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Statistical optimization of Pseudomonas putida (ATCC 49128) growth: Process variables response in hypoxic shake flasks using response surface methodology

Ahmad, Mani Malam and Mohd Azoddien, Abd. Aziz and Mohd Zahari, Mior Ahmad Khusairi and Abu Seman, Mazrul Nizam and Jami, Mohammed Saedi (2018) Statistical optimization of Pseudomonas putida (ATCC 49128) growth: Process variables response in hypoxic shake flasks using response surface methodology. International Journal of Bio-Science and Bio-Technology, 10 (3). pp. 1-14. ISSN 2233-7849 E-ISSN 2208-9810

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Abstract

The modeling of Pseudomonas putida growth is facilitated due to its nonfastidious nature. This research was performed to develop a predictive model for the growth of P. putida in a shake flasks medium. Methods: A response surface methodology (RSM) was employed to predict the synergistic effects with a combination of nutrient concentration (4-16 g/l), agitation (140-200 rpm) and temperature (30-40 ºC) on P. putida (ATCC 49128) growth and cell biomass accumulation. The growth curves generated under different conditions were fitted using a nonlinear regression model equation. The relationship between the response and growth limiting variables were modelled using a face-centered central composite design (FCCCD) quadratic polynomial equation. Results: The predictive model was highly significant (p < 0.01), and the predicted values of the growth parameters obtained using the model equations were in agreement with the observed values (R2= 0.9840). The established model validation indices for describing the growth rate of P. putida were within the acceptable limit of bias (Bf) and accuracy factor (Af). Conclusion: Therefore, the predictive model further confirmed the versatility of P. putida to simple growth media within defined optimal physical operational parameters of simple batch mode.

Item Type: Article (Journal)
Additional Information: 90341/5545
Subjects: T Technology > TP Chemical technology > TP155 Chemical engineering
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Engineering > Department of Biotechnology Engineering
Kulliyyah of Engineering
Depositing User: Professor Dr. Mohammed Saedi Jami, PhD CEng MIChemE
Date Deposited: 20 Jun 2021 15:09
Last Modified: 20 Jun 2021 15:09
URI: http://irep.iium.edu.my/id/eprint/90341

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