Vol. 2 (2026): Continuous Publication
Special Section: Mathematical and Computational Modelling of Agricultural and Natural Resource Systems

A Conservative Nonlocal Framework for Airborne Fungal Epidemics in Fruit Crops

Marlon M. López-Flores Laboratório de Inteligência Artificial, Robótica e Cibernética (LIARC), Instituto Militar de Engenharia (IME-RJ), Rio de Janeiro, Brazil
William Campillay-Llanos Núcleo de Investigación en Producción Alimentaria, Facultad de Recursos Naturales, Universidad Católica de Temuco, Temuco, Chile
Samuel Ortega-Farías Research and Extension Center for Irrigation and Agroclimatology and Research Program on Adaptation of Agriculture to Climate Change, Universidad de Talca, Talca, Chile
Gonzalo A. Díaz Laboratory of Fruit Pathology, Faculty of Agricultural Sciences, Universidad de Talca, Talca, Chile
https://doi.org/10.7770/jonraf-v2-art2908

Published 2026-09-22

Keywords

  • Fruit diseases,
  • Nonlocal dispersal,
  • Fungal epidemiology,
  • Spore dispersal kernel,
  • Spatial risk,
  • Botrytis cinerea
  • ...More
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Abstract

Purpose: Airborne fungal epidemics in fruit crops combine local infection processes with finite-distance inoculum movement; splash-dispersed diseases are considered only as candidate extensions. We developed a conservative nonlocal framework that distinguishes local infection intensity from spatial epidemic footprint and can accommodate polycyclic fruit–pathogen systems after pathogen-specific extension and calibration. Methods: Susceptible, latent, and sporulating host tissue were coupled to a nonlocal equation for free inoculum. We establish sufficient conditions for global well-posedness, positivity, and boundedness and derive a spatial next-generation threshold. A synthetic Botrytis cinerea case study used unclipped second-order strong stability-preserving Runge–Kutta [SSPRK(2,2)] simulations to compare local diffusion and nonlocal kernels with moment-matched controls, numerical refinement, periodic and absorbing boundaries, and targeted sensitivity analyses. Results: Numerical undershoots remained at roundoff scale. On the 200-m grid, the 5-m Gaussian increased infected-tissue-equivalent length from 30.74 to 33.70 m relative to local diffusion, whereas the original mixed kernel increased it to 88.63 m. With mean and variance matched, changing tail shape increased equivalent length to 39.16 m; an 8-m directional shift increased it to 61.56 m. On a 600-m absorbing domain, broad and directional kernels retained larger footprints than local baselines, although their ranking changed. Conclusions: Dispersal scale, tail shape, and directional displacement have distinct effects on epidemic footprint and influence spatial-extent metrics more strongly than peak local infection. The framework is a candidate structure for other fruit diseases, but each application requires pathogen-specific states, forcing, observation models, calibration, and validation.

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