Li Z. Modeling pesticide residue uptake by leguminous plants: a geocarpic fruit model for peanuts.
PEST MANAGEMENT SCIENCE 2023;
79:152-162. [PMID:
36107631 DOI:
10.1002/ps.7184]
[Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Revised: 09/09/2022] [Accepted: 09/15/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND
Pesticide residues are frequently found in leguminous plants; however, no modeling approaches predict residue concentrations in edible legume seeds. In this study, a geocarpic fruit model, simplified for neutral organic compounds, was proposed for high-throughput simulations (over 700 pesticides) of the residue uptake by peanut plants, which characterized three scenarios, namely (i) pesticide foliar application during the pre-seed development stage, (ii) foliar application during the seed development stage, and (iii) soil contamination before plant germination.
RESULTS
In the foliar application scenario, in general, lipophilic pesticides have high simulated residue unit doses (RUDs, residue concentrations in plants per 1.0 kg ha-1 of pesticide application) in peanut leaves owing to intensified uptake via surface deposition, whereas hydrophilic pesticides have high simulated RUDs in peanuts because the uptake of residues via diffusion is enhanced. For the soil-contamination scenario, organic compounds with moderate lipophilicity have a high bioconcentration potential (i.e. the soil-plant system) in leaves and peanuts, due to large transpiration stream concentration factors (TSCFs) that boost the uptake via transpiration.
CONCLUSIONS
The simulation results have some degrees of agreement with field measurements, indicating that the proposed model can be used as a screening tool for dietary risk assessment of pesticides in peanuts. In future research, pH-dependent physicochemical properties (e.g. soil-water partition coefficient and TSCF) and degradation rate constants of chemicals need to be refined to improve the simulation analysis. © 2022 Society of Chemical Industry.
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