Achillea clypeolata Sibth. & Sm. essential oil composition and QSRR model for predicting retention indices
Hemijski sastav etarskog ulja Achillea clypeolata Sibth. & Sm. i QSRR model za predviđanje retencionog vremena
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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.
Cilj ove studije bio je izrada modela za predviđanja retencionog vremena hemijskih jedinjenja iz esencijalnog ulja nadzemnih delova biljke Achillea clypeolata Sibth. & Sm., dobijenog hidrodistilacijom i analiziranog GC–MS tehnikom. Kvantitativna analiza hemijske strukture i predviđanja retencionog vremena (quantitative structure – retention relationship – QSRR) je primenjena da bi se predvidelo vreme zadržavanja hemijskih jedinjenja dobijenih korišćenjem GC–MS analize. Izbor sedam molekulskih deskriptora izvršen je korišćenjem faktorske analize i genetskog algoritma. Primećeno je da izabrani deskriptori nisu bili u međusobnoj korelaciji, pa su korišćeni kao ulazni podaci pri izgradnji veštačke neuronske mreže. U izgradnji modela predviđanja retencionih vremena korišćeno je ukupno 40 eksperimentalno dobijenih retencionih vremena. Koeficijent determinacije tokom ciklusa pripreme, testiranja i validacije dostigao je vrednosti 0,950; 0,825 i 1,000, redom, što ukazuje na to da se ovaj model... može koristiti za predviđanje retencionih vremena hemijskih jedinjenja dobijenih iz esencijalnog ulja A. clypeolata.
Keywords:
hydrodistillation / GC–MS / artificial neural networks / Achillea clypeolata Sibth. & Sm. / Achillea clypeolata / essential oils / composition / retention / prediction models / retention indices / etarsko ulje / retenciono vreme / hidrodistilacija / vreme zadržavanja / veštačke neuronske mrežeSource:
Journal of the Serbian Chemical Society, 2021, 84, 4, 355-366Publisher:
- Belgrade : Serbian Chemical Society
DOI: 10.2298/JSC200524008A
ISSN: 1820-7421; 0352-5139
WoS: 000646020100002
Scopus: 2-s2.0-85107047766
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FiVeRTY - JOUR AU - Aćimović, Milica AU - Pezo, Lato AU - Cvetković, Mirjana AU - Stanković Jeremić, Jovana AU - Čabarkapa, Ivana PY - 2021 UR - http://fiver.ifvcns.rs/handle/123456789/2202 AB - 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. AB - Cilj ove studije bio je izrada modela za predviđanja retencionog vremena hemijskih jedinjenja iz esencijalnog ulja nadzemnih delova biljke Achillea clypeolata Sibth. & Sm., dobijenog hidrodistilacijom i analiziranog GC–MS tehnikom. Kvantitativna analiza hemijske strukture i predviđanja retencionog vremena (quantitative structure – retention relationship – QSRR) je primenjena da bi se predvidelo vreme zadržavanja hemijskih jedinjenja dobijenih korišćenjem GC–MS analize. Izbor sedam molekulskih deskriptora izvršen je korišćenjem faktorske analize i genetskog algoritma. Primećeno je da izabrani deskriptori nisu bili u međusobnoj korelaciji, pa su korišćeni kao ulazni podaci pri izgradnji veštačke neuronske mreže. U izgradnji modela predviđanja retencionih vremena korišćeno je ukupno 40 eksperimentalno dobijenih retencionih vremena. Koeficijent determinacije tokom ciklusa pripreme, testiranja i validacije dostigao je vrednosti 0,950; 0,825 i 1,000, redom, što ukazuje na to da se ovaj model može koristiti za predviđanje retencionih vremena hemijskih jedinjenja dobijenih iz esencijalnog ulja A. clypeolata. PB - Belgrade : Serbian Chemical Society T2 - Journal of the Serbian Chemical Society T1 - Achillea clypeolata Sibth. & Sm. essential oil composition and QSRR model for predicting retention indices T1 - Hemijski sastav etarskog ulja Achillea clypeolata Sibth. & Sm. i QSRR model za predviđanje retencionog vremena EP - 366 IS - 4 SP - 355 VL - 84 DO - 10.2298/JSC200524008A ER -
@article{ author = "Aćimović, Milica and Pezo, Lato and Cvetković, Mirjana and Stanković Jeremić, Jovana and Čabarkapa, Ivana", year = "2021", 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 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., Cilj ove studije bio je izrada modela za predviđanja retencionog vremena hemijskih jedinjenja iz esencijalnog ulja nadzemnih delova biljke Achillea clypeolata Sibth. & Sm., dobijenog hidrodistilacijom i analiziranog GC–MS tehnikom. Kvantitativna analiza hemijske strukture i predviđanja retencionog vremena (quantitative structure – retention relationship – QSRR) je primenjena da bi se predvidelo vreme zadržavanja hemijskih jedinjenja dobijenih korišćenjem GC–MS analize. Izbor sedam molekulskih deskriptora izvršen je korišćenjem faktorske analize i genetskog algoritma. Primećeno je da izabrani deskriptori nisu bili u međusobnoj korelaciji, pa su korišćeni kao ulazni podaci pri izgradnji veštačke neuronske mreže. U izgradnji modela predviđanja retencionih vremena korišćeno je ukupno 40 eksperimentalno dobijenih retencionih vremena. Koeficijent determinacije tokom ciklusa pripreme, testiranja i validacije dostigao je vrednosti 0,950; 0,825 i 1,000, redom, što ukazuje na to da se ovaj model može koristiti za predviđanje retencionih vremena hemijskih jedinjenja dobijenih iz esencijalnog ulja A. clypeolata.", publisher = "Belgrade : Serbian Chemical Society", journal = "Journal of the Serbian Chemical Society", title = "Achillea clypeolata Sibth. & Sm. essential oil composition and QSRR model for predicting retention indices, Hemijski sastav etarskog ulja Achillea clypeolata Sibth. & Sm. i QSRR model za predviđanje retencionog vremena", pages = "366-355", number = "4", volume = "84", doi = "10.2298/JSC200524008A" }
Aćimović, M., Pezo, L., Cvetković, M., Stanković Jeremić, J.,& Čabarkapa, I.. (2021). Achillea clypeolata Sibth. & Sm. essential oil composition and QSRR model for predicting retention indices. in Journal of the Serbian Chemical Society Belgrade : Serbian Chemical Society., 84(4), 355-366. https://doi.org/10.2298/JSC200524008A
Aćimović M, Pezo L, Cvetković M, Stanković Jeremić J, Čabarkapa I. Achillea clypeolata Sibth. & Sm. essential oil composition and QSRR model for predicting retention indices. in Journal of the Serbian Chemical Society. 2021;84(4):355-366. doi:10.2298/JSC200524008A .
Aćimović, Milica, Pezo, Lato, Cvetković, Mirjana, Stanković Jeremić, Jovana, Čabarkapa, Ivana, "Achillea clypeolata Sibth. & Sm. essential oil composition and QSRR model for predicting retention indices" in Journal of the Serbian Chemical Society, 84, no. 4 (2021):355-366, https://doi.org/10.2298/JSC200524008A . .