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

作者：Azar Parviz Aberomand; Nekoei Mehdi; Riahi Siavash^*; Ganjali Mohammad R; Zare Karim

来源：Journal of the Serbian Chemical Society, 2011, 76(6): 891-902.

DOI：10.2298/JSC100219076A

• chemometrics
• QSRR
• genetic algorithms
• multiple linear regression
• retention indices
• essential oils

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.

• 出版日期2011