Submitted to: Journal of Economic Entomology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: March 5, 2000
Publication Date: N/A
Interpretive Summary: Oats and other grains stored in the southeastern United States are at high risk of damage and contamination by insect pests. Protection of stored grain in this region is difficult, because the warm, humid climate permits insect activity throughout the year. The problem has been compounded by pest resistance to chemical insecticides and by loss, or threatened loss, of insecticide registrations for use on stored grain. New pest management methods with minimal reliance on chemicals are needed to solve the problem. Such methods will require better means of monitoring insect infestation and better understanding of the pests and the storage environment. ARS scientists at the Center for Medical, Agricultural and Veterinary Entomology in Gainesville, Florida, contributed to problem definition and solution by collecting data on seasonal variation and spatial distribution of temperature, moisture content, and insect pests in stored oats, and by evaluating a trap for monitoring insects electronically. This information will support new pest management methods that will help reduce pesticide risk by guiding the timing and targeting of control applications to eliminate the need for routine preventive treatment and to reduce the area treated with insecticides. It will also guide application of nonchemical methods. It will be useful to scientists, extension workers, farmers, grain elevator operators, pest control operators, and others.
Technical Abstract: Automated methods of monitoring stored grain for insect pests will contribute to early detection and aid in management of pest problems. An insect population infesting stored oats at a seed processing plant in north-central Florida was studied to test a device for counting insects electronically (Electronic Grain Probe Insect Counter, EGPIC), and to characterize the storage environment. The device counts insects as they fall through an infrared beam incorporated into a modified grain probe (pitfall) trap and transmits the counts to a computer for accumulation and storage. Eight traps were inserted into the surface of the grain bulk, and the insects trapped were identified and counted manually at weekly intervals. Grain temperature and moisture content were also recorded for each trap location. Manual and automatic counts were compared to estimate error in the EGPIC system. Both over- and undercounting occurred, and errors ranged from -79.4 to 82.4%. The mean absolute value of error was 31.7%. At least 31 species, or higher taxa, were detected, but the psocid Liposcelis entomophila (Enderlein) and the foreign grain beetle, Ahasverus advena(Waltl) accounted for 88% of the insect population. Species diversity, phenology and spatial distribution are presented, as well as temporal and spatial distribution of grain temperature and moisture content. The data sets generated will find application in population modeling and development of integrated pest management systems for stored grain.