scholarly journals Quantitative Structure-Retention Relationship Studies as an Analytical Tool in the Determination and Modeling of Pesticide Residues in Plant Organisms

2010 ◽  
Vol 93 (6) ◽  
pp. 1703-1714 ◽  
Author(s):  
Bogusaw Buszewski ◽  
Monika Michel

Abstract Crop models use mathematical equations to simulate the physical and chemical processes that generally control the uptake, translocation, and sorption of pesticides in all parts of plants. Our interest is focused on method optimization to determine the new compounds using stationary and mobile phases with different physicochemical properties. The work deals with five fungicides composed of nitrogen-containing heterocycles, 1,2,4-triazoles. The sample preparation liquid extraction and solid-phase-based methods are used to determine and model the pesticide residues in plants organisms. Analysis of these compounds is generally carried out by GC or HPLC coupled to different detectors, especially to mass spectrometers, in hyphenated techniques that have been extremely developed in recent years. The relationships between the chromatographic retention factor (k) and those physicochemical properties that are relevant in quantitative structure-retention relationship (QSRR) studies were investigated. The accuracy of the simple linear regressions between the chromatographic retention and the descriptors for all of the compounds was satisfactory (correlation coefficient 0.83 ≥ R2 ≥ 0.99). The QSRR models of these nitrogen-containing heterocyclic compounds could be predicted with a multiple linear regression equation having the statistical index R2 = 1.00. Evaluation of chromatographic properties of the new stationary phases and description of the molecular separation mechanism using the QSRR method, including molecular modeling, were performed. A universal model is presented that links the physicochemical parameters describing the fungicide compounds with the anatomical, physiological, and biochemical properties of the plant.


2008 ◽  
Vol 27 (8) ◽  
pp. 996-1005 ◽  
Author(s):  
Adrian Beteringhe ◽  
Ana C. Radutiu ◽  
Daniela C. Culita ◽  
Alice Mischie ◽  
Florica Spafiu


Author(s):  
Nabil Bouarra ◽  
Nawel Nadji ◽  
Loubna Nouri ◽  
Amel Boudjemaa ◽  
Khaldoun Bachari ◽  
...  

In this work, the liquid chromatography retention time in monomeric and polymeric stationary phases of PAHs was investigated. Quantitative structure retention relationship approach has been successfully performed. At first, 3224 molecular descriptors were calculated for the optimized PAHs structure using Dragon software. Afterwards, the modelled dataset was divided using the CADEX algorithm into two subsets for internal and external validation. The genetic algorithm-based on a multiple linear regression was used for feature selection of the most significant descriptors and the model development. The selected models included five descriptors: nCIR, GGI3, GGI4, JGT, and DP14 were used for the monomeric column and nR10, EEig01x, L1m, H5v, HATS6v were introduced for the polymeric column. Robustness and predictive performance of the suggested models were verified by both internal and external statistical validation. The good quality of the statistical parameters indicates the stability and predictive power of the suggested models. This study demonstrated that the suitability of the established models in the prediction of liquid chromatographic retention indices of PAHs.





2009 ◽  
Vol 63 (5) ◽  
Author(s):  
Nagy Moustafa

AbstractA new and simple quantitative structure-retention relationship (QSRR) was tested as a predictive model for adjusted retention times in complex petroleum condensate fractions. This relationship adopted the form of a non-linear collective retention-variables model. The adjusted retention times were correlated with the components molecular descriptors, e.g. total path counts and boiling temperatures, by multi-linear regression analysis. The obtained two QSRR models show an acceptable predictive accuracy with R 2 of 0.9949 and 0.9856, respectively. Stability and validity of the models were tested by comparing the calculated and the experimental retention indices.



2018 ◽  
Vol 5 (2) ◽  
pp. 77-89
Author(s):  
M. N. Moskovkina ◽  
I. P. Bangov

Abstract The Quantitative Structure Retention Relationship (QSRR) approach has been applied to model the gas chromatographic retention of 16 alkyloxazoles and 16 alkylthiazoles on three capillary columns with different polarities. The potential of the Charge-related Topological Index (CTI) developed by one of the authors (I.B.) was investigated as a descriptor in QSRR linear multivariate regressions. Calculated values of atomic charges and the indication of the presence of substitutions in different positions in the solute structures are used to generate regressions. Analysis of the equations derived proves their ability to describe and evaluate the participants in the chromatographic separation process. The present quantitative characterization of the chromatographic retention of alkylazoles shows the potentials of deriving QSRR models to exhibit the retention intermolecular interactions.



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