Nutrients interaction investigation to improve Monascus purpureus FTC5391 growth rate using response surface methodology and artificial neural network
Aims: Two vital factors, certain environmental conditions and nutrients as a source of energy are entailed for successful growth and reproduction of microorganisms. Manipulation of nutritional requirement is the simplest and most effectual strategy to stimulate and enhance the activity of microorgan...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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Malaysian Society for Microbiology
2013
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| Online Access: | http://psasir.upm.edu.my/id/eprint/28079/ http://psasir.upm.edu.my/id/eprint/28079/1/Nutrients%20interaction%20investigation%20to%20improve%20Monascus%20purpureus%20FTC5391%20growth%20rate%20using%20response%20surface%20methodology%20and%20artificial%20neural%20network.pdf |
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| author | Ajdari, Zahra Ebrahimpour, Afshin Abdul Manan, Musaalbakri Ajdari, Daniel Abbasiliasi, Sahar Hamid, Muhajir Mohamad, Rosfarizan Ariff, Arbakariya |
| author_facet | Ajdari, Zahra Ebrahimpour, Afshin Abdul Manan, Musaalbakri Ajdari, Daniel Abbasiliasi, Sahar Hamid, Muhajir Mohamad, Rosfarizan Ariff, Arbakariya |
| author_sort | Ajdari, Zahra |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | Aims: Two vital factors, certain environmental conditions and nutrients as a source of energy are entailed for successful growth and reproduction of microorganisms. Manipulation of nutritional requirement is the simplest and most effectual strategy to stimulate and enhance the activity of microorganisms. Methodology and Results: In this study, response surface methodology (RSM) and artificial neural network (ANN) were employed to optimize the carbon and nitrogen sources in order to improve growth rate of Monascus purpureus FTC5391, a new local isolate. The best models for optimization of growth rate were a multilayer full feed-forward incremental back propagation network, and a modified response surface model using backward elimination. The optimum condition for cell mass production was: sucrose 2.5%, yeast extract 0.045%, casamino acid 0.275%, sodium nitrate 0.48%, potato starch 0.045%, dextrose 1%, potassium nitrate 0.57%. The experimental cell mass production using this optimal condition was 21 mg/plate/12days, which was 2.2-fold higher than the standard condition (sucrose 5%, yeast extract 0.15%, casamino acid 0.25%, sodium nitrate 0.3%, potato starch 0.2%, dextrose 1%, potassium nitrate 0.3%). Conclusion, significance and impact of study: The results of RSM and ANN showed that all carbon and nitrogen sources tested had significant effect on growth rate (P-value < 0.05). In addition the use of RSM and ANN alongside each other provided a proper growth prediction model. |
| first_indexed | 2025-11-15T08:56:00Z |
| format | Article |
| id | upm-28079 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T08:56:00Z |
| publishDate | 2013 |
| publisher | Malaysian Society for Microbiology |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-280792016-06-20T03:06:41Z http://psasir.upm.edu.my/id/eprint/28079/ Nutrients interaction investigation to improve Monascus purpureus FTC5391 growth rate using response surface methodology and artificial neural network Ajdari, Zahra Ebrahimpour, Afshin Abdul Manan, Musaalbakri Ajdari, Daniel Abbasiliasi, Sahar Hamid, Muhajir Mohamad, Rosfarizan Ariff, Arbakariya Aims: Two vital factors, certain environmental conditions and nutrients as a source of energy are entailed for successful growth and reproduction of microorganisms. Manipulation of nutritional requirement is the simplest and most effectual strategy to stimulate and enhance the activity of microorganisms. Methodology and Results: In this study, response surface methodology (RSM) and artificial neural network (ANN) were employed to optimize the carbon and nitrogen sources in order to improve growth rate of Monascus purpureus FTC5391, a new local isolate. The best models for optimization of growth rate were a multilayer full feed-forward incremental back propagation network, and a modified response surface model using backward elimination. The optimum condition for cell mass production was: sucrose 2.5%, yeast extract 0.045%, casamino acid 0.275%, sodium nitrate 0.48%, potato starch 0.045%, dextrose 1%, potassium nitrate 0.57%. The experimental cell mass production using this optimal condition was 21 mg/plate/12days, which was 2.2-fold higher than the standard condition (sucrose 5%, yeast extract 0.15%, casamino acid 0.25%, sodium nitrate 0.3%, potato starch 0.2%, dextrose 1%, potassium nitrate 0.3%). Conclusion, significance and impact of study: The results of RSM and ANN showed that all carbon and nitrogen sources tested had significant effect on growth rate (P-value < 0.05). In addition the use of RSM and ANN alongside each other provided a proper growth prediction model. Malaysian Society for Microbiology 2013 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/28079/1/Nutrients%20interaction%20investigation%20to%20improve%20Monascus%20purpureus%20FTC5391%20growth%20rate%20using%20response%20surface%20methodology%20and%20artificial%20neural%20network.pdf Ajdari, Zahra and Ebrahimpour, Afshin and Abdul Manan, Musaalbakri and Ajdari, Daniel and Abbasiliasi, Sahar and Hamid, Muhajir and Mohamad, Rosfarizan and Ariff, Arbakariya (2013) Nutrients interaction investigation to improve Monascus purpureus FTC5391 growth rate using response surface methodology and artificial neural network. Malaysian Journal of Microbiology, 9 (1). pp. 68-83. ISSN 1823-8262; ESSN: 2231-7538 http://mjm.usm.my/index.php?r=cms/entry/view&id=83&slug=archive |
| spellingShingle | Ajdari, Zahra Ebrahimpour, Afshin Abdul Manan, Musaalbakri Ajdari, Daniel Abbasiliasi, Sahar Hamid, Muhajir Mohamad, Rosfarizan Ariff, Arbakariya Nutrients interaction investigation to improve Monascus purpureus FTC5391 growth rate using response surface methodology and artificial neural network |
| title | Nutrients interaction investigation to improve Monascus purpureus FTC5391 growth rate using response surface methodology and artificial neural network |
| title_full | Nutrients interaction investigation to improve Monascus purpureus FTC5391 growth rate using response surface methodology and artificial neural network |
| title_fullStr | Nutrients interaction investigation to improve Monascus purpureus FTC5391 growth rate using response surface methodology and artificial neural network |
| title_full_unstemmed | Nutrients interaction investigation to improve Monascus purpureus FTC5391 growth rate using response surface methodology and artificial neural network |
| title_short | Nutrients interaction investigation to improve Monascus purpureus FTC5391 growth rate using response surface methodology and artificial neural network |
| title_sort | nutrients interaction investigation to improve monascus purpureus ftc5391 growth rate using response surface methodology and artificial neural network |
| url | http://psasir.upm.edu.my/id/eprint/28079/ http://psasir.upm.edu.my/id/eprint/28079/ http://psasir.upm.edu.my/id/eprint/28079/1/Nutrients%20interaction%20investigation%20to%20improve%20Monascus%20purpureus%20FTC5391%20growth%20rate%20using%20response%20surface%20methodology%20and%20artificial%20neural%20network.pdf |