Prediction of gas chromatography/electron capture detector retention times of chlorinated pesticides, herbicides, and organohalides by multivariate chemometrics methods

Abstract

A quantitative structure–retention relationship (QSRR) study, has been carried out on the gas chromatograph/electron capture detector (GC/ECD) system retention times ( t Rs) of 38 diverse chlorinated pesticides, herbicides, and organohalides by using molecular structural descriptors. Modeling of retention times of these compounds as a function of the theoretically derived descriptors was established by multiple linear regression (MLR) and partial least squares (PLS) regression. The stepwise regression using SPSS was used for the selection of the variables that resulted in the best-fitted models. Appropriate models with low standard errors and high correlation coefficients were obtained. Three types of molecular descriptors including electronic, steric and thermodynamic were used to develop a quantitative relationship between the retention times and structural properties. MLR and PLS analysis has been carried out to derive the best QSRR models. After variables selection, MLR and PLS methods used with leave-one-out cross validation for building the regression models. The predictive quality of the QSRR models were tested for an external prediction set of 12 compounds randomly chosen from 38 compounds. The PLS regression method was used to model the structure-retention relationships, more accurately. However, the results surprisingly showed more or less the same quality for MLR and PLS modeling according to squared regression coefficients R 2 which were 0.951 and 0.948 for MLR and PLS, respectively.