QSRR Prediction of Gas Chromatography Retention Indices of Essential Oil Components

Simple item page
dc.contributor.authorMarrero-Ponce, Yovani
dc.contributor.authorBarigye, Stephen J.
dc.contributor.authorJorge-Rodrı´guez, Marı´a E.
dc.contributor.authorTran-Thi-Thu, Trang
dc.date.accessioned2023-02-09T20:32:36Z
dc.date.available2023-02-09T20:32:36Z
dc.date.issued2018
dc.description.abstractA comprehensive and largest (to the best of our knowledge) database of 791 essential oil components (EOCs) with corresponding gas chromatographic retention properties has been built. With this data set, Quantitative structure–retention relationship (QSRR) models for the prediction of the Kováts retention indices (RIs) on the non-polar DB-5 stationary phase have been built using the DRAGON molecular descriptors and the regression methods: multiple linear regression (MLR) and artificial neural networks (ANN). The obtained models demonstrate good performance, evidenced by the satisfactory statistical parameters for the best MLR (R 2 = 96.75% and Q2ext = 98.0%) and ANN (R 2 = 97.18% and Q2ext = 98.4%) models, respectively. In addition, the built models provide information on the factors that influence the retention of EOCs over the DB-5 stationary phase. Comparisons of the statistical parameters for the QSRR models in the present study with those reported in the literature demonstrate comparable to superior performance for the former. The obtained models constitute valuable tools for the prediction of RIs for new EOCs whose experimental data are undetermined.en_US
dc.identifier.citationMarrero-Ponce, Y., Barigye, S. J., Jorge-Rodríguez, M. E., & Tran-Thi-Thu, T. (2018). QSRR prediction of gas chromatography retention indices of essential oil components. Chemical Papers, 72, 57-69.https://doi.org/10.1007/s11696-017-0257-xen_US
dc.identifier.urihttps://nru.uncst.go.ug/handle/123456789/7727
dc.language.isoenen_US
dc.publisherChemical Papersen_US
dc.subjectGas chromatographyen_US
dc.subjectRetention indexen_US
dc.subjectQuantitative structure–retention relationshipsen_US
dc.subjectMultiple linear regressionen_US
dc.titleQSRR Prediction of Gas Chromatography Retention Indices of Essential Oil Componentsen_US
dc.typeArticleen_US
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
QSRR prediction of gas chromatography retention indices of essential oil components.pdf
Size:
2.15 MB
Format:
Adobe Portable Document Format
Description:
QSRR prediction of gas chromatography retention indices of essential oil components
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description:
Download
Collections
Engineering and Technology