Abstract:
Partition coefficients between plant cuticles and water (
Kcw) are important for investigating penetration and residual of pesticides in plant. Experimental determination of
Kcw values for diverse pesticides was unrealistic. Therefore, it is necessary to develop an effective model for the prediction of
Kcw values. In this work, 64 log
Kcw values for 23 pesticides from previous literatures were collected, and a linear solvation energy relationship (LSER) model for the prediction of log
Kcw was developed. This model exhibits good goodness-of-fit (
R2adj,tra = 0.79, RMSE
tra = 0.38), robustness (
Q2BOOT = 0.78) and external prediction performance (
Q2ext = 0.81). The developed model is appropriate for various pesticides with functional groups such as -X (Cl, F, I), >N-C(O)-NH
2, -OCH
2COOH, -NH-, -NH
2, >C=O, -O-C(O)-NH-, -CN, -S-, -S(O)(O)-. Mechanism analysis indicated that hydrophobic interactions (average relative contribution of 48%) and n/π-electron pairs interactions (average relative contribution of 9%) contributed to the increase of partition, while hydrogen bond accepting ability (average relative contribution of 26%) and polarizability (average relative contribution of 17%) had negative contribution to the partition of pesticides on plant cuticles. The pp-LFER model developed in this study can be used to predict log
Kcw values of new pesticides, and revealed the partition mechanisms of pesticides between plant cuticles and water.