Foliar Uptake of Biocides: Statistical Assessment of Compartmental and Diffusion-Based Models

TL;DR

This paper systematically assesses and compares compartmental and diffusion-based models for pesticide foliar uptake, incorporating uncertainty analysis and data augmentation to improve experimental design and model reliability.

Contribution

It introduces a comprehensive methodology for modeling foliar pesticide uptake, emphasizing uncertainty quantification, parameter identifiability, and model-based experimental design.

Findings

Models differ in parameter identifiability and sensitivity.

Data augmentation enhances model robustness and experimental planning.

Model comparison guides better pesticide formulation strategies.

Abstract

The global population increase leads to a high food demand, and to reach this target products such as pesticides are needed to protect the crops. Research is focusing on the development of new products that can be less harmful to the environment, and mathematical models are tools that can help to understand the mechanism of uptake of pesticides and then guide in the product development phase. This paper applies a systematic methodology to model the foliar uptake of pesticides, to take into account the uncertainties in the experimental data and in the model structure. A comparison between different models is conducted, focusing on the identifiability of model parameters through dynamic sensitivity profiles and correlation analysis. Lastly, data augmentation studies are conducted to exploit the model for the design of experiments and to provide a practical support to future experimental campaigns, paving the way for further application of model-based design of experiments techniques in the context of foliar uptake.