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United States Department of Agriculture

Agricultural Research Service


Location: Application Technology Research

2011 Annual Report

1a. Objectives (from AD-416)
Develop software that incorporates real-time microclimatic conditions and pest and disease prediction models for making pest management decisions that will be integrated into an intelligent sprayer system for ornamental nursery and greenhouse crops; test software under controlled and commercial nursery and greenhouse conditions.

1b. Approach (from AD-416)
The expert pest decision support system will be a computer program that will enable growers to link to local weather stations and use existing pest predictive models such as degree-days, leaf wetness, and historic pest pressure to help make treatment decisions. Based on these parameters, the expert system will make recommendations on the need to treat for a particular pest or disease. Temperature-based insect phenology models will be part of the decision support system to predict spray timing. In addition, information on chemicals and application rates for controlling the various pests will be available in the program. The functions of the expert system will be improved continuously as more scientific information is available for more pests. Initially, models for several key pests will be programmed into the system, then, after successful field-testing more pests will be added. This programming will be incorporated into the intelligent spray system's software.

3. Progress Report
A review of the expert systems in crop protection literature was conducted and based on this review a planning document was developed to profile future activities and to set objectives and deadlines for the development of a decision support system for the ornamental industry. The decision support system will be composed of three main modules: a pest/pathogen identification module, a database for the selection of pest control methods, and a module that uses/connects to nursery pest phenological models. The initial focus of the project has been on the development of a database to facilitate growers' selection of pest control methods (chemical and non-chemical) for both greenhouses and nurseries based on different criteria including: control efficacy, price, toxicity, phytotocixity and mode of action. Meetings with growers and extension agents in the North East Ohio area have been used to receive feedback on the objectives of the pest control selection database. A prototype for this database has been developed and includes tools for selection and rotation of pesticides, evaluation of pest control spectra, record keeping of pest control application events, and growers' ranking of pesticides. The prototype integrates the programs PHP, JavaScript and MS-SQL and will be hosted both online and as a standalone facility integrated to the intelligent sprayer being developed by the USDA-ARS Application Technology Research Unit. Data on pests, ornamental plants and pesticides have been entered in the pest control selection database. Posters describing the database have been presented at the Ohio Florist Association meeting and the Florida Entomological Society for academic and growers' feedback. A protocol for testing of the decision support system has been developed and the prototype testing is being coordinated with the Cincinnati Greenhouse Ornamental Growers Association. A journal article and a presentation are also in development and will be presented later this year at the Entomological Society of America and to a peer reviewed entomology journal. Similarly, planning for the development of a phenological model for continuous growing conditions to target pests at the appropriate windows of time (based on the date of initial pest discovery) are being conducted. This research addressed critical elements for the development of precision sprayer technology envisioned in ARS parent project Objective 1 “Develop precision sprayers that can continuously match canopy characteristics to deliver agrichemicals and bio-products accurately to nursery and fruit crops”. Monitoring of the progress of this project was done by e-mails and monthly group meetings.

4. Accomplishments

Last Modified: 06/22/2017
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