Abstract
Pesticide application techniques are critical not only for integrated pest management (IPM) but also for food and environmental safety. Assessing pesticide application efficiency on plants can help optimize IPM and reduce pesticide environmental impacts. With hundreds of pesticides registered for use in agriculture, this study proposed a modeling approach based on plant uptake models for generalizing routes of plant chemical exposures that can correspond to different types of pesticide application methods and evaluating their respective efficiency on plants. Three representative pesticide application methods (i.e., drip irrigation, foliar spray, and broadcast application) were selected for modeling simulations. The simulation results for three representative pesticides (i.e., halofenozide, pymetrozine, and paraquat) revealed that the soil-based transpiration exposure route facilitated the bioaccumulation of moderately lipophilic compounds in leaves and fruits. While the plant surface-based exposure route (i.e., leaf cuticle penetration) made it easier for highly lipophilic compounds to enter plants, moderately lipophilic pesticides (i.e., log KOW ∼ 2) were more soluble in phloem sap, which enhanced their subsequent transport within plant tissues. In general, moderately lipophilic pesticides had the highest simulated residue concentrations in plant tissues for the three specific application methods, indicating they had the highest application efficiency due to their enhanced uptake routes (via transpiration and surface penetration) and increased solubility in xylem and phloem saps. Compared to foliar spray and broadcast application, drip irrigation produced higher residue concentrations for a wide variety of pesticides, exhibiting the highest application efficiency for many pesticides, especially for moderately lipophilic compounds. Future research should incorporate plant growth stages, crop safety, pesticide formulations, and multiple application events into the modeling approach for understanding pesticide application efficiency evaluation.
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