Disentangling Pathogen Pressure, Disease Expression, and Yield Loss in Soybean Sudden Death Syndrome in Michigan
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A Simple Method for Isolation of Soybean Protoplasts and Application to Transient Gene Expression Analyses
Published on: January 25, 2018
Ryan Hamilton1, Adam Byrne2, Angela Tenney3
1Michigan State University, Plant, Soil and Microbial Sciences , 578 Wilson Rd, Room 104, East Lansing, East Lansing, Michigan, United States, 48824; hamil486@msu.edu.
Abstract:
Soybean sudden death syndrome (SDS), caused by Fusarium virguliforme, is a major constraint to soybean (Glycine max) production in North America, yet disease expression and yield loss remain highly variable across environments. From 2017 to 2024, field trials were conducted across 66 site-years in Michigan to evaluate the relative contributions of pathogen pressure, edaphic factors, and management inputs to SDS development and soybean yield. Fusarium virguliforme DNA abundance and soybean cyst nematode (SCN; Heterodera glycines) density were quantified, alongside soil properties, root disease index (RDX), foliar disease index (FDX), and yield, using linear mixed models and multivariate analyses. Across site-years, F. virguliforme DNA abundance and SCN density were consistent predictors of both FDX and yield, while soil pH was significantly associated with pathogen abundance, disease expression, and yield. However, FDX itself was not consistently aligned with yield loss, and substantial yield reductions were observed in the absence of visible foliar symptoms. Significant seed treatment effects were not detected across all site-years but were detected among site-years under high disease pressure, with yield and revenue benefits confined to site-years characterized by elevated pathogen pressure. Similarly, cultivar SDS tolerance reduced disease and protected yield under specific conditions but was not consistently effective across environments. These results demonstrate that SDS is best understood as a context-dependent disease complex structured by interacting soilborne pathogens and environmental gradients, with management inputs exerting secondary, conditional effects. Collectively, these findings support diagnostic-informed, risk-stratified strategies for integrated SDS management.

