Maximum residue limits (MRLs) for pesticides in export countries from Japan often become a trade barrier for Japanese tea. The purpose of this study is to develop a probabilistic risk estimation method for pesticide residues in green tea. First, we developed a model to estimate the pesticide residue level in green tea. Second, we introduced a regression model for pesticide half-lives on plants, one of the most critical parameters in the model. Finally, we estimated the time-course change of the distribution of the residue level by setting the probability distribution to the half-lives on tea leaves. Applying the model to three pesticides, acetamiprid, dinotefuran, and thiamethoxam, we suggested that the pre-harvest interval of thiamethoxam should be increased by three weeks for export to Taiwan. For EU nations, the MRL excess probabilities of acetamiprid and dinotefuran were measured as 99.6% and 99.5%, respectively, even 28 days after spraying.
Keywords: Japanese tea export; crop residue; dynamic plant uptake model; maximum residue limit; probabilistic risk estimation.