Probabilistic pre-harvest intervals for cyproconazole in green coconut production in Brazil: a Level IV fugacity model with Monte Carlo analysis

Abstract The coconut palm ( Cocos nucifera L.) fruits continuously, and Brazilian growers apply the triazole fungicide cyproconazole via endotherapy without an established pre-harvest interval, creating a food-safety gap. We coupled a Level IV fugacity model with Gompertz growth functions for the water and pulp compartments to predict cyproconazole residues in green coconut at three doses (1.0, 1.5, 2.0 g palm $$^{-1}$$ - 1 ) and three frequencies (monthly, bimonthly, quarterly), for fruit harvested at 5–8 months, propagating uncertainty via Monte Carlo simulation ( $$N=2000$$ N = 2000 ) and Morris sensitivity screening. The plant-tissue degradation half-life (11.5 days nominal; Pesticide Properties Database) was found to be the dominant determinant of predicted residues relative to the maximum residue limit (0.1 mg kg $$^{-1}$$ - 1 ; ANVISA 2023; Codex 2023). The 1.0 g dose meets the study’s safety criterion at every frequency and fruit age ( $$P(C_p>\\textrm{MRL})\\le 0.024$$ P ( C p > MRL ) ≤ 0.024 ); risk for 1.5 and 2.0 g is age-dependent, with younger fruit carrying higher exceedance probabilities. A probabilistic harvest-safety matrix is provided as screening-level decision support pending field-residue validation.