Statistical approach to optimize production of biosurfactant by Pseudomonas aeruginosa 2297.
The main objective of this paper is to optimize biosurfactant production by Pseudomonas aeruginosa 2297 with statistical approaches. Biosurfactant production from P. aeruginosa 2297 was carried out with different carbon sources, and maximum yield was achieved with sawdust followed by groundnut husk and glycerol. The produced biosurfactant has showed active emulsification and surface-active properties. From the kinetic growth modeling, the specific growth rate was calculated on sawdust and it was 1.12 day-1. The maximum estimated value of product yield on biomass growth (Yp/x) was 1.02 g/g. The important medium components identified by the Plackett-Burman method were sawdust and glycerol along with culture parameter pH. Box-Behnken response surface methodology was applied to optimize biosurfactant production. The obtained experimental result concludes that Box-Behnken designs are very effective statistical tools to improve biosurfactant production. These results may be useful to develop a high efficient production process of biosurfactant. In addition, this type of kinetic modeling approach may constitute a useful tool to design and scaling-up of bioreactors for the production of biosurfactant.
Applied Microbiology Laboratory, Department of Virology, Sri Venkateswara University, Tirupati, 517 502, India.
Arthala Praveen
AP
Kumar
Applied Microbiology Laboratory, Department of Virology, Sri Venkateswara University, Tirupati, 517 502, India.
Avilala
A
Janardhan
Applied Microbiology Laboratory, Department of Virology, Sri Venkateswara University, Tirupati, 517 502, India.
Seela
S
Radha
Applied Microbiology Laboratory, Department of Virology, Sri Venkateswara University, Tirupati, 517 502, India.
Buddolla
B
Viswanath
Applied Microbiology Laboratory, Department of Virology, Sri Venkateswara University, Tirupati, 517 502, India. gnsimha123@rediffmail.com.
Golla
G
Narasimha
Biosurfactant; Kinetic growth modeling; Plackett–Burman; Pseudomonas aeruginosa; Response surface methodology (RSM)