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| Meena,Ganga Sahay; Kumar,Nitin; Majumdar,Gautam Chandra; Banerjee,Rintu; Meena,Pankaj Kumar; Yadav,Vijesh. |
| The culture conditions viz. additional carbon and nitrogen content, inoculum size, age, temperature and pH of Lactobacillus acidophilus were optimized using response surface methodology (RSM) and artificial neural network (ANN). Kinetic growth models were fitted to cultivations from a Box-Behnken Design (BBD) design experiments for different variables. This concept of combining the optimization and modeling presented different optimal conditions for L. acidophilus growth from their original optimization study. Through these statistical tools, the product yield (cell mass) of L. acidophilus was increased. Regression coefficients (R²) of both the statistical tools predicted that ANN was better than RSM and the regression equation was solved with the help of... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Response surface methodology (RSM); Artificial neural network (ANN); Genetic algorithms (GA); Box-behnken besign (BBD). |
| Ano: 2014 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1516-89132014000100003 |
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