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Title: A web-based decision support system for managing panicle caterpillars in sorghum

Author
item BACKOULOU, GEORGES - Oklahoma State University
item Elliott, Norman - Norm
item ROYER, THOMAS - Oklahoma State University
item MCCORNACK, BRIAN - Kansas State University
item GILES, KRISTOPHER - Oklahoma State University
item PENDLETON, BONNIE - West Texas A & M University
item BREWER, MICHAEL - Texas A&M University

Submitted to: Crop Management
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/4/2014
Publication Date: 12/1/2014
Citation: Backoulou, G.F., Elliott, N.C., Royer, T.A., McCornack, B.P., Giles, K.L., Pendleton, B.B., Brewer, M.J. 2014. A web-based decision support system for managing panicle caterpillars in sorghum. Crop Management. 13(1):6p. doi: 10.2134/CM-2014-0020-MG.

Interpretive Summary: Sorghum headworms are economically important insect pests of sorghum throughout the United States and are often ranked 1st or 2nd in importance among the myriad of insects that feed on sorghum, depending on the geographic location where the sorghum is grown. An improved, time and cost effective, sampling method was needed for sorghum producers, crop consultants, and extension professionals to aid in managing headworms in the most cost effective manner. Easy access to the sequential sampling method and to up-to-date information on sorghum headworm and insect pest management was also needed. We developed of a decision support system (DSS) based on a knowledge representation model that is easy to understand by users, with no specific training required. The DSS is an interactive instrument integrated in the internet. It is a simple web-based DSS, which is accessible through web browsers from computers with access to the world-wide-web. The DSS consists of series of HTML web pages with images and descriptions and images of sorghum headworms, and also management information that are organized into modules. The module on other sorghum pests contains images, descriptions, and management information on other insect pest species that infest sorghum. There is also a module that serves as a tutorial on how to conduct beat bucket sequential sampling for sorghum headworm. The DSS also contains and expert system for the purpose of supplying users with the information required for conducting sequential sampling for headworms. The DSS will help growers and other pest managers make optimal sorghum headworm pest management decisions.

Technical Abstract: Sorghum headworms are economically important insect pests of sorghum throughout the United States and are often ranked 1st or 2nd in importance among the myriad of insects that feed on sorghum, depending on the geographic location where the sorghum is grown. Sorghum producers, crop consultants, and extension professionals desire to manage headworms in a manner that minimizes economic losses. In order to manage headworms in this manner, sorghum fields must be sampled for headworms to facilitate optimal control decisions for the pest. This article reports on the development of a decision support system (DSS) based on a knowledge representation model that is easy to understand by users, with no specific training required. The DSS is an interactive instrument integrated in the internet. It is a simple web-based DSS, which is accessible through web browsers from computers with access to the world-wide-web. The DSS consists of series of HTML web pages with images and descriptions and images of sorghum headworms, and also management information that are organized into modules. The module on other sorghum pests contains images, descriptions, and management information on other insect pest species that infest sorghum. There is also a module that serves as a tutorial on how to conduct beat bucket sequential sampling for sorghum headworm. The DSS also contains an expert system for the purpose of supplying users with the information required for conducting sequential sampling for headworms. The expert system prompts the user for all the information required to calculate the economic threshold for any sorghum field. Once the economic threshold is determined the system directs the user to the appropriate sequential sampling data form to use in sampling the field.