Cost-optimal seeding strategy during a botanical pandemic in domesticated fields

Area of Science:

• Agricultural Science
• Epidemiology
• Mathematical Modeling

Background:

• Botanical pandemics result in substantial global economic losses and food insecurity.
• Effective management strategies are crucial for mitigating the impact of plant diseases on agriculture.
• Optimizing field management can enhance economic returns for farmers facing persistent pandemics.

Purpose of the Study:

• To develop a novel mathematical model integrating epidemiological and economic factors to maximize agricultural profit during botanical pandemics.
• To propose an optimal grid-formed seeding strategy to enhance economic returns for field owners.
• To analyze the economic influence of epidemiological parameters and farm size.

Main Methods:

• A spatiotemporal extended susceptible-infected-recovered (SIR) epidemiological model was employed to describe disease dynamics.
• A non-linear output economic model was integrated to quantify economic profit.
• An algorithm for an optimal grid-formed seeding strategy was developed and applied.

Main Results:

• The study revealed that recovery and basic infection rates exert similar economic influences.
• Contrary to intuition, larger farm sizes do not guarantee higher economic profits.
• The proposed seeding strategy demonstrated significant benefits in maximizing economic returns.

Conclusions:

• The developed epidemiological-economic model provides a framework for optimizing agricultural practices amidst botanical pandemics.
• Strategic seeding is essential for maximizing economic profit and ensuring food security.
• Understanding the interplay between disease dynamics and economic factors is key for sustainable agriculture.