No abstract

No abstract

The USDA Agricultural Research Service (ARS) funded a demonstration project (1998-2002) for areawide IPM for stored wheat in Kansas and Oklahoma. This project was a collaboration of researchers at the ARS Grain Marketing and Production Research Center in Manhattan, Kansas, Kansas State University, and Oklahoma State University. The project utilized two elevator networks, one in each state, for a total of 28 grain elevators. These elevators stored approximately 31 million bushels of wheat, which is approximately 1.2% of the annual national production. Stored wheat was followed as it moved from farm to the country elevator and finally to the terminal elevator. During this study, thousands of grain samples were taken in concrete elevator silos. Wheat stored at elevators was frequently infested by several insect species, which sometimes reached high numbers and damaged the grain. Fumigation using aluminum phosphide pellets was the main method for managing these insect pests in elevators in the USA. Fumigation decisions tended to be based on past experience with controlling stored-grain insects, or were calendar based. Integrated pest management (IPM) requires sampling and risk benefit analysis. We found that the best sampling method for estimating insect density, without turning the grain from one bin to another, was the vacuum probe sampler. Decision support software, Stored Grain Advisor Pro (SGA Pro) was developed that interprets insect sampling data, and provides grain managers with a risk analysis report detailing which bins are at low, moderate or high risk for insect-caused economic losses. Insect density was predicted up to three months in the future based on current insect density, grain temperature and moisture. Because sampling costs money, there is a trade-off between frequency of sampling and the cost of fumigation. The insect growth model in SGA Pro reduces the need to sample as often, thereby making the program more cost-effective. SGA Pro was validated during the final year of the areawide program. Based on data from 533 bins, SGA Pro accurately predicted which bins were at low, moderate or high risk. Only in two out of 533 bins did SGA Pro incorrectly predict bins as being low risk and, in both cases, insect density was only high (> two insects kg(-1)) at the surface, which suggested recent immigration. SGA Pro is superior to calendar-based management because it ensures that grain is only treated when insect densities exceed economic thresholds (two insects kg(-1)). This approach will reduce the frequency of fumigation while maintaining high grain quality. Minimizing the use of fumigant improves worker safety and reduces both control costs and harm to the environment.

No abstract

No abstract