
Achillea clypeolata Sibth. & Sm. essential oil composition and QSRR model for predicting retention indices
Author(s) -
Milica Aćimović,
Lato Pezo,
Mirjana Cvetković,
Jovana Stanković,
Ivana Čabarkapa
Publication year - 2021
Publication title -
journal of the serbian chemical society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.227
H-Index - 45
eISSN - 1820-7421
pISSN - 0352-5139
DOI - 10.2298/jsc200524008a
Subject(s) - kovats retention index , artificial neural network , molecular descriptor , chemistry , retention time , chromatography , composition (language) , biological system , quantitative structure–activity relationship , mathematics , computer science , artificial intelligence , gas chromatography , stereochemistry , biology , linguistics , philosophy
The aim of this study was the prediction model of retention indices of compounds from the aboveground parts of Achillea clypeolata 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 A. clypeolata, essential oil compounds.