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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4327757/ https://www.ncbi.nlm.nih.gov/pubmed/28324363 http://dx.doi.org/10.1007/s13205-014-0203-3 |
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author | Kumar, Arthala Praveen Janardhan, Avilala Radha, Seela Viswanath, Buddolla Narasimha, Golla |
author_facet | Kumar, Arthala Praveen Janardhan, Avilala Radha, Seela Viswanath, Buddolla Narasimha, Golla |
author_sort | Kumar, Arthala Praveen |
collection | PubMed |
description | 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 (Y (p/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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s13205-014-0203-3) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4327757 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-43277572015-02-19 Statistical approach to optimize production of biosurfactant by Pseudomonas aeruginosa 2297 Kumar, Arthala Praveen Janardhan, Avilala Radha, Seela Viswanath, Buddolla Narasimha, Golla 3 Biotech Original Article 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 (Y (p/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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s13205-014-0203-3) contains supplementary material, which is available to authorized users. Springer Berlin Heidelberg 2014-03-08 2015-02 /pmc/articles/PMC4327757/ /pubmed/28324363 http://dx.doi.org/10.1007/s13205-014-0203-3 Text en © The Author(s) 2014 https://creativecommons.org/licenses/by/4.0/ Open AccessThis article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited. |
spellingShingle | Original Article Kumar, Arthala Praveen Janardhan, Avilala Radha, Seela Viswanath, Buddolla Narasimha, Golla Statistical approach to optimize production of biosurfactant by Pseudomonas aeruginosa 2297 |
title | Statistical approach to optimize
production of biosurfactant by Pseudomonas
aeruginosa 2297 |
title_full | Statistical approach to optimize
production of biosurfactant by Pseudomonas
aeruginosa 2297 |
title_fullStr | Statistical approach to optimize
production of biosurfactant by Pseudomonas
aeruginosa 2297 |
title_full_unstemmed | Statistical approach to optimize
production of biosurfactant by Pseudomonas
aeruginosa 2297 |
title_short | Statistical approach to optimize
production of biosurfactant by Pseudomonas
aeruginosa 2297 |
title_sort | statistical approach to optimize
production of biosurfactant by pseudomonas
aeruginosa 2297 |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4327757/ https://www.ncbi.nlm.nih.gov/pubmed/28324363 http://dx.doi.org/10.1007/s13205-014-0203-3 |
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