Statistical optimization of medium components for biosurfactant production by Achromobacter xylos GSR21

Abstract

Introduction: Biosurfactants have picked up an impressive consideration as of late due to their potential uses in an expansive scope of use territories, including environmental remediation, agriculture, biofilm formation, quorum sensing, textile, pharmaceuticals, cosmetics, and the food, oil, and petrochemical industries. Aim: In the present study, optimization of the critical medium components for biosurfactant production by Achromobacter xylos strain GSR21 using statistical experimental design was studied. Materials and Methods: Response surface methodology (RSM) was employed to determine the optimal level of the four medium variables (agar powder, yeast extract, FeSO 4 7H 2 O, and KH 2 PO 4 ). Central composite design of RSM was applied to study the four variables at five levels, and biosurfactant concentration was measured as a response. Results: Regression coefficients were calculated by regression analysis and the model equation was determined. R 2 value for biosurfactant (g/L) was calculated as 72%, and it indicates that the model was well fitted with the experimental results. Surface plots were made, and the maximum biosurfactant production (A. xylos strain GSR21) (10.20 g/L) was predicted at the optimized values of agar powder 90 g/L, yeast extract 5 g/L, FeSO 4 7H 2 O 0.05 g/L, and KH 2 PO 4 0.15 g/L. The obtained mathematical model was verified by performing the experiment with the predicted optimized values, and the yield of bio-surfactant was found to be 9.69 g/L. Validation of the predicted model was fitted 96.9% with the experimental results conducted at the optimum conditions. Conclusion: Results of this statistical analysis showed that agar powder and yeast extract had found significant medium components for biosurfactant (A. xylos GSR21) production.