ECOLOGY, SAMPLING, AND MODELING OF INSECT PESTS OF STORED GRAIN, PROCESSING FACILITIES, AND WAREHOUSES
Location: Stored Product Insect Research Unit
Project Number: 5430-43000-031-00
Start Date: Feb 12, 2010
End Date: May 02, 2011
This project proposes to develop better tools to monitor insect populations; to improve IPM strategies for managing insects in stored grain, food processing facilities, and warehouses; to investigate the dispersal patterns that insects utilize to avoid treatments and to reinfest facilities; and to conduct investigations on emerging pests. The primary goal of the research is to reduce losses in quality to grain and grain products caused by insects. To achieve this goal, the following research objectives will be investigated: 1) improve methods for detecting insects in raw grain and other products by determining the critical factors that affect trap catch, and the relationship between trap catch and actual level of product infestation; 2) determine how the spatial distribution and population structure of stored-product insects inside and outside processing facilities before, during, and after control treatments affects re-infestation potential; 3) develop models that predict insect population growth in grain processing facilities and warehouses, and use the models to investigate optimal IPM strategies; and 4) determine the prevalence and pest potential of psocids and grain mites in stored grain, processing, and warehouse facilities, and conduct ecological studies on those emerging pests that prove to be economically important to implement monitoring and control strategies.
Laboratory and field experiments will be conducted to improve insect detection, sampling, and monitoring techniques in raw grain, grain processing facilities, and warehouses. We will improve interpretation of pheromone monitoring programs by determining the important factors that influence trap capture of walking beetles in grain processing facilities and warehouses, and optimize the accuracy of pheromone traps in locating red flour beetle infestation sources. We will characterize the factors responsible for pest resurgence after fumigation or other treatments; determine how spatial distributions of insect pests change before, during, and after control treatments; evaluate how long-term population dynamics of stored-product pests influences pest resurgence following treatment; and assess the potential for pests to survive in food residues and to avoid treated areas during or after control treatments. We will develop computer simulation models for insect pests of grain processing facilities and warehouses, and use these models to optimize monitoring and management strategies. Spatial simulation models will be developed for the red flour beetle, warehouse beetle, and Indianmeal moth. We will investigate the ecology and potential economic impact of emerging pest species, such as psocids and grain mites. Determine the prevalence of these pests in grain storages and mills and develop monitoring and control strategies for species that prove to be economically important.