Lipophilicity matters – A new look at experimental plant uptake data from literature

Abstract

Peer-reviewed Transpiration Stream Concentration Factor (TSCF) values were analysed to elucidate whether pH-induced changes in lipophilicity can explain some of the variability in reported TSCF and whether a potential relationship between lipophilicity and TSCF can be described by a simple mathematical model. The data set for this investigation combined TSCF values of 42 non-ionisable and ionisable compounds from hydroponic tests with intact plants and publicly available lipophilicity data for the tested compounds. The data set was not homogenous in terms of molecular weight of the tested compounds, plant species used for testing and experimental conditions, but a strong effect of one of these factors on variation in reported TSCF was not detected. Variation in TSCF was high for the same or similar predicted octanol/water partitioning coefficient (log P) but could be reduced by considering octanol/water distribution coefficients (log D) instead. The TSCF data set was split into a training and a test data set in order to identify and test a best-fit model describing the relationship between log D and TSCF. Comparing different types of models (linear, sigmoidal, Gaussian), the Gaussian model fitted to the training data set after removal of two outliers was identified as best-fit model based on visual assessment and fit statistics (RMSE = 0.20, NSE = 0.57, R = 0.75 (p < 0.001)). The 95% confidence interval around the best-fit model contained about 70% of data points in the training set and the test set, respectively. In conclusion, compound lipophilicity expressed as log D is a more appropriate descriptor of uptake by plant roots and subsequent translocation than log P when ionisable compounds are considered. Furthermore, findings in this study suggest that a relationship exists between log D and TSCF for uptake tests with intact plants which can be described by a simple bell-shaped Gaussian model.