Enhancing biosurfactant production by hypersaline Bacillus amyloliquefaciens SK27 using response surface methodology and genetic algorithm

Malik, R.; Kerkar, S.

dc.contributor.author	Malik, R.
dc.contributor.author	Kerkar, S.
dc.date.accessioned	2019-09-11T12:16:29Z
dc.date.available	2019-09-11T12:16:29Z
dc.date.issued	2019
dc.identifier.citation	Current Science. 117(5); 2019; 847-852.	en_US
dc.identifier.uri	https://www.currentscience.ac.in/Volumes/117/05/0847.pdf
dc.identifier.uri	http://irgu.unigoa.ac.in/drs/handle/unigoa/5844
dc.description.abstract	The use of biosurfactants has been limited because of their low yield and high production cost. A central composite design was used to study the interactive effect of sucrose, yeast extract and sodium chloride which were the most influencing variables. Response surface analysis showed that the quadratic model with R sup(2) value of 0.9983 was fit for biosurfactant production. When genetic algorithm was used for maximization, the optimal activity (oil displacement zone) was found close to that obtained by response surface methodology, both of which were close to the predicted value. Biosurfactant production was enhanced by 1.2- fold using these approaches.	en_US
dc.publisher	Current Science Association	en_US
dc.subject	Biotechnology	en_US
dc.title	Enhancing biosurfactant production by hypersaline Bacillus amyloliquefaciens SK27 using response surface methodology and genetic algorithm	en_US
dc.type	Journal article	en_US
dc.identifier.impf	y