首页> 中文期刊> 《结构化学》 >Structural Characterization and Retention Time Prediction for Components of Essential Oil of Meconopsis Integrifolia Flowers

Structural Characterization and Retention Time Prediction for Components of Essential Oil of Meconopsis Integrifolia Flowers

         

摘要

A molecular structural characterization (MSC) method called reduced molecular electronegativity-distance vector (MEDVR) was used to describe the molecular structures of 55 components of meconopsis integrifolia flowers. By use of stepwise multiple regression (SMR) and partial least square (PLS) methods, a model with the correlation coefficient (R1) of 0.987 and the standard deviation (SD1) of 1.377 could be obtained. Then through multiple linear regression (MLR), another model with the correlation coefficient (R2) of 0.989 and standard deviation (SD2) of 1.395 could be constructed. Furthermore, in virtue of variable screening by the stepwise multiple regression technique (SMR), 8 vectors were selected to build up another model with its correlation coefficient (R3) and standard deviation (SD3) of 0.989 and 1.366, respectively. Then all the three models were evaluated by performing cross-validation with the leave-one-out (LOO) procedure, and the correlation coefficients (QCV) were 0.981, 0.976 and 0.979, respectively. The results show that the models constructed could provide estimation stability and favorable predictive ability.

著录项

  • 来源
    《结构化学》 |2010年第11期|1638-1645|共8页
  • 作者单位

    College of Resource and Environment Science, Neijiang Normal University, Sichuan 641112, China;

    College of Chemistry and Chemical Engineering, Chongqing University, Chongqing 400044, China;

    College of Resource and Environment Science, Neijiang Normal University, Sichuan 641112, China;

    College of Chemistry and Chemical Engineering, Chongqing University, Chongqing 400044, China;

    College of Resource and Environment Science, Neijiang Normal University, Sichuan 641112, China;

    College of Resource and Environment Science, Neijiang Normal University, Sichuan 641112, China;

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