Optimal Oil Extraction Research Articles

Infrared‐aided hot‐air drying of coconut: Impact on drying kinetics and quality metrics

AbstractThis study explored various drying techniques and temperatures to analyze their effects on the drying kinetics and quality of copra. The initial moisture content of coconut kernels was 50%–55% (w.b.), which decreased to 6%–8% (w.b.) as a result of the drying process. This study focuses on evaluating the individual and hybrid effects of infrared drying (IRD) and hot‐air drying (HAD) techniques to enhance the quality of copra. Three drying methods were used: IRD, HAD, and infrared‐assisted hot‐air drying (IRAHAD). Coconut pieces were subjected to different drying temperatures (50, 60, and 70°C) with a constant air speed of 2 m/s. Optimal results were achieved by employing the IRAHAD method at 60°C, preserving a crucial fat content of 68.4% essential for increased extraction of oil from copra and comparatively high drying rates. In particular, the drying rates in IRAHAD were twice as high as those in IRD and HAD. At a drying temperature of 60°C, the logarithmic model and the diffusion approximation model were deemed the best fit for HAD and IRAHAD, respectively.Practical applicationsThis study demonstrates the efficacy of infrared‐assisted hot‐air drying (IRAHAD) at 60°C in preserving copra's crucial fat content of 68.4% for optimal oil extraction. By implementing IRAHAD, producers can efficiently dry coconut kernels while maintaining quality, enhancing extraction yields, and improving overall profitability in the coconut processing industry.

An overview of fatty acids-based nutritional quality indices of fish oils from Cameroon: Impact of fish pre-treatment and preservation methods

This research provides a comprehensive examination of fish oils obtained from different fish species in Cameroon. It meticulously evaluates their nutritional quality indices based on fatty acids profile and scrutinizes the impact of diverse pre-treatment procedures on these indices. The fatty acid profiles and nutritional quality indices of seventeen fish species were reviewed, with a focus on the impact of refrigeration, boiling, and drying. The use of both synthetic and natural antioxidants in preserving oil quality during drying was also examined. The oil from Fontitrygon margarita liver had the highest nutritional quality, followed by oils from the fillets of seven other species. However, oils from certain species were found to have poor nutritional quality due to an unacceptable polyunsaturated fatty acids/saturated fatty acids ratio, atherogenicity index hypocholesterolemic/hypercholesterolemic ratio, and other parameters. Interestingly, boiling was found to enhance the nutritional quality of fish oil, while refrigeration and drying appeared to degrade it. Natural antioxidants, especially aqueous spices extracts, proved to be as effective, if not better than synthetic ones in preserving oil quality. Overall, this research enhances our understanding of the health benefits of fish oils and offers valuable insights into optimal oil extraction and preservation practices.

Investigating the Impact of Hydrocarbon Solvent on In-Situ Asphaltene Precipitation in Solvent-Assisted Cyclic Steam Technique

Summary Heavy oil recovery techniques often confront a significant challenge in in-situ asphaltene precipitation. This procedure significantly affects the characteristics of reservoirs and impedes optimal oil extraction. The purpose of this research was to examine how hydrocarbon solvents affect asphaltene precipitation occurring naturally in the reservoir as well as the resulting asphaltene content in processed oil. This was conducted using a laboratory-level dynamic model and the solvent-assisted cyclic steam stimulation (CSS) method. Throughout this experiment, which comprised six cycles, the steam-solvent blend’s pressure was consistently maintained close to 680 psi and the temperature was maintained at 500°F at the injection point. The findings revealed crude oil cracking at this temperature and noticeable in-situ asphaltene precipitation during the solvent-assisted CSS process. Notably, asphaltenes demonstrated mobility within porous media, contributing to their production in subsequent CSS cycles. Compared to a steam-only CSS control experiment, a higher asphaltene content in the original oil was observed, indicating that thermodynamic changes during the experiments likely caused asphaltene cracking. To sum up, this research provides an understanding of the effects of heavy oil recovery methods that rely on solvents on the precipitation of in-situ asphaltene and the content of asphaltene in the refined oil.

Determination of Hopper Fullness of Smart Screw Press Using Machine Learning

Problem statement. This research addresses the challenge of accurately determining the fullness of the hopper within a screw press for optimal oil extraction efficiency and quality. Existing weight or volume-based measurement methods can often struggle with determining the feed hopper fullness due to variable oil weights during extraction stages, material heterogeneity, environmental influences and imprecise instrument calibration. Purpose. The study proposes a novel solution via the application of machine learning, specifically aiming to develop and validate a technique that uses acoustic signals to calculate screw press bowl load. Methodology. To implement this solution, the study uses quantitative research, data collection and data analysis, supervised learning. The method is based on the processing of audio data received from microphones located near the auger and the use of machine learning algorithms, such as sound classification. Model training process was facilitated by ML tool Arduino. Findings. The results of this study, facilitated by effective data analysis via ML tools, demonstrate that the evaluated filling level of the screw press hopper can effectively be determined by the sound signals produced and corresponding machine learning algorithms. Originality. The distinct advantage of this approach lies in its ability to automate the monitoring and operational control process of the oil press, thereby improving device efficiency and resource conservation. Practical value. The proposed approach allows to automate the process of determining the fullness of the bowl and monitor the condition of the auger by its sound characteristics. This solution can be utilized in the oil production industry to enhance the productivity of the screw presses. This research underscores the promise of machine learning applications and the potential for future research focusing on improving model adaptability and developing predictive maintenance systems. These future investigative scopes could essentially revolutionize monitoring and operational practices within the oil extraction industry.

An oligopoly model for analysing oil extraction in the presence of renewable substitutes

ABSTRACT Optimal oil extraction models have often focused on economic costs and benefits in oil production. Anthropogenic pressures in accelerating climate change have become increasingly important in energy policy analysis. Renewables have gained prominence in climate policy analysis and academic discourse, and to some extent with different governments. The two strands of literature, the economically optimal extraction and climate change induced renewable substitutions, have developed separately. A Cournot-Nash equilibrium model was formulated and applied to conduct simulation experiments over a longer time horizon of 150 years. The findings indicated that if there is no renewable substitution, global oil reserves will be fully extracted in less than eighty-seven years, with slight differences depending on variations on marginal cost of oil extraction. Further, reductions in unit cost of renewable production have a greater impact on oil extraction than the respective marginal cost of oil extraction. If the unit cost of renewables falls closer to the level of currently low marginal cost for oil producers, then renewable substitution for oil would accelerate – rendering oil extraction uneconomical long before known oil reserves would be exhausted.

Intelligent oil field technology maturity level assessment: using the technology readiness level criteria

PurposeThis study aims to focused on conducting a comprehensive assessment of the technology readiness level (TRL) of Iran’s oil field intelligence compared to other countries with similar oil reservoirs. The ultimate objective is to optimize oil extraction from this field by leveraging intelligent technology. Incorporating intelligent technology in oil fields can significantly simplify operations, especially in challenging-to-access areas and increase oil production, thereby generating higher income and profits for the field owner.Design/methodology/approachThis study evaluates the level of maturity of present oil field technologies from the perspective of an intelligent oil field by using criteria for measuring the readiness of technologies. A questionnaire was designed and distributed to 18 competent oil industry professionals. Using weighted criteria, a mean estimate of oil field technical maturity was derived from the responses of respondents. Researchers evaluated the level of technological readiness for Brunei, Kuwait and Saudi Arabia’s oil fields using scientific studies.FindingsNone of the respondents believe that the intelligent oil field in Iran is highly developed and has a TRL 9 readiness level. The bulk of experts believed that intelligent technologies in the Iran oil industry have only reached TRL 2 and 1, or are merely in the transfer phase of fundamental and applied research. Clearly, Brunei, Kuwait and Saudi Arabia have the most developed oil fields in the world. In Iran, academics and executive and contracting firms in the field of intelligent oil fields are working to intelligently develop young oil fields.Originality/valueThis study explores the level of maturity of intelligent technology in one of Iran’s oil fields. It compares it to the level of maturity of intelligent technology in several other intelligent oil fields throughout the globe. Increasing intelligent oil fields TRL enables better reservoir management and causes more profit and oil recovery.

Optimization of oil extraction from soybean by Response Surface Methodology utilizing d-Limonene as solvent

Commercial oil extraction from soybeans is commonly achieved using solvent extraction with n-Hexane. The desire for fewer harmful and less combustible solvents has fueled the search for suitable green solvents. In the current investigation, Response Surface Methodology (RSM) was used to optimize oil extraction from soybeans by d-Limonene as a solvent. Temperature was varied from 25 to 170 oC, solvent volume from 4 to 20 mL, contact time from 30 to 360 min, particle size from 0.25 to 0.50 mm, and agitation rate from 50 to 200 rpm to study their effects on the yield with the aid of a two-level, five-factor central composite design (CCD). The quality of extracted oil using d-Limonene was compared to that extracted with n-Hexane by Fourier transform infrared spectroscopy (FTIR). The second-order model developed accurately predicts the extracted oil yield. A 55 percent maximum oil yield was achieved at 170 °C, 20 mL solvent volume, 360 minutes, 0.5 mm particle size, and 200 rpm. Temperature, solvent volume, contact time, and particle size substantially influence the extracted oil yield. The rate of agitation has minimal effect on the oil yield. The oil extracted at the process condition by d-Limonene or n-Hexane has the same quality.

Utilization of Supercritical Carbon Dioxide and Co-solvent n-hexane to Optimize Oil Extraction from Gliricidia sepium Seeds for Biodiesel Production

This study was conducted to optimize the supercritical carbon dioxide (scCO2) extraction of oil from Gliricidia sepium seeds using response surface methodology. Initial experiments were carried out using scCO2 and scCO2 with co-solvent n-hexane to determine the effect of co-solvent addition in oil yield. In order to obtain the maximum yield, experiments were conducted using Response Surface Methodology - Face Centered Central Composite Design (RSM – FCCD) under the following conditions: pressure of 20, 30, and 40 MPa, temperature of 50, 60, and 70°C, and CO2 flow rate of 2, 2.5, and 3 mL/min. A second-order polynomial with extended cubic interaction model was significantly fitted (p < 0.05), and a high coefficient determination value (R2 = 0.98) was recorded. At a constant extraction time of 60 minutes, the best extraction yield (12.12%) was obtained at 60°C, 40 MPa, and 2.5 mL/min. The pressure, temperature, and CO2 flow rate were all found to have a significant effect on the oil yield. The oil was used in biodiesel production and its methyl ester composition was analyzed using Gas Chromatography-Flame Ionization Detector (GC-FID).

Optimization Methods for the Extraction of Vegetable Oils: A Review

Most seed oils are edible while some are used generally as raw material for soap production, chocolate, margarine, and recently in biodiesel formulations as potential candidates capable of replacing fossil fuels which are costly and destructive to the environment. Oilseeds are a green and major reservoir which when properly exploited can be used sustainably for the production of chemicals at both the laboratory and industrial scales. Oil extraction is one of the most critical steps in seed oil processing because it determines the quality and quantity of oil extracted. Optimization of the extraction conditions for each extraction method enhances yield and quality meanwhile a carefully chosen optimization process equally has the potential of saving time and heat requirements with an associated consequence on cost reduction of the entire process. In this review, the techniques used to optimize oil extraction from plant materials which can be consulted by stakeholders in the field are brought to focus and the merits and demerits of these methods highlighted. Additionally, different types of optimization techniques used for various processes including modeling and the software employed in the optimization processes are discussed. Finally, the quality of the oil as affected by the methods of extraction and the optimization process used are also presented.

Innovative and flexible single screw press for the oil extraction of Calophyllum seeds

The oil extraction of Calophyllum seeds using a conventional single screw press leads to an inferior yield and is perceived to be less efficient as well as difficult to operate. An innovative and flexible single screw press was, therefore, designed and investigated in this study to solve these problems. Moreover, the effects of the seeds’ moisture content, pressing temperature and seeds’ feed rate on the oil yield and quality were identified to determine the optimal oil extraction performance from the Calophyllum seeds. The study found that the seeds’ moisture content, pressing temperature and seeds’ feed rate generally affected the oil yield. The yield indeed improved as the pressing temperature and the seeds’ feed rate increased respectively from 45 to 75°C and 1.5 to 5 kg·h<sup>–1</sup>. The oil yield also ameliorated as the seeds’ moisture content rose from 1.7 to 12.8%, but it was optimal when the seeds’ moisture content was 5.5%. The best oil yield of 80.6% was, thus, obtained with the seeds’ moisture content of 5.5%, a pressing temperature of 75°C and the seeds’ feed rate of 5 kg per h. Although the quality of the crude oil was poor with a high viscosity (³ 94 mm<sup>2</sup>·s<sup>–1</sup>) and high acid value (³ 48 mg KOH/g), its density, saponification and iodine values were acceptable. After the oil refining process by degumming and neutralisation, its quality improved and met the Indonesian Biofuel Standards, except for its viscosity.

Enzyme-Assisted Aqueous Oil Extraction from High Oleic Sunflower Seeds in a Scalable Prototype Reactor

Enzyme assisted aqueous extraction processing (EAEP) facilitates the production of high quality oils without the need for chemical refining. However, up to date, oil recovery remains remarkably below that found in mechanical and solvent extraction. In this study, response surface methodology (RSM) was applied, to optimize oil extraction from high oleic sunflower seeds via EAEP in a prototype automatic continuous stirred-tank extractor. Temperature, enzyme mass, water mass and proton concentration were varied for the exploration of optimum process conditions. The fit of a full second-order model was significant (p = 0.003), while the lack of fit was non-significant (p = 0.111). A local maximum was found at an extraction efficiency of 82.18%. A subsequent mass balance succeeded in reproducing the results from the RSM optimization. 93.03 ± 2.80% of the initial total mass was recovered, of which 90.90 ± 4.3% could be related to the components of the fractions.

Walnut and almond oil screw-press extraction at industrial scale: Effects of process parameters on oil yield and quality

Walnut and almond kernels are highly nutritious mainly due to their high oil contents. In this study, 32 factorial experimental designs were used to optimize processes for oil extraction by screw-pressing at industrial scale. Experimental designs included seed moisture content (SMC), and restriction die (RD) as the main processing parameters. Theoretical models were scanned against experimental data in order to optimize oil extraction conditions. The response variables analyzed were oil yield (OY), fine solid content (FC) in oil, and oil quality parameters. Fitted models for OY indicated maximum predicted values similar to the highest experimental values. Walnut oil extractions showed a maximum OY (84.5 ± 2.3 %) at 7.21% SMC, and 10 mm RD. For almond kernels, maximum OY (71.9 ± 3.5%) was obtained at 9.42% SMC, and 12 mm RD. Chemical quality parameters from both oils were in the ranges stated in Codex (FAO/WHO) standards for virgin (non-refined) oils.

Optimization of coffee oil extraction from spent coffee grounds using four solvents and prototype-scale extraction using circulation process

The optimization of two parameters—espresso coffee oil extraction time and the ratio of dried spent coffee grounds (DSCG)-to-solvent—were conducted on DSCG employing four solvents. Extracted yields were investigated using response surface methodology. The two independent variables—ratio of DSCG-to-solvent (5.1–24.9 g/g) and extraction time (0.2–39.8 min)—were optimized in the batch mode. The predicted model was verified using actual experiments. The experimental yields achieved were 14.7 percent by weight (wt%; using hexane), 13.1 wt% (using anhydrous ethanol), 11.8 wt% (using hydrous ethanol), and 7.5 wt% (using methanol). Prototype extraction was tested using a circulation process. Approximately 11.8 wt% oil yield of prototype extraction could be obtained from DSCG under the optimal conditions of 30.4 min extraction time and 22.5 g/g ratio of DSCG-to-hexane from the laboratory-scale results. In this study, the miscella (the solution of coffee oil dissolved in the solvent) from up to six successive extractions was investigated to determine the optimal oil extraction process. The repeated miscella from each successive extraction showed high efficiency and stability of coffee oil yield similar to that obtained using fresh hexane.

Optimisation of Omega 3 Rich Oil Extraction from Elateriospermum Tapos Seed by Microwave Assisted Aqueous Enzymatic Extraction

Microwave assisted aqueous enzymatic extraction (MAAEE) of Elateriospermum Tapos Seed (ETS) was performed in this study. This is a novel method which can reduce the extraction time and solvent consumption. The Elateriospermum Tapos oil (ETO) yield was optimised by using a central composite design (CCD) at condition parameters of microwave power (110 - 1,100 W), extraction time (30 - 120 s), enzyme cocktail concentration (1 - 5 %) and particle size (0.5 - 1.5 mm). The effect of each parameter was investigated by Response Surface Methodology (RSM). The optimal oil extraction yield was obtained at 110 W microwave power, 30 s extraction time, 1 % enzyme cocktail concentration and 0.5 mm particle size. Under these conditions, the maximum value obtained for the oil extraction yield was 46.12 ± 1.48 % recovery which was in good agreement with the predicted value (43.87 %). Thus, MAAEE could speed up extraction process as compared to Soxhlet which required 6 h extraction time to achieve similar amount of extraction yield.

ABOUT THE INFLUENCE OF GEOLOGICAL HETEROGENEITY OF MOUTH BAR ON THE HYDRODYNAMICS OF THE RESERVOIR ROCK OF RED FOREST FIELD (CHINA)

The article considers the geological structure of C 6 productive bed of Red forest oilfield (China). It is determined that reservoir rock belongs to mouth bar of delta front. The survey shows the laminated structure of the reservoir, consisting of several regressive sedimentation cyclical beds separated by impermeable clay layers. In the structure of the regression mouth bar are dedicated two subfacies: crest and slope. It is established that crest subfacie is characterized by high grain maturity and made more powerful and homogeneous sandy sediments with high permeability properties. Slope subfacie of mouth bar has a high stratification with frequent interlayering of discontinuous thin sand bodies composed of immature sediments with the deterioration of reservoir properties. The presence of macroheterogeneity in bar sediments determines the filtration reservoir structure and its dynamics that must be considered when selecting the system of the injection wells location, the design of horizontal wells and design of hydraulic fracturing. It is shown that the most significant effect on the fluid dynamics of the reservoir have a layered structure of the reservoir, the location of injection and production wells in relation to the bar body and, especially, differences in the azimuthal direction of seepage flow and the strike of mouth bar sand bodies. The simulation results showed that the reservoir with a large number of layers is watered with more effectively, and the amount of remaining oil in it more than in the reservoir with a small number of layers; quick the water-cut and the decline in oil production are established in models where the sand body strike coincides with the direction of fluid flow. Recommendations on the organization of the flooding system for optimal oil extraction of laminated heterogeneous bar reservoir.

Optimal oil production and the world supply of oil

We study the optimal oil extraction strategy and the value of an oil field using a multiple real option approach. The numerical method is flexible enough to solve a model with several state variables, to discuss the effect of risk aversion, and to take into account uncertainty in the size of reserves. Optimal extraction in the baseline model is found to be volatile. If the oil producer is risk averse, production is more stable, but spare capacity is much higher than what is typically observed. We show that decisions are very sensitive to expectations on the equilibrium oil price using a mean reverting model of the oil price where the equilibrium price is also a random variable. Oil production was cut during the 2008–2009 crisis, and we find that the cut in production was larger for OPEC members, for countries facing a lower discount rate, and for countries whose governments' finances are less dependent on oil revenues. However, the net present value of a country's oil reserves would be increased significantly (by 100%, in the most extreme case) if production was cut completely when prices fall below the country's threshold price. If several producers were to adopt such strategies, world oil prices would be higher but more stable.

Optimal Oil Production and the World Supply of Oil

We study the optimal oil extraction strategy and the value of an oil field using a multiple real option approach. The numerical method is flexible enough to solve a model with several state variables, to discuss the effect of risk aversion, and to take into account uncertainty in the size of reserves. Optimal extraction in the baseline model is found to be volatile. If the oil producer is risk averse, production is more stable, but spare capacity is much higher than what is typically observed. We show that decisions are very sensitive to expectations on the equilibrium oil price using a mean reverting model of the oil price where the equilibrium price is also a random variable. Oil production was cut during the 2008–2009 crisis, and we find that the cut in production was larger for OPEC, for countries facing a lower discount rate, as predicted by the model, and for countries whose governments’ finances are less dependent on oil revenues. However, the net present value of a country’s oil reserves would be increased significantly (by 100 percent, in the most extreme case) if production was cut completely when prices fall below the country's threshold price. If several producers were to adopt such strategies, world oil prices would be higher but more stable.

Tax policy can change the production path: A model of optimal oil extraction in Alaska

We model the economically optimal dynamic oil production decisions for seven production units (fields) on Alaska's North Slope. We use adjustment cost and discount rate to calibrate the model against historical production data, and use the calibrated model to simulate the impact of tax policy on production rate. We construct field-specific cost functions from average cost data and an estimated inverse production function, which incorporates engineering aspects of oil production into our economic modeling. Producers appear to have approximated dynamic optimality. Consistent with prior research, we find that changing the tax rate alone does not change the economically optimal oil production path, except for marginal fields that may cease production. Contrary to prior research, we find that the structure of tax policy can be designed to affect the economically optimal production path, but at a cost in net social benefit.

Optimization of roasting temperature and time during oil extraction from orange (Citrus sinensis) seeds: A response surface methodology approach

Nutritionally, oils obtained from oilseeds provide the calories, vitamins and essential fatty acids in the human diet in an easily digested form. The rate of vegetable oil consumption is increasing compared with animal fat due to its low sterol. In addition to being nutritious, edible vegetable oils also have industrial uses. Separation of oil from oil seeds is an important processing operation because it affects the quality and quantity of oil obtained from the oil seeds. Literature on oil extraction from some cultivars of citrus seeds showed good potential, therefore, focus on optimization of oil extraction could enhance economic status of the seed. In this study, response surface modeling approach was employed to optimize oil extraction from orange (Citrus sinensis) seed. Each sample was roasted for 10, 20, 30, 40 and 50 minutes at temperatures of 110, 120, 130, 150, and 170 oC. The parameters analysed included oil yield, free fatty acid, color, refractive index, specific gravity and pH. The treatments resulted in oil yield ranging from 32.0 ± 2.7 to 56.0 ± 6.5 %, free fatty acid (0.3 ± 0.0 to 3.01± 1.7%), colour (3.45 ± 1.9 to 20.5 ± 1.8 abs), refractive index (1.4 ± 0.1 to 1.46 ± 0.1), specific gravity (0.87 ± 0.1 to 0.94 ± 0.0) and pH (4.05 ± 1.0 to 5.66 ± 1.1). Maximum oil yield of 56.0 ± 6.5 % was obtained after roasting citrus seed at 170 oC for 30 min. Roasting temperature and duration showed significant (p < 0.05) effect on oil yield, free fatty acid, colour and specific gravity of the oil. However, nonsignificant (p > 0.05) effect was recorded on refractive index and pH of the extracted oil. The computer software package (Design-Expert) used for optimization gave four possible optimum conditions with desirability ranging from 0.50 to 0.68. The best desirability (0.68) was achieved at roasting temperature and duration of 150o C and 20 min., respectively. At these conditions oil yield was 52.6 ± 0.1%; free fatty acid, 1.4 ± 0.0%; colour, 4.7 ± 0.0 abs; specific gravity, 0.92 ± 0.0, and pH, 5.4 ± 0.1. The quantity, free fatty acid, colour and specific gravity of extracted oil from orange seed significantly depend on temperature at which the seed is roasted and duration of roasting.

Effects of solid pre-treatment towards optimizing supercritical methanol extraction and transesterification of Jatropha curcas L. seeds for the production of biodiesel

Experimental studies for in situ extraction and transesterification of oil seeds had been carried out recently for the process intensification of biodiesel production. As opposed to the conventional method, the solid oil seeds would be in direct contact with the transesterification reagent. Both the oil extraction and subsequent transesterification process to biodiesel will occur simultaneously. Consequently, solid pre-treatments would play a critical role to ensure that the oil seeds are in a state for optimal oil extraction. Apart from obtaining a higher yield, this could also ensure that the oil extraction phase would not bottleneck the entire in situ extraction and transesterification process. However, solid pre-treatments could be both cost and energy intensive and therefore should be carefully selected for optimum advantages. In this experimental work, ground Jatropha curcas L. seeds were subjected to pre-treatments processes including de-shelling, sieving, drying and heat treatment at five different temperatures (45–105 °C) and two different durations (12 and 24 h) before undergoing single-step supercritical methanol extraction and transesterification. Conventional two-step extraction and transesterification was also performed as comparison to the single-step process. The effects of each pre-treatment were analyzed and optimized towards two responses (extraction and FAME yield). The highest extraction and FAME yield for the two-step and single-step processes were 66.82% w/w, 114.87% w/w and 68.50% w/w, 128.78% w/w respectively. Single-step supercritical methanol extraction and transesterification was found to be able to provide a higher extraction and FAME yield for the production of biodiesel with less pre-treatment stages and intensity as compared to the conventional two-step process. Therefore, this is a highly promising approach to reduce the high biodiesel production cost which is currently impairing the industry.