Enhanced lipase production from a ternary substrate mix of agricultural residues: A case of optimization of microbial inducers and global sensitivity analysis
An optimally formulated ternary substrate mix was utilized for lipase production.
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Microbial induction of lipase production was modelled and optimized using RSM and ANN.
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ANN showed better predictions compared with RSM.
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Olive oil had the most significant impact on lipase production.
Abstract
In this study, a ternary substrate mix made up of coconut pulp waste, banana peels and pineapple peels was optimally formulated to produce lipase. The optimum mix of coconut pulp waste (7.46 g), banana peels (0.01 g) and pineapple peels (7.53 g) gave a maximum lipase activity of 339.4 U/gds. The effect of inducers (castor oil, jatropha oil and olive oil) on lipase production from the substrate mix was investigated using response surface methodology (RSM) and artificial neural networks (ANN). ANN predictions were marginally superior to those of RSM. Optimized levels of castor oil (1.99%w/w), jatropha oil (0.02%w/w) and olive oil (1.99%w/w) yielded a maximum lipase activity of 488.7 U/gds which was a 30.6% increase compared to the un-induced system. Global sensitivity analysis revealed that olive oil was the most sensitive inducer. Thus, biological induction can enhance the production of lipase from the ternary substrate mix.
