Linear modeling of the soil-water partition coefficient normalized to organic carbon content by reversed-phase thin-layer chromatography
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Andrić, Filip![](/themes/Mirageintam/images/orcid.png)
Segan, Sandra
Dramicanin, Aleksandra
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Majstorović, Helena
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Milojković-Opsenica, Dušanka
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Soil-water partition coefficient normalized to the organic carbon.content (K-OC) is one of the crucial properties influencing the fate of organic compounds in the environment. Chromatographic methods are well established alternative for direct sorption techniques used for K-OC determination. The present work proposes reversed-phase thin-layer chromatography (RP-TLC) as a simpler, yet equally accurate method as officially recommended HPLC technique. Several TLC systems were studied including octadecyl-(RP18) and cyano-(CN) modified silica layers in combination with methanol-water and acetonitrile-water mixtures as mobile phases. In total 50 compounds of different molecular shape, size, and various ability to establish specific interactions were selected (phenols, beznodiazepines, triazine herbicides, and polyaromatic hydrocarbons). Calibration set of 29 compounds with known logK(OC) values determined by sorption experiments was used to build simple univariate calibrations, Principal Com...ponent Regression (PCR) and Partial Least Squares (PLS) models between logK(OC) and TLC retention parameters. Models exhibit good statistical performance, indicating that CN-layers contribute better to logK(OC) modeling than RP18-silica. The most promising TLC methods, officially recommended HPLC method, and four in silico estimation approaches have been compared by non-parametric Sum of Ranking Differences approach (SRD). The best estimations of logK(OC) values were achieved by simple univariate calibration of TLC retention data involving CN-silica layers and moderate content of methanol (40-50% v/v). They were ranked far well compared to the officially recommended HPLC method which was ranked in the middle. The worst estimates have been obtained from in silico computations based on octanol-water partition coefficient. Linear Solvation Energy Relationship study revealed that increased polarity of CN-layers over RP18 in combination with methanol-water mixtures is the key to better modeling of logK(OC) through significant diminishing of dipolar and proton accepting influence of the mobile phase as well as enhancing molar refractivity in excess of the chromatographic systems.
Keywords:
Sum of Ranking Differences (SRD) / Soil-water partition coefficient / Reversed-phase thin-layer chromatography (RP-TLC) / Polycyclic aromatic hydrocarbons (PAHs) / Multivariate regression methods / BenzodiazepinesSource:
Journal of Chromatography A, 2016, 1458, 136-144Publisher:
- Elsevier, Amsterdam
Funding / projects:
- Structure-properties relationships of natural and synthetic molecules and their metal complexes (RS-MESTD-Basic Research (BR or ON)-172017)
DOI: 10.1016/j.chroma.2016.06.063
ISSN: 0021-9673
PubMed: 27378251
WoS: 000380972800016
Scopus: 2-s2.0-84993983941
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Istraživačko razvojni institut TAMIŠTY - JOUR AU - Andrić, Filip AU - Segan, Sandra AU - Dramicanin, Aleksandra AU - Majstorović, Helena AU - Milojković-Opsenica, Dušanka PY - 2016 UR - https://intam.institut-tamis.rs/handle/123456789/168 AB - Soil-water partition coefficient normalized to the organic carbon.content (K-OC) is one of the crucial properties influencing the fate of organic compounds in the environment. Chromatographic methods are well established alternative for direct sorption techniques used for K-OC determination. The present work proposes reversed-phase thin-layer chromatography (RP-TLC) as a simpler, yet equally accurate method as officially recommended HPLC technique. Several TLC systems were studied including octadecyl-(RP18) and cyano-(CN) modified silica layers in combination with methanol-water and acetonitrile-water mixtures as mobile phases. In total 50 compounds of different molecular shape, size, and various ability to establish specific interactions were selected (phenols, beznodiazepines, triazine herbicides, and polyaromatic hydrocarbons). Calibration set of 29 compounds with known logK(OC) values determined by sorption experiments was used to build simple univariate calibrations, Principal Component Regression (PCR) and Partial Least Squares (PLS) models between logK(OC) and TLC retention parameters. Models exhibit good statistical performance, indicating that CN-layers contribute better to logK(OC) modeling than RP18-silica. The most promising TLC methods, officially recommended HPLC method, and four in silico estimation approaches have been compared by non-parametric Sum of Ranking Differences approach (SRD). The best estimations of logK(OC) values were achieved by simple univariate calibration of TLC retention data involving CN-silica layers and moderate content of methanol (40-50% v/v). They were ranked far well compared to the officially recommended HPLC method which was ranked in the middle. The worst estimates have been obtained from in silico computations based on octanol-water partition coefficient. Linear Solvation Energy Relationship study revealed that increased polarity of CN-layers over RP18 in combination with methanol-water mixtures is the key to better modeling of logK(OC) through significant diminishing of dipolar and proton accepting influence of the mobile phase as well as enhancing molar refractivity in excess of the chromatographic systems. PB - Elsevier, Amsterdam T2 - Journal of Chromatography A T1 - Linear modeling of the soil-water partition coefficient normalized to organic carbon content by reversed-phase thin-layer chromatography EP - 144 SP - 136 VL - 1458 DO - 10.1016/j.chroma.2016.06.063 UR - conv_160 ER -
@article{ author = "Andrić, Filip and Segan, Sandra and Dramicanin, Aleksandra and Majstorović, Helena and Milojković-Opsenica, Dušanka", year = "2016", abstract = "Soil-water partition coefficient normalized to the organic carbon.content (K-OC) is one of the crucial properties influencing the fate of organic compounds in the environment. Chromatographic methods are well established alternative for direct sorption techniques used for K-OC determination. The present work proposes reversed-phase thin-layer chromatography (RP-TLC) as a simpler, yet equally accurate method as officially recommended HPLC technique. Several TLC systems were studied including octadecyl-(RP18) and cyano-(CN) modified silica layers in combination with methanol-water and acetonitrile-water mixtures as mobile phases. In total 50 compounds of different molecular shape, size, and various ability to establish specific interactions were selected (phenols, beznodiazepines, triazine herbicides, and polyaromatic hydrocarbons). Calibration set of 29 compounds with known logK(OC) values determined by sorption experiments was used to build simple univariate calibrations, Principal Component Regression (PCR) and Partial Least Squares (PLS) models between logK(OC) and TLC retention parameters. Models exhibit good statistical performance, indicating that CN-layers contribute better to logK(OC) modeling than RP18-silica. The most promising TLC methods, officially recommended HPLC method, and four in silico estimation approaches have been compared by non-parametric Sum of Ranking Differences approach (SRD). The best estimations of logK(OC) values were achieved by simple univariate calibration of TLC retention data involving CN-silica layers and moderate content of methanol (40-50% v/v). They were ranked far well compared to the officially recommended HPLC method which was ranked in the middle. The worst estimates have been obtained from in silico computations based on octanol-water partition coefficient. Linear Solvation Energy Relationship study revealed that increased polarity of CN-layers over RP18 in combination with methanol-water mixtures is the key to better modeling of logK(OC) through significant diminishing of dipolar and proton accepting influence of the mobile phase as well as enhancing molar refractivity in excess of the chromatographic systems.", publisher = "Elsevier, Amsterdam", journal = "Journal of Chromatography A", title = "Linear modeling of the soil-water partition coefficient normalized to organic carbon content by reversed-phase thin-layer chromatography", pages = "144-136", volume = "1458", doi = "10.1016/j.chroma.2016.06.063", url = "conv_160" }
Andrić, F., Segan, S., Dramicanin, A., Majstorović, H.,& Milojković-Opsenica, D.. (2016). Linear modeling of the soil-water partition coefficient normalized to organic carbon content by reversed-phase thin-layer chromatography. in Journal of Chromatography A Elsevier, Amsterdam., 1458, 136-144. https://doi.org/10.1016/j.chroma.2016.06.063 conv_160
Andrić F, Segan S, Dramicanin A, Majstorović H, Milojković-Opsenica D. Linear modeling of the soil-water partition coefficient normalized to organic carbon content by reversed-phase thin-layer chromatography. in Journal of Chromatography A. 2016;1458:136-144. doi:10.1016/j.chroma.2016.06.063 conv_160 .
Andrić, Filip, Segan, Sandra, Dramicanin, Aleksandra, Majstorović, Helena, Milojković-Opsenica, Dušanka, "Linear modeling of the soil-water partition coefficient normalized to organic carbon content by reversed-phase thin-layer chromatography" in Journal of Chromatography A, 1458 (2016):136-144, https://doi.org/10.1016/j.chroma.2016.06.063 ., conv_160 .