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United States Department of Agriculture

Agricultural Research Service

Research Project: ECOLOGY, SAMPLING, AND MODELING OF INSECT PESTS OF STORED GRAIN, PROCESSING FACILITIES, AND WAREHOUSES

Location: Stored Product Insect Research Unit

Title: Integrating the Stored Grain Advisor Pro Expert System with An Automated Electronic Grain Probe Trapping System

Authors
item Flinn, Paul
item Opit, George
item Throne, James

Submitted to: Meeting Abstract
Publication Type: Other
Publication Acceptance Date: June 6, 2006
Publication Date: October 15, 2006
Citation: Flinn, P.W., Opit, G.P., Throne, J.E. 2006. Integrating the stored grain advisor pro expert system with an automated electronic grain probe trapping system. Meeting Abstract. 9th International Working Conference on Stored Product Protection, Campinas, Sao Paulo, Brazil, October 15-18, 2006.

Technical Abstract: Automation of grain sampling should help to increase the adoption of stored-grain integrated pest management. A new commercial electronic grain probe trap (OPI Insector) has recently been marketed. To make accurate insect management decisions, managers need to know both the insect species and numbers found in their grain. Ideally, the electronic grain probe counts should be converted into insects per kg of grain. Insect species and grain temperature are two important factors that influence trap catch. Thus, the electronic trap needs to be able to estimate not only the number caught, but also the species and grain temperature. We field tested OPI Insector electronic grain probes in two bins, each containing 30 Tonne of wheat, for a 10-month period. We compared estimates of insect density (insects/kg wheat) to the Insector counts. The Insector was unable to distinguish between the species Rhyzopertha dominica and Tribolium castaneum because of their similar body sizes. Because of Cryptolestes ferrugineus’ smaller size, the system was able to distinguish C. ferrugineus from T. castaneum and R. dominica. Regression analysis was used to estimate insect density based on the grain temperature and insect species caught in the Insector. Correlation between insect density and trap catch was much higher for C. ferrugineus than for T. castaneum or R. dominica. Stored Grain Advisor Pro (SGA Pro) was modified to automatically read the Insector database, and used regression equations to transform insect counts into insect density. SGA Pro’s management recommendations were similar when using either the grain trier insect density estimates or OPI Insector estimates.

Last Modified: 7/28/2014
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