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IEEE Computer Volume 16 Number 1 -- NEW APPLICATIONS & RECENT RESEARCH Disclosure Number: IPCOM000131585D
Original Publication Date: 1983-Jan-01
Included in the Prior Art Database: 2005-Nov-11
Document File: 4 page(s) / 21K

Publishing Venue

Software Patent Institute

Related People

Demetrios Michalopoulos: AUTHOR [+2]


NEW APPLICATIONS & RECENT RESEARCH * Agriculture gets help from technology as computers take to the fields. . ** In pest control ** In livestock maintenance ** In gardening

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New Applications Editor: Prof. Demetrios Michalopoulos

California State University, Fullerton

Agriculture gets help from technology as computers take to the fields. .

In pest control

Agricultural researchers at the University of California have installed a transactionoriented computer network as part of the Statewide Integrated Pest Management Program.

The project integrates pest control information generated at the university and through other research with the practical needs of growers and farm advisers. Through careful monitoring and computer-aided projections of the factors that affect an agricultural ecosystem, researchers hope to aid farmers in making more well-informed daily selections of pest control methods durmg growmg season.

The system uses a Prime 550 connected in a star configuration over 4800-baud phone lines to two Prime 250's. A third 250 stands next to the 550. Each 250 services four farm advisory offices in the UC cooperative extenslon system.

In this distributed-function network, users communicate directly via terminals with the 250. The 550 functions as a database machine and does heavy computational work while maintaining communications throughout the network. The system uses X.25 protocol techniques for communication between computers and runs menu-driven programs, most in Fortran 77 with some in Pascal. Researchers have been developing models of crop growth cycles, which are being compared with what takes place in the field. The use of models developed thus far is still in a research and validation stage, though some are nearing practical application.

Ultimately models will be developed that predict plant- pest interaction in a certain environment so that the best timing and type of treatment for crop-threatening pests can be evaluated both before and during the actual growing season.

Before planting, for example, farmers will have a large database comprising past weather, soil conditions, and pest activity to guide them in selecting a crop that is likely to do well on a certain parcel of land. They will also have a better idea of the costs for irrigation, plant nutrition, and pest treatments, which will aid in selecting a profit- making crop.

During the season, data will be collected, which the system will analyze and use to monitor the daily growth of the crop as well as variables affecting a harmful level of pest activity. Thus farmers will have a more precise picture of their current position and alternatives throughout the growing cycle.

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