Optimization of Biodiesel and Glycerol Production From Mango Seed Oil Using Response Surface Methodology and Central Composite Design

Abstract

In the recent past, the world has experienced drastic climatic change mainly due to global warming as a result of environmental pollution. Biodiesel is biodegradable, renewable and environmental friendly fuel from non-edible vegetable oil. Response Surface Methodology (RSM) and Central Composite Design (CCD) is an important tool for modeling and analysis of statistical problems where the response of interest is influenced by several variables with an objective of optimizing the response. The main objective of this study is to optimize the biodiesel and glycerol production from mango seed oil using RSM and CCD. The study was guided by the following specific objectives: to optimize oil extraction from mango seed using RSM and Artificial Neural Networks (ANN), determine the effect of controlled variables on the yield of biodiesel and glycerol through trans-esterification process from mango seed oil using CCD, determine the appropriate mathematical model of second order polynomial that best fits the experimental data and determine the optimum conditions for biodiesel and glycerol production from mango seed oil using RSM. The experimental design for this study was a four factor five levels CCD. This research used mango seed oil because it is a non-edible oil and available. The study found that to obtain optimal oil yield of 9.05% from mango seeds, a temperature of 72.09 oC, time of 2.14 hours and a solute to solvent ratio of 1:7 are required at optimal levels using response surface methodology. Artificial Neural Networks (ANN) gave an oil yield of 9.7%, which was higher than the yield realized by RSM. In the presence of an interaction effect, the variables cannot be analyzed separately, therefore the application of statistical methods shows the interactions oil: methanol ratio and catalyst concentration as well as oil: methanol ratio and reaction temperature were significant on biodiesel production. The second order polynomial model gave adjusted R2 value of 0.964. This value indicated that 96.4% variation in biodiesel yield was accounted for by controlled variables in the model. Hence there was no proof that the fitted model fails to fit the data. This implies that the model is suitable to represent the relationship among the controlled variables. The study revealed that to obtain maximum (optimal) biodiesel yield of 86.7%, oil to methanol ratio of 1: 6.4, catalyst concentration of 8.2%, reaction temperature of 63.74oC and 82.9 minutes of reaction time are required. Also, to obtain minimum (Optimal) glycerol yield of 10.6%, 1: 6.95 oil to methanol ratio, 7.7% catalyst concentration, 65.99 oC of reaction temperature and 87.45 minutes of reaction time are required to produce glycerol from mango seeds oil. The study has established that the mango seed has a substantial amount of oil which can be extracted using the optimal conditions set on controlled variables. Value addition on mango seeds could guarantee improvement of economic status of farmers and the country. The study recommends that to achieve the United Nations (UN) sustainable development goal number seven, which advocates for clean energy, the government through the ministry of energy and petroleum should have concerted effort to promote production of biodiesel which is environmentally friendly. This could lead to reduction in environmental pollution and improvement of livelihoods of mango farmers.