Graduate Research Assistant Montana State University Bozeman, Montana
The wheat stem sawfly (Cephus cinctus Norton) was first documented as a significant pest to the production of small grains within the Northern Great Plains (NGP) of North America around the beginning of the 20th century. It is estimated that the wheat stem sawfly (WSS) is responsible for up to $350 million annually in economic losses across the NGP. Management tactics include no-till, crop rotation, and choosing solid-stemmed cultivars. The success of these tactics is seldom documented and adoption is not widespread. The lack of uniform WSS management strategies may be partially explained by the difficulty in monitoring WSS infestation. Due to the cryptic nature of this stem boring insect, the only accurate method of estimating WSS infestation is dissecting large quantities of stems. This is a resource intensive practice that is mostly confined to the research domain. Remote sensing (RS) presents an opportunity to improve WSS infestation monitoring practices. RS is commonly referred to as the study of objects and surfaces through analysis of their spectral behavior. Building off the work of Nansen et al. (2009) we are conducting a multiscale study of the reflectance of wheat in the presence of WSS infestation to identify reflectance behavior consistent with WSS injury. To accomplish this, we grew wheat plants in a controlled environment and monitored their reflectance with a hyperspectral spectroradiometer (350-2500nm) at the leaf and plant level on weekly basis. This study presents novel proximal remote sensing methods for detection of WSS infestation in growing wheat plants.
