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United States Department of Agriculture

Agricultural Research Service

Research Project: BIOLOGICALLY BASED CEREAL APHID MANAGMENT Title: Airborne remote sensing to detect greenbug stress to wheat

Authors
item Elliott, Norman
item Mirik, Mustafa - TEXAS A&M UNIVERSITY
item Yang, Zhiming - OKLAHOMA STATE UNIV
item Jones, Doug -
item Phoofolo, Mpho - OKLAHOMA STATE UNIV
item Catana, Vasile - OKLAHOMA STATE UNIV
item Giles, Kris - OKLAHOMA STATE UNIV
item Michels, Jerry - TEXAS A&M UNIVERSITY

Submitted to: Southwestern Entomologist
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: February 15, 2009
Publication Date: September 1, 2009
Citation: Elliott, N.C., Mirik, M., Yang, Z., Jones, D., Phoofolo, M., Catana, V., Giles, K., Michels, J. 2009. Airborne remote sensing to detect greenbug stress to wheat. Southwestern Entomologist. 34(3):205-211.

Interpretive Summary: Airborne remote sensing, which is based on measuring how objects on the earth's surface reflect sunlight back to sensors located in an airplane or some other airborne device, has been used to quantify levels of stress to plants in agricultural crops. Greenbugs cause stress to wheat plants and therefore remote sensing may be useful for detecting greenbug infested wheat fields. If greenbug infested fields can be detected by remote sensing prior to the plants becoming severely damaged then the field can be treated with insecticide to mitigate the problem. The objectives of this study were to assess whether variation in light reflectance of plants infested with varying densities of greenbugs could be detected using airborne multi-spectral imaging using a multi-spectral digital camera mounted in a fixed wing aircraft. We found that two winter wheat varieties infested by greenbugs exhibited somewhat different reflectance responses in airborne multi-spectral imagery. While, both varieties showed a reduction in the normalized differenced vegetation index (an index based on the amount of reflectance in the red and near-infrared parts of the light spectrum) with increasing greenbug density the rate at which the index declined differed among the two varieties. In a second study conducted in four productions winter wheat fields we found a significant reduction in two vegetation indexes with increasing greenbug density in three of the four fields. The results indicate that airborne multi-spectral imaging can be used to monitor winter wheat fields for greenbug infestation. However, more research is needed to determine whether the approach is practical.

Technical Abstract: Vegetation indices calculated from the quantity of reflected electromagnetic radiation have been used to quantify levels of stress to plants. Greenbugs cause stress to wheat plants and therefore multi-spectral remote sensing may be useful for detecting greenbug infested wheat fields. The objectives of this study were to assess whether variation in light reflectance of plants infested with varying densities of greenbugs could be detected using airborne multi-spectral imaging using a multi-spectral digital camera mounted in a fixed wing aircraft. We found that two winter wheat varieties ('Jagger' and 'OK 101') infested by greenbugs exhibited somewhat different reflectance responses in airborne multi-spectral imagery. While, both varieties showed a reduction in the normalized differenced vegetation index (NDVI) with increasing greenbug density, as indicated by a negative slope for the regression, the slope for Jagger was greater in magnitude (-0.0031) than the slope for OK 101 (-0.0011) indicating that NDVI decreased more rapidly as greenbug density increased for Jagger than for OK 101. A second vegetation index, Green NDVI, responded similarly to NDVI with increasing greenbug density. In a second study conducted in four productions winter wheat fields we found significant negative correlations between greenbug density and the two vegetation indexes for three of the four fields. The results indicate that airborne multi-spectral imaging can be used to monitor winter wheat fields for greenbug infestation. However, more research is needed to determine whether the approach is practical.

Last Modified: 12/21/2014
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