ESA Annual Meetings Online Program

0578 Interactions between a nematode, fungus and aphid: implications for soybean management

Monday, November 14, 2011: 10:03 AM
Room A6, First Floor (Reno-Sparks Convention Center)
Michael T. McCarville , Entomology, Iowa State University, Ames, IA
Matthew E. O'Neal , Department of Entomology, Iowa State University, Ames, IA
Gregory L. Tylka , Plant Pathology and Microbiology, Iowa State University, Ames, IA
Gustavo C. MacIntosh , Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, IA
Soybean is an introduced crop to America, because of this it has benefited from a small number of pests threatening its production. Since its rapid expansion in production acres beginning in the 1930s, several pests have been introduced from the native range of soybean. Our knowledge of how these pests interact and the implications for management is limited. We examined how three common economic soybean pests, the soybean cyst nematode (SCN), the brown stem rot fungus (BSR) and the soybean aphid (SBA) interact on soybean. From 2008 to 2010 six soybean cultivars were exposed to four different pest treatments consisting of SCN, BSR and SBA in a micro-plot field experiment. Pest treatments were manipulated by using artificial infestations in a field virgin to soybean production. Plots were artificially infested with either a single pest or all three pests in combination. The performance of each pest was measured in a “single pest” treatment and compared to pest performance measured in the “multiple pest” treatment. This designed allowed us to measure the impact of the presence of two other soybean pests on the performance of each pest. Soil samples were taken prior to planting and after harvest to assess SCN performance during the season. Internal stem discoloration was used as a measure of BSR performance. Soybean aphid populations were monitored from initial infestation to leaf senescence to track performance. The presence of multiple pests significantly decreased SBA and BSR performance, but significantly increased SCN performance.

doi: 10.1603/ICE.2016.58874