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Background: This study targets to optimize and analyse the interactive effects of process variables for improved bioactive metabolite production using RSM and unstructured kinetic modelling by S. halotolerans VSM 2. Materials and Methods: RSM was applied to optimize the interactive effects of five variables, viz., time of incubation, pH, temperature, concentration of maltose and meat extract on bioactive metabolite production and its effect against the five responses viz., S. flexneri, S. marcescens, P. vulgaris, P. aeruginosa and E. coli. Models of Logistic and Luedeking-Piret were used to simulate the cellular increase and bioactive metabolite production. Results: RSM optimal conditions for the bioactive metabolite production recorded were incubation time (12days), pH (8), and temperature (250C), concentrations of maltose and meat extract (1 % w/v) (each). The effect of the bioactive metabolite produced (zone of inhibition) against the responses were found to be 17 mm for S. flexneri, 17 mm for S. marcescens, 16 mm for P. vulgaris, 17 mm for P. aeruginosa and 18 mm for E coli. The data obtained from experimental values are in close agreement with the predicted values of RSM. Model adequacy was evaluated using ANOVA variance where the quadratic effect of p<0.0001 which imply the significance of the model. The unstructured-, mathematicalkinetic models provided a better approximation of profiles of S. halotolerans VSM 2 growth, optimized media utilization and bioactive metabolite production. Conclusion: Optimization of the independent variables for the production of the bioactive metabolite using RSM by S. halotolerans VSM 2 and its effect against the five responses were documented. The predicted values are in good agreement with the experimental values. Unstructured models provided a better approximation of kinetic profiles for bioactive metabolite production by S. halotolerans VSM 2.

Improved Bioactive Metabolite Production by Saccharopolyspora halotolerans VSM-2 Using Response Surface Methodology and Unstructured Kinetic Modelling