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 modiÞed grain probe

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... ll) 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 identiÞed and counted manually at weekly intervals. Grain temperature and moisture content also were 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 Ϫ79.4 to 82.4%. The mean absolute value of error (ϮSE) was 31.7% (Ϯ4.3). 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 captured insects. 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 Þnd application in population modeling and development of integrated pest management systems for stored grain.