Projects

Ongoing Research

Asymptomatic Spread of Huanglongbing (HLB) in Citrus Groves

This ongoing project investigates the hidden spread of Huanglongbing (HLB) during the asymptomatic phase, motivated by the work of Lee et al. (2014/2015). Unlike direct plant-to-plant transmission systems, HLB spreads indirectly through the movement of the Asian citrus psyllid, creating complex spatial dynamics before visible symptoms appear.

The goal of this project is to develop a spatial and network-based modeling framework that captures vector-mediated transmission, short latency periods, and grove geometry. The model incorporates weighted migration patterns, flush-level infectiousness, and intervention scenarios to understand how early management strategies may delay large-scale infection.

Key components:

Vector mediated transmission through psyllid migration
Spatially weighted network structure (within-row vs between-row movement)
Latent period dynamics and asymptomatic spread
Evaluation of early intervention strategies

Major Research Project

Network Based SEIRB Modeling of Frogeye Leaf Spot in Soybean

This project develops a spatially explicit stochastic SEIRB network model to study the spread and management of Frogeye Leaf Spot (FLS) in soybean fields. The framework integrates environmental reservoirs, plant-to-plant transmission, and realistic field geometry to evaluate disease control strategies.

Using Approximate Bayesian Computation Sequential Monte Carlo (ABC-SMC), the model is calibrated against observed epidemic data to explore parameter sensitivity, intervention timing, and roguing strategies.

Highlights:

Spatial plant network with environmental inoculum dynamics
Calibration using ABC-SMC inference
Analysis of targeted vs random intervention strategies
Simulation of realistic field scale epidemics

Page updated

Report abuse