Growth Characteristics Modeling of Lactobacillus casei Using Response Surface Methodology

Abstract

Different conditions viz. additional carbon and nitrogen content, temperature and pH of growth medium as well as inoculum size and age of Lactobacillus casei culture were optimized using response surface methodology (RSM) to maximize the growth of L. casei. Kinetic growth models were fitted for the cultivations using a Box-Benkhan design (BBD) for different independent variables. This unique concept of combining the optimization and modeling resulted in different optimal conditions for L. casei growth rather than its one variable at-a-time (OVAT) optimization study. Through this statistical tools, the product yield (cell mass) of the L. casei was increased. Developed models have Regression coefficients (R²) values as 0.9760 and 0.9900 for L. casei growth and reduction in pH of MRS broth, respectively. The optimum conditions for the maximum L. casei growth were at temperature 34.20^°C, pH 6.99, inoculum volume 1.89 mL, inoculum age 12 h, carbon content 0.30% (w/v), and nitrogen content 0.14% (w/v). Optimization of different independent variables resulted in 68×10⁸ CFU/ml, increase in the counts of L. casei compared to control media. Results demonstrated that RSM is better than OVAT method for the optimization of studied independent variables to maximize the growth of L. casei.