Improvement of a two - stage fermentation process for docosahexaenoic acid production by Aurantiochytrium limacinum SR21 applying statistical experimental designs and data analysis
Statistical screening experimental designs were applied to identify the significant culture variables for biomass production of Aurantiochytrium limacinum SR21 and their optimal levels were found using a combination of Artificial Neural Networks, genetic algorithms and graphical analysis. The biomass value obtained [40.3 g cell dry weight l-1] employing the selected culture conditions agreed with that predicted by the model. Subsequently, two significant culture conditions for docosahexaenoic acid [DHA] production were determined, finding that an inoculum of 10 percent [v/v], obtained from the previous [statistically optimized] stage, should be used in a DHA production medium having a molar C:N ratio of 55:1, to reach a production of 7.8 g DHA l-1 d-1. The production step was thereafter scaled in a 3.5 l bioreactor, and DHA productivity of 3.7 g l-1 d-1 was obtained. This two-stage strategy: statistically optimized inoculum production [fist step] and a DHA production step, is presented for the first time to optimize a bioprocess conducive to the obtention of microbial DHA.
| Main Authors: | , , , |
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| Format: | Texto biblioteca |
| Language: | eng |
| Subjects: | ARTIFICIAL NEURAL NETWORKS, AURANTIOCHYTRIUM, DOCOSAHEXAENOIC ACID, STATISTICAL DESIGNS, TWO-STAGE FERMENTATION, BIOMASS, BIOREACTOR, BIOTECHNOLOGY, CULTURE MEDIUM, EUKARYOTE, FERMENTATION, GROWTH, DEVELOPMENT AND AGING, METABOLISM, METHODOLOGY, MICROBIOLOGY, PHYSIOLOGY, REPRODUCIBILITY, STATISTICAL MODEL, STATISTICS, CULTURE MEDIA, EUKARYOTA, MODELS, STATISTICAL, REPRODUCIBILITY OF RESULTS, STATISTICS AS TOPIC, |
| Online Access: | http://ceiba.agro.uba.ar/cgi-bin/koha/opac-detail.pl?biblionumber=46542 |
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