ARS | Publication request: THE USE OF GPS, GIS, AND REMOTELY SENSED HYPERSPECTRAL IMAGERY TO DETECT PARAQUAT DRIFT INJURY ON CORN (ZEA MAYS) IN A FIELD SETTING

Submitted to: Agronomy Abstracts
Publication Type: Abstract Only
Publication Acceptance Date: January 1, 2003
Publication Date: January 1, 2003
Citation: Henry, W.B., Shaw, D.R., Easley, J.W., Williams, W.P. 2003. The use of gps, gis, and remotely sensed hyperspectral imagery to detect paraquat drift injury on corn (zea mays) in a field setting. Agronomy Abstracts. Presented at the National Weed Science Society of America 2003 Annual Meeting. Jacksonville, FL.

Technical Abstract: This research was the result of a burndown application of paraquat that drifted off-site onto an adjacent 8 ha field of corn. This research was conducted during the 2002 growing season at the North Farm at Mississippi State. Paraquat was applied at 0.3 kg cation/L at approximately 140 L/ha at 160 kPa. A wind blowing directly out of the East at 9-13 km/h carried a substantial amount of herbicide onto an adjacent USDA cornfield that was located directly to the West of the field to which the paraquat was applied. The corn in the adjacent field varied in height ranging from 1 to 2 meters, depending upon variety, planting date and irrigation status. Farmworks software and a Trimble GPS unit were used to create a GPS referenced map of the field. Within this map of the field a grid was generated on a 0.2 ha scale. The GPS unit was used to navigate to the centrally located points within each of the 40 grids. Visual injury data were then collected at each of the grid points. ArcView software was used to interpolate these injury data and create an injury gradient map. Visual injury estimates ranged from 90% on the edge of the cornfield directly adjacent to the burndown area, to less than 3% injury on the opposite side of the field. Remotely sensed hyperspectral data were gathered approximately one week following the drift event. Data analysis included correlation of NDVI to visual injury. This type of drift analysis could potentially be useful to producers for identifying herbicide drift injury within their fields and perhaps for quantifying the extent of this injury thereby enhancing a producer's ability to make informed management decisions.