Journal ArticleDOI
QSRR Study on GC Retention Time of Aromatic Components in Red Raspberry Wine
Li Ping Cheng,Xu Li Zhang +1 more
TLDR
In this article, a quantitative structure-retention relationship (QSRR) study had been carried out for aromatic components in red raspberry wine based on various quantum-chemical and physicochemical descriptors.Abstract:
In the present study, quantitative structure-retention relationship (QSRR) study had been carried out for aromatic components in red raspberry wine based on various quantum-chemical and physicochemical descriptors. To build QSRR models, a multiple linear regression (MLR) stepwise method was used. The generated models have good predictive ability and are of high statistical significance with good correlation coefficients (R2 ≥ 0.854) and p values far less than 0.05. Preliminary results indicated that the application of the models, especially the prediction of GC retention time of aromatic components of red raspberry, will be helpful. The models contribute also to the identification of important quantum-chemical and physicochemical descriptors responsible for retention time. It was found that the shape attribute (ShpA) plays a vital role in determining component’s GC retention time. the importance of the melting point (MP) and the HOMO-LUMO energy gap (DE) of analytes is also embodied in models.read more
Citations
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Journal ArticleDOI
Molecular modeling and prediction accuracy in Quantitative Structure-Retention Relationship calculations for chromatography
TL;DR: It is found that the method of geometry optimization and descriptor selection is of less importance than the chromatographic similarity of compounds in the training sets used for model building in order to reduce the error of the model.
References
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Journal ArticleDOI
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