title: Optimization of cultural conditions using response surface methodology versus artificial neural network and modeling of L-glutaminase production by Bacillus cereus MTCC 1305.
abstract: Response surface methodology and artificial neural network were used to optimize cultural conditions of L-glutaminase production from Bacillus cereus MTCC 1305. ANN model was superior to RSM model with higher value of coefficient of determination (99.97ANN>97.78RSM), predicted distribution coefficient (0.9992ANN>0.896RSM) and lower value of absolute average deviation (1.17%ANN<18.47%RSM). Optimum cultural conditions predicted by ANN were pH (7.5), fermentation time (40 h), temperature (34°C), inoculum size (2%), inoculum age (10 h) and agitation speed (175 rpm) with a maximum predicted production of L-glutaminase 666.97 U/l which was close to experimental production of L-glutaminase 667.23 U/l at simulated optimum cultural condition. The production of L-glutaminase was enhanced by 1.58-fold after optimization of cultural conditions. Simple kinetic models were developed using Logistic equation for cell growth, Luedeking Piret equation for L-glutaminase production and modified Luedeking Piret equation for glucose utilization indicating that L-glutaminase fermentation is non growth associated process.
authors.affiliation: School of Biochemical Engineering, Indian Institute of Technology (BHU), Varanasi, India.
authors.forename: Priyanka
authors.initials: P
authors.lastname: Singh
authors.forename: Shailendra Singh
authors.initials: SS
authors.lastname: Shera
authors.forename: Jaba
authors.initials: J
authors.lastname: Banik
authors.forename: Rathindra Mohan
authors.initials: RM
authors.lastname: Banik
mesh_terms: D001409:Bacillus cereus / Q000201:enzymology*; D018533:Biomass; D018929:Cell Culture Techniques; D005285:Fermentation; D005972:Glutaminase / Q000096:biosynthesis*; D007700:Kinetics; D008954:Models, Biological; D016571:Neural Networks, Computer
chemical_list: D005972:Glutaminase