Prediction of retention indices for identification of fatty acid methyl esters

Abstract

Quantitative structure–retention relationships have been developed to predict retention indices of fatty acid methyl esters on standard non-polar polydimethylsiloxane stationary phases. Branched, saturated and unsaturated compounds were included. All retention indices have been evaluated by statistical processing of experimentally measured and literature data in accordance with the concept of interlaboratory data randomization. Multiple linear regression (MLR) has been carried out to find relationships between selected properties and retention indices. Models have been built in two different ways (i) the same degrees of freedom for all models have been fixed and the variable selection ability has been compared; (ii) variable selection methods have been used in their best performance. The five selection methods were: pair-wise correlation, forward selection, partial least squares projection of latent structures, modified best subset selection and the Lasso method. The stability and the validity of models have been tested by internal and external validation. The error of predicted retention indices is close to the error of interlaboratory reproducibility of retention indices. The most relevant variables in description of retention indices were molecular mass, number of double bonds and number of rotatable bonds complemented with topological descriptors. Predictive models have been built for 130 fatty acid methyl esters for identification purposes. Moreover, prediction of unknown retention indices for 37 fatty acid methyl esters has also been carried out.