Achillea clypeolata Sibth. & Sm. essential oil composition and QSRR model for predicting retention indices

Authors

  • Milica Aćimović Institute of Field and Vegetable Crops Novi Sad, Maksima Gorkog 30, 21000 Novi Sad, Serbia https://orcid.org/0000-0002-5346-1412
  • Lato Pezo University of Belgrade, Institute of General and Physical Chemistry, Studentski trg 10–12, 1000 Belgrade, Serbia https://orcid.org/0000-0002-0704-3084
  • Mirjana Cvetković University of Belgrade, Institute of Chemistry, Technology and Metallurgy, Njegoševa 12, 11000 Belgrade, Serbia
  • Jovana Stanković Institute of Chemistry, Technology and Metallurgy, University of Belgrade, Serbia
  • Ivana Čabarkapa University of Novi Sad, Institute of Food Technology, Bulevar cara Lazara 1, 21000 Novi Sad, Serbia https://orcid.org/0000-0003-2215-4281

DOI:

https://doi.org/10.2298/JSC200524008A

Keywords:

GC–MS, QSRR, artificial neural networks, essential oil, hydrodistillation

Abstract

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 un–correlated 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.

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Published

2021-02-12

How to Cite

[1]
M. Aćimović, L. Pezo, M. Cvetković, J. Stanković, and I. Čabarkapa, “Achillea clypeolata Sibth. & Sm. essential oil composition and QSRR model for predicting retention indices”, J. Serb. Chem. Soc., Feb. 2021.

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Section

Organic Chemistry

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