Methyl Linoleate Synthesis From Cotton Seeds Oil : Optimization Study - Erin Ryantin Gunawan; Dedy Suhendra; Rohana Rohana; Desy Komalasari (Chemistry Education Program, the University of Mataram, 2020)
Methyl esters are derivatives of triglycerides (oils or fats) that can be produced through esterification and transesterification process. One example of the methyl esters are widely used as an industrial raw material is methyl linoleate. Methyl linoleate is a colorless liquid with molecular formula C19H34O2. Methyl linoleate is a fatty acid ester and has a lot of common use as biodiesel ingredient, textiles, in medical research, emulsifiers and lubricants. The raw materials commonly used for the synthesis of methyl esters are palm oil, coconut oil, soybean oil, and others. But these oils are edible oil materials, so that in this case the raw materials that will be used is the cotton seed that has not been exploited well. The optimization reaction of the methyl linoleate synthesis through enzymatic transesterification from cotton (Ceiba pentandra L.) seed oils and methanol by Response Surface Methodology (RSM) was carried out. Immobilized lipase (lipozymeTL IM) used as catalyst. This research aims to optimize the reaction by observing variety of conditions that are influenced by several variables, such asreaction time, molar ratio, the amount of enzyme and the reaction temperature. Design Expert v.7 software used to view the interaction between the variables via RSM. The mathematical equations and statistical methods showed that the optimum condition of the enzymatic transesterification was obtained at 0.15 gram of amount of the enzyme, the ratio of cotton seed oils: methanol of 1: 2.05 (g/g), a reaction time of 14 hours and a temperature of 49.95 oC with the predicted and actual percentages yield of 37.87 and 38.24%, respectively. The model recommended for obtaining optimum results is a quadratric model with a R-squared value of 0.6957. Keywords: Methyl linoleate, Cotton seed oils, Lipozyme, Optimization study, Design Expertv.7