Comparative Analyses of Response Surface Methodology and Artificial Neural Network on Medium Optimization for Tetraselmis sp. FTC209 Grown under Mixotrophic Condition
Mixotrophic metabolism was evaluated as an option to augment the growth and lipid production of marine microalga Tetraselmis sp. FTC 209. In this study, a five-level three-factor central composite design (CCD) was implemented in order to enrich the W-30 algal growth medium. Response surface methodol...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2013-01-01
|
| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2013/948940 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832552321367670784 |
|---|---|
| author | Mohd Shamzi Mohamed Joo Shun Tan Rosfarizan Mohamad Mohd Noriznan Mokhtar Arbakariya B. Ariff |
| author_facet | Mohd Shamzi Mohamed Joo Shun Tan Rosfarizan Mohamad Mohd Noriznan Mokhtar Arbakariya B. Ariff |
| author_sort | Mohd Shamzi Mohamed |
| collection | DOAJ |
| description | Mixotrophic metabolism was evaluated as an option to augment the growth and lipid production of marine microalga Tetraselmis sp. FTC 209. In this study, a five-level three-factor central composite design (CCD) was implemented in order to enrich the W-30 algal growth medium. Response surface methodology (RSM) was employed to model the effect of three medium variables, that is, glucose (organic C source), NaNO3 (primary N source), and yeast extract (supplementary N, amino acids, and vitamins) on biomass concentration, Xmax, and lipid yield, Pmax/Xmax. RSM capability was also weighed against an artificial neural network (ANN) approach for predicting a composition that would result in maximum lipid productivity, Prlipid. A quadratic regression from RSM and a Levenberg-Marquardt trained ANN network composed of 10 hidden neurons eventually produced comparable results, albeit ANN formulation was observed to yield higher values of response outputs. Finalized glucose (24.05 g/L), NaNO3 (4.70 g/L), and yeast extract (0.93 g/L) concentration, affected an increase of Xmax to 12.38 g/L and lipid a accumulation of 195.77 mg/g dcw. This contributed to a lipid productivity of 173.11 mg/L per day in the course of two-week cultivation. |
| format | Article |
| id | doaj-art-cc8aef921ab04fe9a7f479a972563b71 |
| institution | Kabale University |
| issn | 1537-744X |
| language | English |
| publishDate | 2013-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-cc8aef921ab04fe9a7f479a972563b712025-02-03T05:59:00ZengWileyThe Scientific World Journal1537-744X2013-01-01201310.1155/2013/948940948940Comparative Analyses of Response Surface Methodology and Artificial Neural Network on Medium Optimization for Tetraselmis sp. FTC209 Grown under Mixotrophic ConditionMohd Shamzi Mohamed0Joo Shun Tan1Rosfarizan Mohamad2Mohd Noriznan Mokhtar3Arbakariya B. Ariff4Department of Bioprocess Technology, Faculty of Biotechnology and Biomolecular Sciences, Universiti Putra Malaysia, 43400 Serdang, Selangor, MalaysiaInstitute of Bioscience, Universiti Putra Malaysia, 43400 Serdang, Selangor, MalaysiaDepartment of Bioprocess Technology, Faculty of Biotechnology and Biomolecular Sciences, Universiti Putra Malaysia, 43400 Serdang, Selangor, MalaysiaDepartment of Process and Food Engineering, Faculty of Engineering, Universiti Putra Malaysia, 43400 Serdang, Selangor, MalaysiaDepartment of Bioprocess Technology, Faculty of Biotechnology and Biomolecular Sciences, Universiti Putra Malaysia, 43400 Serdang, Selangor, MalaysiaMixotrophic metabolism was evaluated as an option to augment the growth and lipid production of marine microalga Tetraselmis sp. FTC 209. In this study, a five-level three-factor central composite design (CCD) was implemented in order to enrich the W-30 algal growth medium. Response surface methodology (RSM) was employed to model the effect of three medium variables, that is, glucose (organic C source), NaNO3 (primary N source), and yeast extract (supplementary N, amino acids, and vitamins) on biomass concentration, Xmax, and lipid yield, Pmax/Xmax. RSM capability was also weighed against an artificial neural network (ANN) approach for predicting a composition that would result in maximum lipid productivity, Prlipid. A quadratic regression from RSM and a Levenberg-Marquardt trained ANN network composed of 10 hidden neurons eventually produced comparable results, albeit ANN formulation was observed to yield higher values of response outputs. Finalized glucose (24.05 g/L), NaNO3 (4.70 g/L), and yeast extract (0.93 g/L) concentration, affected an increase of Xmax to 12.38 g/L and lipid a accumulation of 195.77 mg/g dcw. This contributed to a lipid productivity of 173.11 mg/L per day in the course of two-week cultivation.http://dx.doi.org/10.1155/2013/948940 |
| spellingShingle | Mohd Shamzi Mohamed Joo Shun Tan Rosfarizan Mohamad Mohd Noriznan Mokhtar Arbakariya B. Ariff Comparative Analyses of Response Surface Methodology and Artificial Neural Network on Medium Optimization for Tetraselmis sp. FTC209 Grown under Mixotrophic Condition The Scientific World Journal |
| title | Comparative Analyses of Response Surface Methodology and Artificial Neural Network on Medium Optimization for Tetraselmis sp. FTC209 Grown under Mixotrophic Condition |
| title_full | Comparative Analyses of Response Surface Methodology and Artificial Neural Network on Medium Optimization for Tetraselmis sp. FTC209 Grown under Mixotrophic Condition |
| title_fullStr | Comparative Analyses of Response Surface Methodology and Artificial Neural Network on Medium Optimization for Tetraselmis sp. FTC209 Grown under Mixotrophic Condition |
| title_full_unstemmed | Comparative Analyses of Response Surface Methodology and Artificial Neural Network on Medium Optimization for Tetraselmis sp. FTC209 Grown under Mixotrophic Condition |
| title_short | Comparative Analyses of Response Surface Methodology and Artificial Neural Network on Medium Optimization for Tetraselmis sp. FTC209 Grown under Mixotrophic Condition |
| title_sort | comparative analyses of response surface methodology and artificial neural network on medium optimization for tetraselmis sp ftc209 grown under mixotrophic condition |
| url | http://dx.doi.org/10.1155/2013/948940 |
| work_keys_str_mv | AT mohdshamzimohamed comparativeanalysesofresponsesurfacemethodologyandartificialneuralnetworkonmediumoptimizationfortetraselmisspftc209grownundermixotrophiccondition AT jooshuntan comparativeanalysesofresponsesurfacemethodologyandartificialneuralnetworkonmediumoptimizationfortetraselmisspftc209grownundermixotrophiccondition AT rosfarizanmohamad comparativeanalysesofresponsesurfacemethodologyandartificialneuralnetworkonmediumoptimizationfortetraselmisspftc209grownundermixotrophiccondition AT mohdnoriznanmokhtar comparativeanalysesofresponsesurfacemethodologyandartificialneuralnetworkonmediumoptimizationfortetraselmisspftc209grownundermixotrophiccondition AT arbakariyabariff comparativeanalysesofresponsesurfacemethodologyandartificialneuralnetworkonmediumoptimizationfortetraselmisspftc209grownundermixotrophiccondition |