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Optimization of parameters for the production of biodiesel from rubber seed oil using onsite lipase by response surface methodology.

ABSTRACT: In the present study, we demonstrate the properties of rubber seed oil (RSO) and its potential application for producing biodiesel by lipase-catalyzed transesterification. Rubber seed contains 39.45% of oil on a dry weight basis. Lipase was secreted from novel bacterial isolate of Pseudomonas aeruginosa strain BUP2. Response Surface Methodology (RSM) cum Box-Behnken Design (BBD) was employed to optimize the combined effect of different independent parameters namely oil-methanol ratio, enzyme unit, reaction temperature and reaction time. Biodiesel yield of 99.52% was obtained in the validation experiments at the optimal level of lipase (750 U), methanol ratio (1:10), temperature (45 °C) and time (4 h). The fuel properties of biodiesel obtained under the validation condition met the specifications as mentioned in ASTM D6751 and EN 14214 standards. Biodiesel aliquots were characterized using thin-layer chromatography (TLC), gas chromatography (GC), fourier transform infra-red spectroscopy (FTIR) and elemental analysis. The present study demonstrates an important application of a potential substitute for fossil fuel from raw feedstocks with high economic value.

SUBMITTER: Panichikkal AF

PROVIDER: S-EPMC6199197 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature

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Optimization of parameters for the production of biodiesel from rubber seed oil using onsite lipase by response surface methodology.

Panichikkal Abdul Faisal AF Prakasan Priji P Kizhakkepowathial Nair Unni U Kulangara Valappil Mohanan M

3 Biotech 20181023 11

In the present study, we demonstrate the properties of rubber seed oil (RSO) and its potential application for producing biodiesel by lipase-catalyzed transesterification. Rubber seed contains 39.45% of oil on a dry weight basis. Lipase was secreted from novel bacterial isolate of <i>Pseudomonas aeruginosa</i> strain BUP2. Response Surface Methodology (RSM) <i>cum</i> Box-Behnken Design (BBD) was employed to optimize the combined effect of different independent parameters namely oil-methanol rat ...[more]

PMID: 30370200

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Project description:Thermostable bacterial lipases occupy a place of prominence among biocatalysts owing to their novel, multifold applications and resistance to high temperature and other operational conditions. The capability of lipases to catalyze a variety of novel reactions in both aqueous and nonaqueous media presents a fascinating field for research, creating interest to isolate novel lipase producers and optimize lipase production. The most important stages in a biological process are modeling and optimization to improve a system and increase the efficiency of the process without increasing the cost.Different production media were tested for lipase production by a newly isolated thermophilic Geobacillus sp. strain ARM (DSM 21496 = NCIMB 41583). The maximum production was obtained in the presence of peptone and yeast extract as organic nitrogen sources, olive oil as carbon source and lipase production inducer, sodium and calcium as metal ions, and gum arabic as emulsifier and lipase production inducer. The best models for optimization of culture parameters were achieved by multilayer full feedforward incremental back propagation network and modified response surface model using backward elimination, where the optimum condition was: growth temperature (52.3 degrees C), medium volume (50 ml), inoculum size (1%), agitation rate (static condition), incubation period (24 h) and initial pH (5.8). The experimental lipase activity was 0.47 Uml(-1) at optimum condition (4.7-fold increase), which compared well to the maximum predicted values by ANN (0.47 Uml(-1)) and RSM (0.476 Uml(-1)), whereas R2 and AAD were determined as 0.989 and 0.059% for ANN, and 0.95 and 0.078% for RSM respectively.Lipase production is the result of a synergistic combination of effective parameters interactions. These parameters are in equilibrium and the change of one parameter can be compensated by changes of other parameters to give the same results. Though both RSM and ANN models provided good quality predictions in this study, yet the ANN showed a clear superiority over RSM for both data fitting and estimation capabilities. On the other hand, ANN has the disadvantage of requiring large amounts of training data in comparison with RSM. This problem was solved by using statistical experimental design, to reduce the number of experiments.

Dataset Information

Optimization of parameters for the production of biodiesel from rubber seed oil using onsite lipase by response surface methodology.

Publications

Optimization of parameters for the production of biodiesel from rubber seed oil using onsite lipase by response surface methodology.

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