Characterization of Septoria brown spot disease development and yield effects on soybean in Illinois

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Brown spot, caused by Septoria glycines Hemmi, is a highly prevalent foliar disease of soybean (Glycine max (L.) Merr.). Despite its wide distribution, the development of Septoria brown spot and its relationship with yield reduction remain poorly characterized. In this study, we conducted replicated multi-location inoculated field trials to characterize the disease development and evaluated the relationship between Septoria brown spot and soybean yield. Multiple components of disease and yield were rated weekly to characterize disease development. Fungicide treatments had a significant effect on ratings of vertical progress of the disease and chlorotic area at the end of the season. There were also significant differences between the fungicide treatments for the Area Under the Disease Progress Curve (AUDPC) of all the disease components, including necrotic area and defoliation rate. Soybean yield was negatively correlated with the vertical progress of the disease (r = −0.36). The vertical progress was the best linear predictor of yield with an R2 = 0.08 for the end of the season rating and an R2 = 0.2 for the AUDPC. A variance component analysis of the data showed that location was the most critical factor, illustrating the large effect of local environmental conditions on the disease. There was no statistically significant effect of the fungicide treatments on yield. Power analyses indicated that at least eight locations are needed to detect an effect of 269 kg ha−1. Our results provide useful information in the characterization of the disease development and for estimations of yield damage.

Original languageEnglish (US)
Pages (from-to)62-72
Number of pages11
JournalCanadian Journal of Plant Pathology
Issue number1
StatePublished - 2021


  • Septoria glycines
  • fungicides
  • late-season disease complex
  • linear regression model
  • power analysis
  • soybean

ASJC Scopus subject areas

  • Agronomy and Crop Science
  • Plant Science


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