In-silico prediction of dislodgeable foliar residues and regulatory implications for plant protection products.

ABSTRACT:

Background

When experimentally determined dislodgeable foliar residue (DFR) values are not available, regulatory agencies use conservative default DFR values as a first-tier approach to assess post-application dermal exposures to plant protection products (PPPs). These default values are based on a limited set of field studies, are very conservative, and potentially overestimate exposures from DFRs.

Objective

Use Random Forest to develop classification and regression-type ensemble models to predict DFR values after last application (DFR0) by considering experimentally-based variability due to differences in physical and chemical properties of PPPs, agronomic practices, crop type, and climatic conditions.

Methods

Random Forest algorithm was used to develop in-silico en

SUBMITTER: Shi Y 

PROVIDER: S-EPMC12401724 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature