Structural Characterization of Volatile Components of Rosa Banksiae Ait for Estimation and Prediction of Their Linear Retention Indices and Retention Times

The molecular electronegativity-distance vector(MEDV)was used to describe the molecular structure of volatile components of Rosa banksiae Ait,and QSRR model was built up by use of multiple linear regression(MLR).Furthermore,in virtue of variable screening by the stepwise multiple regression technique,the QSRR models of 10 and 6 variables and linear retention index(LRI)10,7 and 6 varieables were built up by combinating MEDV with the Ultra2 column GC retention time(tR)of 53 volatile components of Rosa Banksiae Ait.The multiple correlation coefficients(R)of modeling calculation values of QSRR model were 0.906,0.906,0.949,0.943 and 0.949,respectively.The cross-verification multiple correlation coefficients(Rcv)were 0.903,0.904,0.867,0.90 1 and 0.904,respectively.The results show that the models constructed could provide estimation stability and favorable predictive ability.