Quantitative Structure–Property Relationship for the Retention Index of Volatile and Semi-Volatile Compounds of Coffee

Abstract

: This study describes the development of a quantitative structure–property relationship to predict the retention indices of volatile and semi-volatile compounds identified in Arabica coffee samples from different geographical origins. The analytical method utilized rapid headspace solid-phase microextraction (HSSPME)–gas chromatography–time-of-flight mass spectrometry (GC-TOFMS) data measured in divinylbenzene/carboxen/polydimethylsiloxane (DVB/CAR/PDMS) fiber. A total of 102 molecules were optimized with the PM6/ZDO level of theory in order to calculate several molecular descriptors. Ordinary least squares were coupled with genetic algorithm–supervised variable subset selection to find the best three descriptors. For model validation, the dataset was split into a training set (70%) and a test set (30%). The quality of the model was evaluated by means of the coefficient of determination and the root-mean-square error.