|NANSEN, CHRISTIAN - Texas Agrilife Research|
Submitted to: Stewart Postharvest Review
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/30/2011
Publication Date: 12/1/2011
Citation: Nansen, C., Meikle, W.G. 2011. The economic injury level and the action threshold in stored-product systems. Stewart Postharvest Review. 3(7):2-8.
Interpretive Summary: Integrated Pest Management, or IPM, has been used often in field crops but it has not been used very often in managing pests in stored products. One reason may be because using pesticides based on a calendar is easy and cheap. Another reason may be because taking samples to check pest levels, which is an important part of IPM, is needed to see if pest levels are high enough to need treatment, but sampling can be difficult to do in large granaries or warehouses, and deciding what to do with the data is not always clear. Improved, faster methods for sampling are needed if farmers and grain store operators are going to adopt IPM, as well as clear decision rules to tell them what to do with sampling data.
Technical Abstract: Grain stores are ideal systems for forecasting and controlling growth in insect populations, yet they represent food a step closer to human consumption than field crops and therefore particular care should be taken with chemical control. Integrated pest management (IPM) is a highly-regarded approach to the control of insect pests in agriculture. Pest control, particularly chemical control, in IPM is based on insect densities as determined by sampling, combined with information on the economic injury levels (EIL) and action thresholds for the control method. While IPM has had success in field crops, it is comparatively seldom applied in stored product systems, partly due to the ease of calendar application, and partly due to labor involved in sampling. Also, there are difficulties in interpreting sampling or trap data, and to relating those data to grain value. A better understanding of insect pest ecology, combined with improved sampling methods and data interpretation tools, would increase the likelihood of IPM adoption in stored product systems.