Demand on producing pigment from natural sources is increasing due to the awareness of the dangers of synthetic materials in life. Because of the high cost growth medium of pigment production, various studies have been carried out to explore other types of medium which are less costly,
such as agricultural waste. This study focuses on the application of Genetic Algorithm (GA) in optimizing yellowish-orange pigment production (flexirubin) using bacteria Chryseobacterium artocarpi CECT 8497T . So far, the most preferred methods for empirical modelling
and optimization is response surface methodology (RSM). However, in last two decades, GA has come up as one of the most efficient method for the empirical modelling and optimization problems. This study focuses on optimizing multi-parameters medium fermentation (lactose, L-tryptophan and KH2PO4)
on flexirubin production from agricultural waste using GA. The predictive ability and sensitivity analysis of RSM and GA was proven by wet lab experiments. The results show GA gives better pigmentation yields with optimal fermentation concentrations.
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Response Surface Methodology
Document Type: Research Article
UTM Big Data Centre, Universiti Teknologi Malaysia, Skudai, 81310 Johor, Malaysia
Faculty of Science, Universiti Teknologi Malaysia, Skudai, 81310 Johor, Malaysia
October 1, 2018
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