2008
DOI: 10.2116/analsci.24.139
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Retention Prediction Modeling of Ginsenosides on a Polyvinyl Alcohol-bonded Stationary Phase at Subambient Temperatures Using Multiple Linear Regression and Artificial Neural Network

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Cited by 16 publications
(4 citation statements)
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References 42 publications
(36 reference statements)
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“…The retention and separation mechanism of aromatic compounds including a variety of polycyclic aromatic hydrocarbons (PAHs) and pyrazines have been studied. [4][5][6][7][8][9][10][11][12][13][14][15][16][17] On the basis of actual retention measurements for pyrazines in several experimental conditions, a theoretical interpretation and the subsequent retention prediction were also studied in our previous work, 17 where the retention prediction models for pyrazine and alkylpyrazines were developed using multiple linear regression (MLR) and artificial neural networks (ANNs). During the study, the retention of these compounds was carefully determined in various conditions, including a variety of mobile phase conditions and column temperatures.…”
Section: Introductionmentioning
confidence: 99%
“…The retention and separation mechanism of aromatic compounds including a variety of polycyclic aromatic hydrocarbons (PAHs) and pyrazines have been studied. [4][5][6][7][8][9][10][11][12][13][14][15][16][17] On the basis of actual retention measurements for pyrazines in several experimental conditions, a theoretical interpretation and the subsequent retention prediction were also studied in our previous work, 17 where the retention prediction models for pyrazine and alkylpyrazines were developed using multiple linear regression (MLR) and artificial neural networks (ANNs). During the study, the retention of these compounds was carefully determined in various conditions, including a variety of mobile phase conditions and column temperatures.…”
Section: Introductionmentioning
confidence: 99%
“…Venusil HILIC, Unitary X Amide and Unitary Diol phases could provide stronger hydrogen bonding interactions [31]. For the separation of ginsenosides, hydrogen bonding is probably the predominant type of interaction [36,37]. As can be seen in Fig.…”
Section: Optimization Of the Sfc-ms Methodsmentioning
confidence: 91%
“…Development of novel fibrous extraction/separation media having different chemical structures and then different functionalities on the surface could be realized in the near future based on the concept of molecular shape recognition [3][4][5][6][7][8] and the systematic retention mechanism analysis with a help of various modern computational data calculations in LC [106][107][108][109][110][111][112][113][114][115][116][117][118]. Miniaturization of packed columns in GC [119][120][121][122][123] is also possible for high speed analysis with a unique selectivity but without a loss of sample loading capacity.…”
Section: Future Prospectivementioning
confidence: 99%