@article{Aćimović_Pezo_Cvetković_Stanković_Čabarkapa_2021, place={Belgrade, Serbia}, title={Achillea clypeolata Sibth. & Sm. essential oil composition and QSRR model for predicting retention indices: Scientific paper}, volume={86}, url={https://www.shd-pub.org.rs/index.php/JSCS/article/view/9536}, DOI={10.2298/JSC200524008A}, abstractNote={<p>The aim of this study was the prediction model of retention indices of compounds from the aboveground parts of <em>Achillea clypeolata </em>Sibth. & Sm. essential oil, obtained by hydrodistillation and analysed by GC–MS. The quan­titative structure–retention relationship analysis was applied in order to anti­ci­pate the retention time of the obtained compounds. The selection of the seven molecular descriptors was done by a genetic algorithm. The chosen des­criptors were uncorrelated and were used to construct an artificial neural network. A total of 40 experimentally obtained retention indices was used to build this pre­diction model. The coefficient of determination for the training, testing and val­id­ation cycles were: 0.950, 0.825 and 1.000, respectively, indi­ca­t­ing that this model could be used for prediction of retention indices for <em>A. clypeolata</em>, essential oil compounds.</p>}, number={4}, journal={Journal of the Serbian Chemical Society}, author={Aćimović, Milica and Pezo, Lato and Cvetković, Mirjana and Stanković, Jovana and Čabarkapa, Ivana}, year={2021}, month={Apr.}, pages={355–366} }