Statistical Optimization of Culture Conditions for Enhanced Biomass Yield of Lactobacillus acidophilus CM1 Using Plackett-Burman and Response Surface Methodology.

Abstract

This study is aimed at enhancing the biomass yield of Lactobacillus acidophilus CM1 by identifying and optimizing critical growth parameters. Using the Plackett-Burman design (PBD), 11 physical and chemical variables were screened, of which pH, temperature, NaCl concentration, and inoculum size were found to significantly influence cell growth (p < 0.05). These statistically significant factors were subsequently optimized using response surface methodology (RSM) with a central composite design (CCD). Optimization led to a 1.45-fold increase in biomass yield, achieving a maximum of 1.948 g/100 mL. ANOVA confirmed model validity with an R ² of 0.9689 and adequate precision of 52.77, indicating a strong predictive capability. The integration of PBD and RSM-CCD proved efficient for minimizing experimental runs while maximizing output, supporting the development of cost-effective cultivation strategies for probiotic production. This approach offers a scalable model for bioprocess optimization in industrial fermentation.