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Optimal feed profile for the Rhamnolipid kinetic models by using Tabu search: metabolic view point

Overview of attention for article published in AMB Express, November 2016
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Title
Optimal feed profile for the Rhamnolipid kinetic models by using Tabu search: metabolic view point
Published in
AMB Express, November 2016
DOI 10.1186/s13568-016-0279-8
Pubmed ID
Authors

J. Satya Eswari, Kannekanti kavya

Abstract

Rhamnolipids are bio surfactants which are extra-cellular glycolipids composed of L-rhamnose and 3-hydroxyalkanoics. Rhamnolipids are produced through fermentation process by using Pseudomonas sp. as the species. An alteration to the traditional procedures in order to achieve increase in the production of biosurfactants, a numerous process technologies have been adopted in fed batch mode. Fed batch mode facilitates the high production of product by avoiding the substrate or product inhibition line of attack. To overcome the controlling parameters which reduce the product yield, optimal control profiles are designed. In order to develop viable control methods for fed-batch fermentation of Rhamnolipid production, multiple substrate feeding strategies were employed and their efficiencies were compared with different substrates concentration of glucose, nitrogen and phosphorous. The product formation depends upon the substrate feeding strategy and so, the fed-batch fermentation was carried out by using P. aeruginosa providing substrates at manifold rates. With the obtained experimental data, using the kinetic models (logistic equation and by Luedeking Piret), the kinetic parameters were estimated. These kinetic parameters were implemented in tabu search algorithm and this programme was executed in Dev-C++, optimal control profiles were generated as a result. These obtained optimal control profiles have shown an increase in productivity of rhamnolipid with a decline in computational time. Through this procedure, the optimal control profiles of substrate feeding strategies of glucose, nitrogen and phosphorous were estimated. In comparison with other algorithms like genetic algorithm, Tabu Search algorithm was able to generate an accurate optimal control profiles with a reduction in their intricacy.

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The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 22 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 27%
Student > Master 3 14%
Student > Bachelor 3 14%
Other 2 9%
Researcher 2 9%
Other 2 9%
Unknown 4 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 7 32%
Biochemistry, Genetics and Molecular Biology 4 18%
Engineering 3 14%
Chemical Engineering 2 9%
Chemistry 1 5%
Other 0 0%
Unknown 5 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 16 November 2016.
All research outputs
#15,393,913
of 22,901,818 outputs
Outputs from AMB Express
#446
of 1,236 outputs
Outputs of similar age
#169,071
of 270,398 outputs
Outputs of similar age from AMB Express
#17
of 45 outputs
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We're also able to compare this research output to 45 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.