A quantitative structure–retention relationship for the prediction of retention indices of the essential oils of Ammoides atlantica

• Main Authors: PARVIZ ABEROMAND AZAR, MEHDI NEKOEI, SIAVASH RIAHI, MOHAMMAD R. GANJALI, KARIM ZARE
• Format: Article
• Language: English
• Published: Serbian Chemical Society 2011-06-01
• Series: Journal of the Serbian Chemical Society
• Subjects: chemometrics; QSRR; genetic algorithms; multiple linear regression; retention indices; essential oils
• Online Access: http://www.shd.org.rs/JSCS/Vol76/No6/09_4911_4169.pdf

A simple, descriptive and interpretable model, based on a quantitative structure–retention relationship (QSRR), was developed using the genetic algorithm-multiple linear regression (GA-MLR) approach for the prediction of the retention indices (RI) of essential oil components. By molecular modeling, three significant descriptors related to the RI values of the essential oils were identified. A data set was selected consisting of the retention indices for 32 essential oil molecules with a range of more than 931 compounds. Then, a suitable set of the molecular descriptors was calculated and the important descriptors were selected with the aid of the genetic algorithm and multiple regression method. A model with a low prediction error and a good correlation coefficient was obtained. This model was used for the prediction of the RI values of some essential oil components which were not used in the modeling procedure.