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The Scientific World Journal
Volume 2013, Article ID 948940, 14 pages
http://dx.doi.org/10.1155/2013/948940
Research Article

Comparative Analyses of Response Surface Methodology and Artificial Neural Network on Medium Optimization for Tetraselmis sp. FTC209 Grown under Mixotrophic Condition

1Department of Bioprocess Technology, Faculty of Biotechnology and Biomolecular Sciences, Universiti Putra Malaysia, 43400 Serdang, Selangor, Malaysia
2Institute of Bioscience, Universiti Putra Malaysia, 43400 Serdang, Selangor, Malaysia
3Department of Process and Food Engineering, Faculty of Engineering, Universiti Putra Malaysia, 43400 Serdang, Selangor, Malaysia

Received 4 July 2013; Accepted 29 July 2013

Academic Editors: J. E. Barboza-Corona, C. W. Choi, S. Menoret, and N. Vassilev

Copyright © 2013 Mohd Shamzi Mohamed et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [16 citations]

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  • Zhou Lan, Chen Zhao, Weiqun Guo, Xiong Guan, and Xiaolin Zhang, “Optimization of culture medium for maximal production of spinosad using an artificial neural network - Genetic algorithm modeling,” Journal of Molecular Microbiology and Biotechnology, vol. 25, pp. 253–261, 2015. View at Publisher · View at Google Scholar
  • Muthusivaramapandian Muthuraj, Niharika Chandra, Basavaraj Palabhanvi, Vikram Kumar, and Debasish Das, “Process Engineering for High-Cell-Density Cultivation of Lipid Rich Microalgal Biomass of Chlorella sp FC2 IITG,” Bioenergy Research, vol. 8, no. 2, pp. 726–739, 2015. View at Publisher · View at Google Scholar
  • Pavan P. Jutur, and Asha A. Nesamma, “Genetic Engineering of Marine Microalgae to Optimize Bioenergy Production,” Handbook of Marine Microalgae, pp. 371–381, 2015. View at Publisher · View at Google Scholar
  • Fábio Coelho Sampaio, Tamara Lorena da Conceição Saraiva, Gabriel Dumont de Lima e Silva, Janaína Teles de Faria, Cristiano Grijó Pitangui, Bahar Aliakbarian, Patrizia Perego, and Attilio Converti, “Batch growth of Kluyveromyces lactis cells from deproteinized whey: Response surface methodology versus Artificial neural network—Genetic algorithm approach,” Biochemical Engineering Journal, vol. 109, pp. 305–311, 2016. View at Publisher · View at Google Scholar
  • K. Vivek, K.V. Subbarao, and B. Srivastava, “Optimization of postharvest ultrasonic treatment of kiwifruit using RSM,” Ultrasonics Sonochemistry, 2016. View at Publisher · View at Google Scholar
  • Yeshona Sewsynker-Sukai, Funmilayo Faloye, and Evariste Bosco Gueguim Kana, “Artificial neural networks: an efficient tool for modelling and optimization of biofuel production (a mini review),” Biotechnology & Biotechnological Equipment, pp. 1–15, 2016. View at Publisher · View at Google Scholar
  • Fábio Coelho Sampaio, Janaína Teles de Faria, Gabriel Dumond de Lima Silva, Ricardo Melo Gonçalves, Cristiano Grijó Pitangui, Alessandro Alberto Casazza, Saleh Al Arni, and Attilio Converti, “Comparison of Response Surface Methodology and Artificial Neural Network for Modeling Xylose-to-Xylitol Bioconversion,” Chemical Engineering & Technology, 2016. View at Publisher · View at Google Scholar
  • Norfarina Muhamad Nor, Mohd Shamzi Mohamed, Teck Chwen Loh, Hooi Ling Foo, Raha Abdul Rahim, Joo Shun Tan, and Rosfarizan Mohamad, “ Comparative analyses on medium optimization using one-factor-at-a-time , response surface methodology, and artificial neural network for lysine–methionine biosynthesis by Pediococcus pentosaceus RF-1 ,” Biotechnology & Biotechnological Equipment, pp. 1–13, 2017. View at Publisher · View at Google Scholar
  • Mouna Dammak, Bilel Hadrich, Ramzi Miladi, Mohamed Barkallah, Faiez Hentati, Ridha Hachicha, Céline Laroche, Philippe Michaud, Imen Fendri, and Slim Abdelkafi, “Effects of nutritional conditions on growth and biochemical composition of Tetraselmis sp.,” Lipids in Health and Disease, vol. 16, no. 1, 2017. View at Publisher · View at Google Scholar
  • M.C. Heinitz, C. Figueiredo Silva, C. Schulz, and A. Lemme, “ The effect of varying dietary digestible protein and digestible non-protein energy sources on growth, nutrient utilization efficiencies and body composition of carp ( Cyprinus carpio ) evaluated with a two-factorial central composite study design ,” Aquaculture Nutrition, 2017. View at Publisher · View at Google Scholar
  • Eric Bradford, Artur M. Schweidtmann, Dongda Zhang, Keju Jing, and Ehecatl Antonio del Rio-Chanona, “Dynamic modeling and optimization of sustainable algal production with uncertainty using multivariate Gaussian processes,” Computers & Chemical Engineering, 2018. View at Publisher · View at Google Scholar
  • Ping Pan, Weifeng Jin, Xiaohong Li, Yi Chen, Jiahui Jiang, Haitong Wan, and Daojun Yu, “Optimization of multiplex quantitative polymerase chain reaction based on response surface methodology and an artificial neural network-genetic algorithm approach,” Plos One, vol. 13, no. 7, pp. e0200962, 2018. View at Publisher · View at Google Scholar
  • Jihao Shi, Jingde Li, Hong Hao, Thong M. Pham, Yuan Zhu, and Guoming Chen, “Vented gas explosion overpressure prediction of obstructed cubic chamber by using newly developed Bayesian Regularization Artificial Neuron Network – Bauwens model,” Journal of Loss Prevention in the Process Industries, 2018. View at Publisher · View at Google Scholar
  • Radosław Winiczenko, Krzysztof Górnicki, Agnieszka Kaleta, Alex Martynenko, Monika Janaszek-Mańkowska, and Jędrzej Trajer, “Multi-objective optimization of convective drying of apple cubes,” Computers and Electronics in Agriculture, vol. 145, pp. 341–348, 2018. View at Publisher · View at Google Scholar
  • Vaibhav V. Goud, Atanu Kumar Paul, Venu Babu Borugadda, and Machhindra S. Bhalerao, “In situ epoxidation of waste soybean cooking oil for synthesis of biolubricant basestock: A process parameter optimization and comparison with RSM, ANN, and GA,” Canadian Journal of Chemical Engineering, 2018. View at Publisher · View at Google Scholar