|Table of Contents|

Prediction of chromatographic retention index of volatilefragrance compound in fresh flower of lilium sppby artificial neural network(PDF)

《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

Issue:
2018年02期
Page:
249-
Research Field:
Publishing date:

Info

Title:
Prediction of chromatographic retention index of volatilefragrance compound in fresh flower of lilium sppby artificial neural network
Author(s):
Chen YanQu CuilingYan Yuanfang
School of Chemistry and Chemical Engineering,Xuzhou Institute of Technology,Xuzhou 221111,China
Keywords:
fresh flower of lilium spp volatile fragrance compounds chromatographic retention indices artificial neural network quantiative structure-retention relationships
PACS:
O657.63; Q949.718.23
DOI:
10.14177/j.cnki.32-1397n.2018.42.02.018
Abstract:
Based on the topological theory,the molecular connectivity index Xi,the electrotopological state indexes Ej and the molecular electro-negativity distance vector Mk of 35 volatile fragrance compounds in fresh flowers of lilium spp are calculated. Using the stepwise regression method,the optimal variable combination of X1,E9,M9 and M10 is selected. The artificial neural network model of the chromatographic retention index(RI)of the titled compunds is set up by taking the preselected four parameters as the input unit and the RI is predicted by this model. The result shows that,the predicted values of the RI are close to their experimental values,and the average relative error is 1.165%. This method can predict the gas chromatographic retention index of the compounds successfully,and it is helpful for selecting the experimental separation condition and exploring the mechanism of chromatographic retention.

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Last Update: 2018-04-30