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ARS Home » Southeast Area » Fort Pierce, Florida » U.S. Horticultural Research Laboratory » Subtropical Plant Pathology Research » Research » Research Project #435810

Research Project: Development of Preseason Risk Prediction Models to Facilitate Areawide Pest Management of Whitefly-transmitted Viruses of Vegetables

Location: Subtropical Plant Pathology Research

Project Number: 6034-22000-045-017-A
Project Type: Cooperative Agreement

Start Date: Oct 1, 2018
End Date: Jul 31, 2024

Develop preseason risk-prediction models for whitefly-transmitted viruses, and deliver as a user-friendly tool as a smartphone app and with web-based access, that can be used as the basis for areawide pest management. 1) Cooperator will identify participating growers. 2) Cooperator will coordinate whitefly and virus sampling activities in commercial production fields.

Vegetable production in the southeastern states is regularly threatened by whiteflies (Bemisia tabaci) and whitefly-transmitted viruses. Epidemics of whitefly-transmitted viruses tend to be episodic, appearing sometimes for just a single field season, but often persisting over multiple seasons. Generally it is not clear what drives these episodes and it is difficult to predict which virus (or viruses) will be most prevalent and how severe it will be. But a recent and severe resurgence has been developing over the last two years that has growers on edge. The long-term goal of this project is to develop a disease and pest management strategy that utilizes a risk prediction model to provide a pre-planting (preseason) assessment of the risk of whitefly-transmitted viruses and to lay the foundation for an areawide pest management program for whitefly-transmitted viruses of vegetables. Cooperator will: 1) Identify participating growers. Obtain grower participation. Select appropriate crops and fields. 2) Coordinate sampling activities in commercial production fields. Georeference and map fields and areas surrounding fields. Assist with whitefly monitoring and virus data collection programs. Assist with testing and validation of risk prediction models.