电性距离矢量预测有机污染物的生物富集因子  

Estimation and Prediction of Bioconcentration Factors of Nonionic Organic Compounds in Fish by Electronegativity-Distance Vector

作　　者：李鸣建[1] 冯长君[1] 蔡可迎[1] 

机构地区：[1]徐州工程学院化学化工学院,江苏徐州221008

出　　处：《北京理工大学学报》2011年第12期1469-1473,1488,共6页Transactions of Beijing Institute of Technology

基　　金：国家自然科学基金资助项目(21075138);徐州市科技局基金资助项目(XZZD1104);贾汪科技局基金资助项目(XM10A05)

摘　　要：以电性距离矢量Mt表征165种非离子性有机物(NOC)的分子结构.利用多元回归方法建立了122种NOC的生物富集因子(lg BCF)与32个Mt的数学模型,其相关系数R为0.976.经逐步回归建立最佳四变量(M15,M17,M36,M91)模型,其R为0.960;并以Jackknife法检验,其LOO交互检验系数(q2)为0.915.这4个Mt参数揭示了影响NOC生物富集因子的主要因素,结果表明该模型具有良好的估算能力与鲁棒性.以111个NOC为训练集的生物富集模型作用于11个NOC的检验集,显示出良好的预测能力.Molecular electronegativity-distance vector （Mt） was used to describe the molecular structures of 165 nonionic organic compounds in this paper. A quantitative linear relationship between 32 Mt descriptors and bioconcentration factor （lg BCF） of 122 NOC was set up using the method of multiple linear regression （MLR）. The satisfactory model of 4 parameters （such as M15, M17, M36, M91） was built by stepwise multiple regression and the Jackknifed method （the leave-one-out, LOO）, of which the calibrated correlation coefficient （R） was 0.960 and the validated correlation coefficient （q2） was 0.915. The 4-variable model has shed light on some main structural factors influencing the BCF on NOC, which shows the good estimation ability and robustness. A prediction power for the external sample of 11 NOC was validated by the model built from the training set with 111 NOC.

关 键 词：非离子性有机物 电性距离矢量 生物富集因子 定量构效关系 

分 类 号：O641[理学—物理化学] X131.2[理学—化学]