https://orcid.org/0000-0002-8895-1489
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ABSTRACT
In this paper, conventional response surface methodology (RSM) based on low-order polynomials and an alternative Kriging-based method are used for the model-based single and multi-objective optimization of fatty-acid methyl ester (FAME) production catalyzed by a novel crude lipase from the yeast Cryptococcus diffluens (D44). The coefficient of determination for the two modeling approaches was calculated as 0.97 for the Kriging method, and 0.86 for RSM; showing a more reliable representation of experimental data by Kriging. Both models were used to perform single (maximizing FAME titer and temporal productivity separately) and multi-objective (maximizing FAME titer and temporal productivity simultaneously) optimizations of four important operating conditions (reaction time and temperature; amount of crude enzyme; and volume of methanol used). In all cases, the highest temperature considered (60°C) gave the best results. A reduction of reaction time in half was seen to be necessary to achieve optimum productivity compared to titer, when the two objectives were considered separately. The observed trade-off between the two objectives was quantified via multi-objective optimization using Pareto-front analysis.
Acknowledgments
Funding was provided by Marmara University, Scientific Research Projects Committee (FEN-C-DRP-080415-0124). Ceyda KULA was supported by TUBITAK-BIDEB 2211 fellowship.
We would like to thank Prof. Dilek Kazan for her guidance and support with the analytical technicalities of the experiments.
Lyophilization process was carried out using freeze-dryer at Tubitak Marmara Research Center Genetic Eng&Bitech Institute.