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United States Department of Agriculture

Agricultural Research Service


Location: Application Technology Research

2013 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 decision support system for the ornamental industry was developed. The system 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 currently the elements of selection and rotation of pesticides, evaluation of pest control options, record keeping of pest control application events, and growers' ranking of pesticides. The prototype integrated the programs PHP, JavaScript and MS-SQL and is hosted both online and as a standalone module integrated to the intelligent sprayer being developed by the USDA ATRU division. During 2012 growers ranking of pesticides and forms that validated and edited pesticide/pest data were also implemented. Similarly, the database started to be populated with efficacy data from various sources (i.e. IR4 program public database). An additional tool implemented in 2012 is a graphical tool to forecast the mean development time of pest life stages by using the mean average temperature. Green house pest developmental time information from entomological journals is being used to for this application. The decision support system and database were both presented as an oral paper in Entomological Society of America national meeting in November 2012 for feedback from peer scientists. The feedback provided is being used to further improve the decision support system. Experiments to determine the developmental time of greenhouse pests on different host plants were conducted during 2013. For this purpose four greenhouse rooms were conditioned with drippers, artificial lighting and shade cloth and were kept at 4 different temperatures to measure the effect of temperature on developmental time. Each room was equipped with insect cages which housed host plants. A total of four replicates from 9 host species arranged in a randomized block design were tested to measure their effect on the developmental time of whiteflies. Whiteflies were followed individually to different leafs of the plants from egg to adults. Data entry and analysis are being conducted after which differences will be modeled and incorporated in an insect simulation tool which accounts for differences in the rate of variability. Similarly, samples from the plant tissues were taken at the end of the experiment and amino acid and mineral content analysis will be carried to determine the factors enhancing or inhibiting whitefly development. A second run to measure developmental time will be conducted in the fall of 2013. Similarly testing of the decision support system by greenhouse and nursery growers and entering pesticide information in the database will be done during this year. 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”.

4. Accomplishments

Last Modified: 05/29/2017
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