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United States Department of Agriculture

Agricultural Research Service

Research Project: Develop Software for Models Predicting Pest Activity for Intelligent Sprayer Development

Location: Application Technology Research Unit

2012 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:

The decision support system for the ornamental Industry is 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 database prototype has the following elements: selection and rotation of pesticides, evaluation of pest control spectra, record keeping of pest control application events, and growers' ranking of pesticides. These elements have not been implemented yet. The prototype integrated three types of computer server/languages: the programs hypertext preprocessor (PHP), JavaScript and the Microsoft server software (MS-SQL), and is hosted both online and as a standalone module 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. The database prototype, originally tested in one browser, has been improved and works on most browsers. Testing of the database was conducted in October 2011 with members of the Cincinnati Flower Growers association and the Cleveland Flower Grower Association testing both at the group and individual level. Growers perceived all the components of the database as useful including efficacy information. Testing at the individual level indicated the need to present information in different formats based on the size of greenhouse operations and confirmed the need to present information on efficacy based on growers, research and industry feedback. Suggestions from these meetings are being used to improve the database. During 2012, the database will be populated with information for various pests and testing by a selected group of users will continue. The record keeping function will be improved to match the requirements for the states of Ohio, Oregon and Tennessee. During 2012, other potential users will be contacted to increase the pool of voluntary evaluators of this tool. A framework for the development of pest population prediction models/simulations in controlled environments that account for different sources of variability, including pest population and plant host variability is being developed based on previous methodologies with the help of a Senior Statistician at Ohio Agricultural Research & Development Center (OARDC). Similarly, literature searches for insect development variability for three of the most important pests in greenhouses: sweet potato whiteflies, western flower thrips and spider mites, were conducted. A simulation tool is being produced in real time and is expected to be complemented with secondary information retrieved from the literature and primary information from life history studies being conducted at OARDC. The aim of this tool is to predict the windows of activity for these three pests based on the initial date of discovery. Since the host plant has an impact on the development of these pests, colonies of these pests are being developed on 15 different hosts. Initial tests have been conducted on whiteflies to estimate the amount of developmental time variability present in different hosts at different temperatures in greenhouses. The information will be used to estimate sample sizes needed to develop reliable models. This project addresses 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”.


Last Modified: 10/21/2014
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