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

Authors

Lourival Costa Paraíba

Published in

Environmental science and pollution research international. Sep 09, 2026. Epub Sep 09, 2026.

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 $_{}^{-1}$ ) and three frequencies (monthly, bimonthly, quarterly), for fruit harvested at 5-8 months, propagating uncertainty via Monte Carlo simulation ( $N=2000$ ) 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 $_{}^{-1}$ ; ANVISA 2023; Codex 2023). The 1.0 g dose meets the study's safety criterion at every frequency and fruit age ( $P(C_p>\text{MRL})\le 0.024$ ); 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.

PMID:
42714785
Bibliographic data and abstract were imported from PubMed on 10 Sep 2026.

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