| Revista: | Brazilian archives of biology and technology |
| Base de datos: | PERIÓDICA |
| Número de sistema: | 000372619 |
| ISSN: | 1516-8913 |
| Autors: | Meena, Ganga Sahay1 Kumar, Nitin1 Majumdar, Gautam Chandra1 Banerjee, Rintu1 Meena, Pankaj Kumar2 Yadav, Vijesh2 |
| Institucions: | 1Indian Institute of Technology, Department of Agricultural and Food Engineering, Kharagpur. India 2National Dairy Research Institute, Dairy Technology Division, Karnal, Haryana. India |
| Any: | 2014 |
| Període: | Ene-Feb |
| Volum: | 57 |
| Número: | 1 |
| Paginació: | 15-22 |
| País: | Brasil |
| Idioma: | Inglés |
| Tipo de documento: | Artículo |
| Enfoque: | Experimental |
| Resumen en inglés | 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 genetic algorithms (GA). The normalized percentage mean squared error obtained from the ANN and RSM models were 0.06 and 0.2%, respectively. The results demonstrated a higher prediction accuracy of ANN compared to RSM |
| Disciplines | Biología, Química, Matemáticas |
| Paraules clau: | Bacterias, Bioquímica, Matemáticas aplicadas, Metodología de superficie de respuesta, Redes neuronales artificiales, Algoritmos genéticos, Diseño de Box-Behnken |
| Keyword: | Biology, Chemistry, Mathematics, Bacteria, Biochemistry, Applied mathematics, Response surface methodology, Artificial neural networks, Genetic algorithms, Box-Behnken design |
| Text complet: | Texto completo (Ver PDF) |
