2012 ; 22(7):
|Author||C. K. M. Tripathi, Mahvish Khan, Vandana Praveen, Saif Khan, Akanksha Srivastava|
|Affiliation||Division of Fermentation Technology, C.S.I.R., Central Drug Research Institute, Lucknow 226001, India|
|Title||Enhanced Antibiotic Production by Streptomyces sindenensis Using Artificial Neural Networks Coupled with Genetic Algorithm and Nelder-Mead Downhill Simplex|
J. Microbiol. Biotechnol.2012 ; 22(7):
|Abstract||Antibiotic production with Streptomyces sindenensis MTCC
8122 was optimized under submerged fermentation
conditions by artificial neural network (ANN) coupled
with genetic algorithm (GA) and Nelder-Mead downhill
simplex (NMDS). Feed forward back-propagation ANN
was trained to establish the mathematical relationship
among the medium components and length of incubation
period for achieving maximum antibiotic yield. The
optimization strategy involved growing the culture with
varying concentrations of various medium components for
different incubation periods. Under non-optimized condition,
antibiotic production was found to be 95 μg/ml, which
nearly doubled (176 μg/ml) with the ANN-GA optimization.
ANN-NMDS optimization was found to be more efficacious,
and maximum antibiotic production (197 μg/ml) was
obtained by cultivating the cells with (g/l) fructose 2.7602,
MgSO4 1.2369, (NH4)2PO4 0.2742, DL-threonine 3.069%,
and soyabean meal 1.952%, for 9.8531 days of incubation,
which was roughly 12% higher than the yield obtained by
ANN coupled with GA under the same conditions.|
|Keywords||Streptomyces sindenensis, Antibiotic, Artificial neural networks, Genetic algorithm, Nelder mead downhill simplex|
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