A quantitative structure-retention relationship study for prediction of chromatographic relative retention time of chlorinated monoterpenes

A novel quantitative structure-retention relationship model has been developed for the gas chromatographic relative retention times (t (R)) of 67 polychlorinated monoterpene congeners in a non-polar column. Modeling of the relative retention time of these compounds as a function of the theoretically derived descriptors was established by principal component and partial least squares regressions. The choice of optimal training sets is efficiently performed by Kohonen self-organizing map. The genetic algorithm was used for the selection of the variables resulted in the best-fitted models. Appropriate models with low standard errors and high correlation coefficients were obtained. Wiener index, Balaban index, and ideal gas thermal capacity are examples of the descriptors affected by the retention times of polychlorinated monoterpenes.