Assessment of Fuel Quality Parameters and Selection of Bacteria Using PROMETHEE-GAIA Algorithm

Recently, biodiesel is gaining significant importance due to eco-friendly nature and development of large-scale production methodologies. Biodiesel is a mixture of mono-alkyl esters of fatty acids (FA). During transesterification, the long-chain FAs are combined with methanol to produce fatty acid methyl ester (FAME), the principle component of biodiesel. The biodiesel fuel properties are determined by structural components of FAs such as chain length, degree of unsaturation, and branching of the carbon chain. The fuel quality of biodiesel are evaluated by assessing the properties such as cetane number (CN), iodine value (IV), cold filter plugging point (CFPP), higher heating value (HHV), cloud point (CP), pour point (PP) etc., of FAME. The amount of lipid or fat produced may vary from organism to organism. A particular species may have high biomass with low lipid content and vice versa. So the selection of suitable species/genus by decision analysis software is much needed. Besides various multi-criteria decision analyses, Preference Ranking Organization Method for Enrichment of Evaluation (PROMETHEE) and Graphical Analysis for Interactive Aid (GAIA) analysis is considered as the most promising tool in selecting the prominent biodiesel producing strain. Here we describe the method of evaluating the fuel quality parameters for the produced FAME and selecting the prominent strain through PROMETHEE-GAIA algorithm.