Optimization Of Oil Production From Mango Seed Using Response Surface Methodology And Central Composite Design

Abstract

Response Surface Methodology (RSM) and Central Composite Design (CCD) is an important statistical tool for modeling and analysis of statistical problems where the response of interest is influenced by several variables with the objective of optimizing the response. The purpose of this study was to optimize oil extraction from mango seed using Response Surface Methodology. The experimental design for this study had three factors at five levels. Central Composite Design, is more useful methodology for modelling a second order model for a response variable in a full factorial design of experiments. This research optimized extraction of oil from mango seeds which are readily available and treated as a waste, and left to litter everywhere. n-hexane solvent and Soxhlex apparatus was used to extract oil from the powdered mango seeds. This may lead to reduced environmental pollution which has contributed immensely to climate change. The study sought to determine the effect of controlled variables (reaction Temperature, Solvent to Solute ratio and reaction Time) on the Yield of the Oil. The experimental data was analyzed using R-studio statistical software. The findings from the experimental data revealed that the optimum conditions for maximum oil yield (9.056%) obtained from Mango seed, are a temperature of 72.8 0C, seed powder to solvent ratio of 1:7 and a time of 138 minutes. The regression equation obtained for the model having a coefficient of correlation (R2), and adjusted coefficient of correlation (R2adj) are 0.9549 and 0.9143 respectively which shows the goodness of fit for the model. From the results optimization using CCD gave satisfactory results almost 82.33% of mango seed oil composition. A further research on determining edibility and quantitative composition of the mango seed oil are recommended.