100–1000 μm in size) were broken and the content of small particles (2–100 μm in size) increased, and the relative standard deviation of the biomass detection method was as low as 3.32% (intra-day) and 3.75% (inter-day). The most suitable carbon source—cassava starch—and the most suitable nitrogen source—corn steep liquor powder (CSLP)—were screened from multiple carbon and nitrogen sources. Through single-factor optimization and an artificial neural network combining genetic algorithm optimization, the optimal recipe including cassava starch 0.0314 g·cm−3, CSLP 0.004885 g·cm−3 and water 0.2630 g·cm−3 was obtained, and the highest biomass yield was verified as 0.1379 g·cm−3, which was 45.0% higher than the original recipe before the optimization (0.0951 g·cm−3). The modeling of microbial growth was based on the Logistic model and executed by nonlinear regression with the R2 value as high as 0.9525 and absolute value of the residues completely under 0.003 g·cm−3, which validated not only the feasibility of modeling the growth kinetics of B. bassiana using total biomass content, but also the reliability of the improved biomass pretreating and determination method.