In-silico prediction of gas chromatographic retention indices of some terpenols

Quantitative structure-retention relationships of the chromatographic retentions of phthalic acid ester contaminants in foods

The harmful health effects caused by phthalic acid esters have been supported from the increasing scientific evidence, developing the efficient methodologies to monitor the levels of phthalic acid esters in various foods become especially important from the aspects of human exposure assessment and their migration mechanistic understanding. In this study, quantitative structure-retention relationship studies on both the gas and liquid chromatographic retention times of 23 phthalic acid esters were performed by genetic function approximation, and the optimal quantitative structure-retention relationship models (r²  > 0.980, r² _CV  > 0.960, and r² _pred  > 0.865) passed the statistical tests of cross-validation, randomization, external prediction, Roy' r_m ² metrics, Golbraikh-Tropsha' criteria and applicability domain. The established predictive models elucidate the structural requirements for the retention of phthalic acid esters over different chromatographic columns, which were finally used to predict the retention times of 11 new phthalic acid esters. Hopefully, this work could provide useful guidelines for better understanding and accurate prediction of the retention behavior of undetermined phthalic acid esters when lacking standard samples or under poor experimental conditions, and make the simultaneous identification and quantification of numerous phthalic acid esters possible.