Growth characteristics modeling of Bifidobacterium bifidum using RSM and ANN
| Autor: | Rintu Banerjee, Suneel Gupta, Ganga Sahay Meena, G.C. Majumdar |
|---|---|
| Rok vydání: | 2011 |
| Předmět: |
Multidisciplinary
Bifidobacterium bifidum Mean squared error ved/biology business.industry Probiotics lcsh:Biotechnology ved/biology.organism_classification_rank.species Fractional factorial design artificial neural network (ANN) Biotechnology response surface methodology (RSM) Volume (thermodynamics) genetic algorithms (GA) lcsh:TP248.13-248.65 Yield (chemistry) Statistics Linear regression Probiotic bacteria Response surface methodology business FFD Mathematics |
| Zdroj: | Brazilian Archives of Biology and Technology, Vol 54, Iss 6, Pp 1357-1366 (2011) Brazilian Archives of Biology and Technology v.54 n.6 2011 Brazilian Archives of Biology and Technology Instituto de Tecnologia do Paraná (Tecpar) instacron:TECPAR Brazilian Archives of Biology and Technology, Volume: 54, Issue: 6, Pages: 1357-1366, Published: DEC 2011 |
| ISSN: | 1516-8913 |
| DOI: | 10.1590/s1516-89132011000600023 |
| Popis: | The aim of this work was to optimize the biomass production by Bifidobacterium bifidum 255 using the response surface methodology (RSM) and artificial neural network (ANN) both coupled with GA. To develop the empirical model for the yield of probiotic bacteria, additional carbon and nitrogen content, inoculum size, age, temperature and pH were selected as the parameters. Models were developed using ¼ fractional factorial design (FFD) of the experiments with the selected parameters. The normalized percentage mean squared error obtained from the ANN and RSM models were 0.05 and 0.1%, respectively. Regression coefficient (R²) of the ANN model showed higher prediction accuracy compared to that of the RSM model. The empirical yield model (for both ANN and RSM) obtained were utilized as the objective functions to be maximized with the help of genetic algorithm. The optimal conditions for the maximal biomass yield were 37.4 °C, pH 7.09, inoculum volume 1.97 ml, inoculum age 58.58 h, carbon content 41.74% (w/v), and nitrogen content 46.23% (w/v). The work reported is a novel concept of combining the statistical modeling and evolutionary optimization for an improved yield of cell mass of B. bifidum 255. |
| Databáze: | OpenAIRE |
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