Inoculum Dose, Diversity, Dispersal, and Damage: Simulating Optimal Economic Control of Hop Powdery Mildew at the Landscape Level ¿

Authors: PEDRO, JOSHUA - City University Of New York; BHATTACHARYYA, SHARMODEEP - Oregon State University; CHATTERJEE, SHIRSHENDU - City University Of New York; MARSH, THOMAS - Washington State University; Hwang, Jae Young; Gent, David

Submitted to: Agricultural Systems
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/2/2026
Publication Date: 5/16/2026
Citation: Pedro, J.F., Bhattacharyya, S., Chatterjee, S., Marsh, T.L., Hwang, J., Gent, D.H. 2026. Inoculum Dose, Diversity, Dispersal, and Damage: Simulating Optimal Economic Control of Hop Powdery Mildew at the Landscape Level ¿. Agricultural Systems. https://doi.org/10.1016/j.agsy.2026.104792.
DOI: https://doi.org/10.1016/j.agsy.2026.104792

Interpretive Summary: Plant diseases that spread long distances by airborne dispersal may cause damage to nearby or distant fields. Controlling diseases that can spread potentially over long distances requires consideration of factors that influence how and when the disease spreads and other factors related to how growers may manage the disease. In this research, we developed a model that considers these factors and linked it to an economic model to understand how to minimize profit loss in complex scenarios when a plant disease may affect both yield and quality. We show that conditions in the early stages of disease outbreaks determine the optimal regional control strategy. We used the important disease hop powdery mildew as our motivating example, but the model and its findings are generalizable to other scenarios with related diseases.

Technical Abstract: CONTEXT: Plant pathogens that disperse by airborne propagules may cause damage that extends beyond the borders of individual fields. Developing sound management strategies, therefore, requires consideration of heterogeneity in pathogen transmission, the effectiveness of control measures, host susceptibility and pathogen virulence, and the resulting economic outcomes that scale up at the regional level with coordinated management. OBJECTIVE: We use hop powdery mildew as a motivating pathosystem to develop a coupled epidemiological-economic model to enable simulation of the impact of epidemic conditions and coordinated management interventions on profitability. This pathosystem is a well-suited case study because disease development may be limited by primary inoculum and fungicide applications, yet the pathogen can spread via long-distance dispersal between fields and rapidly damage both crop yield and quality. METHODS: We parameterized the model using data collected from a census sample of commercial hop yards in Oregon during 2014 to 2017, including the monthly incidence of plants with powdery mildew, fungicides applied by growers, and estimated revenue depending on how the incidence of diseased hop cones affects yield and the likelihood of crop devaluation. We show that conditions in the early stages of epidemics related to primary inoculum dose, pathogen diversity, and the intensity of management intervention interact and determine the optimal regional control strategy. RESULTS AND CONCLUSIONS: As the likelihood of primary infection increases, due to either the dose of primary inoculum or virulence of the pathogen population, mean profitability decreases. These effects are most pronounced when primary infection occurs in yards that are most central in the disease transmission network. The choice of how many fungicide applications to make in response to initial infection has little effect on profitability when the primary inoculum is relatively infrequent. However, as primary inoculum increases, targeted fungicide applications made in the early stages of epidemics are essential for maximizing profitability region-wide. These principles hold across a range of market demand scenarios that change crop quality standards, even though relative profit losses increase under low demand conditions. SIGNIFICANCE: Our analysis addresses a multifaceted challenge in agricultural disease management where epidemic control decisions must account for interactions between pathogen biology, management practices, market conditions, and regional-scale disease transmission. This research provides a framework for formally understanding factors that influence the cost of disease in complex agricultural systems where pathogens disperse across management units.