Detecting sugarcane aphid (Melanaphis sacchari) infestation in grain sorghum (Sorghum bicolor) using leaf spectral response - Craigie, Grace (Kansas State University, 2022)
Sugarcane aphids (Melanaphis sacchari) are major agricultural pests to sorghum and infestation can cause up to 70% yield loss without timely insecticide applications. Populations can build exponentially on susceptible plants and require frequent field monitoring to determine when densities reach injurious levels. Current monitoring practices for sugarcane aphids (SCA) are time consuming and not practical for high acreage fields. Our overarching goal in Integrated Pest Management (IPM) is to develop more efficient monitoring techniques for SCA using remote sensing technologies, but this requires a better understanding of the interactions between aphids and leaf damage. Therefore, we studied the effect of SCA density on sorghum spectral responses near the feeding site and quantified potential systemic effects (i.e., plant-induced response) to see if the aphid feeding can be detected on leaves distal to the infestation. A leaf spectrometer, 400-1000 nm range, was used to measure reflectance changes in the range of 400-1000 nm by varying levels of SCA density on lower leaves and those distant to the caged infestation. Our results show that SCA infestation can be determined by changes in reflected light, especially between the green-red range (500-650 nm) and that sorghum plants respond systemically. This research is an important first step in developing more effective pest management strategies for SCA, as it shows that leaf reflection sensors can be used to identify aphid feeding regardless of where the infestation occurs on the plant. Future research should address whether such reflectance signatures can be observed autonomously using small unmanned aircraft systems or sUAS equipped with comparable sensor technologies. The goal is to improve sampling efficiency and overall decision making for this invasive species and reduce potential yield losses for growers through timely decisions.
Keywords: Sugarcane aphid; Sorghum; Remote sensing; Leaf spectrometer; Unmanned aircraft system; Leaf spectral response