|Hagstrum, D. - ARS (RETIRED)|
|Reed, Carl - KANSAS STATE UNIVERSITY|
|Phillips, Thomas - OKLAHOMA STATE UNIVERSITY|
Submitted to: Journal of Stored Products Research
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: July 15, 2002
Publication Date: July 31, 2003
Citation: FLINN, P.W., HAGSTRUM, D.W., REED, C., PHILLIPS, T. SIMULATION MODEL OF RHYZOPERTHA DOMINICA POPULATION DYNAMICS IN CONCRETE GRAIN STORES. JOURNAL OF STORED PRODUCTS RESEARCH. 2003. v. 40. p. 39-45. Interpretive Summary: The primary goal of this research was to provide stored-grain managers with a more accurate method of predicting when the lesser grain borer will become a problem in wheat stored in concrete bins. To accomplish this goal, an insect population growth model was combined with a model that predicts seasonal changes in grain temperature for any location within a concrete bin. Output from the grain bin temperature and moisture model is used by the insect model to predict changes in insect numbers within the grain bin. We compared the model predictions to actual insect numbers collected from 13 grain silos located in Hutchinson Kansas. The model accurately predicted how the insect numbers increased over time. The model also accurately predicted the areas in the bin that would have the highest insect numbers. In December, the highest insect density was in the top center of the grain mass, and decreased steadily with increasing depth and towards the side of the bin wall. The lesser grain borer reaches this distribution because immigration is primarily through the top of the bin, and higher populations occur in the interior of the grain mass because of warmer temperatures there. From 20 September to 14 December, populations of the lesser grain borer increased from 0.1 to 3.5 insects per kg of wheat. This model will be used in a decision support system we are developing for elevators, as part of the area-wide integrated pest management (IPM) program for insect pests in stored wheat. Predictions of insect growth can reduce the cost of sampling by reducing its frequency. An additional advantage of the model is that it can predict the time required for insects to reach an economically damaging level. This allows fumigations to be targeted more precisely, and reduces the number of fumigations.
Technical Abstract: Rhyzopertha dominica is one of the most damaging insect pests in grain elevators and causes millions of dollars of stored grain losses annually in the USA. A simulation model was developed for predicting Rhyzopertha dominica population dynamics in concrete grain bins. The model used a two-dimensional representation of a cylindrical concrete bin (33 m tall by 6.4 m wide), and used hourly weather data to predict changes in grain temperature. Output from the grain bin temperature and moisture module was used by the insect module to predict changes in insect density in 32 different bin regions. When compared to validation data from 9 grain bins, the model accurately predicted insect vertical distribution and insect density. In December, the highest insect density was in the top center of the grain mass, and decreased steadily with increasing depth and towards the periphery of the grain mass. Rhyzopertha dominica attains this spatial distribution because immigration is primarily through the top of the bin, and higher populations occur in the interior of the grain mass because of warmer temperatures there. Initially, the model underestimated actual insect density in the grain bins. We increased the immigration rate by 50% and this resulted in a much better prediction of R. dominica density by the model. From 20 September to 14 December, populations of R. dominica increased from 0.1 to 3.5 insects per kg of wheat.