Submitted to: Computers and Electronics in Agriculture
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: March 18, 2009
Publication Date: June 1, 2009
Citation: McKinion, J.M., Jenkins, J.N., Willers, J.L., Zumanis, A. 2009. Spatially variable insecticide applications for early season control of cotton insect pests. Computers and Electronics in Agriculture. 67:71-79. Interpretive Summary: The use of multispectral imagery (pictures of farm fields in which red, blue, green, and infrared filters are used) is discussed for making early season insecticide applications so that only field areas are sprayed where pests are present. Several methodologies are needed to make this possible. One new methodology discussed is the use of an insect sampling technique which detects low level insect populations using maps from the imagery. An automation technique is discussed which tremendously reduces the time required to take a multispectral image and convert it to an application map which directs the farm machinery to spray only needed areas where pests are present. Global positioning sensors tell the equipment where it is in the field. To further reduce the time element (a maximum of 48 hours is allowed from the time the picture is taken to the time the field is sprayed), wireless local area network systems are discussed which allow large data files to be transmitted directly to the equipment in the field and recovery of as-applied data files from the equipment to the base station using high speed digital radios.
Technical Abstract: Our research has shown that cotton insect pests, specifically tarnished plant bugs, Lygus lineolaris (Palisot de Beauvois) (Heteroptera: Miridae), can be controlled early season in commercial cotton fields in Mississippi, USA, using spatially variable insecticide applications. Technology was developed for using GIS-based map scouting and a technique called the line-intercept method for obtaining low-level insect population counts in both rapidly growing areas of cotton and in poorer growing areas. Using these population characteristics in combination with heuristic knowledge of the cotton fields and with the GIS maps, a spatially sensitive map could then be developed which could drive a spatially variable insecticide application for control of the insect pest. We outline the steps needed to develop an automated technology for overcoming the time-sensitive events for early season control of cotton pests. This technology not only includes software systems for processing multi-spectral images to spatially variable insecticide application maps for spray controllers in the field but also high-speed wireless local area network (WLAN) technology for automated delivery of these controller application maps and for acquisition of as-applied and harvest maps from the field.