POSTERS: Analytical and theoretical plant pathology
Growth stage vs. forecasting model based fungicide application to manage Phomopsis stem canker of sunflower (Helianthus annuus)
Febina Mathew - South Dakota State University. Tyler Patrick- University of Nebraska, Nathan Braun- South Dakota State University, Clay Carlson- University of Nebraska, Scott Isard- Penn State University, Jessica Halvorson- North Dakota State University, Roger Magarey- USDA APHIS PPQ CPHST, Samuel Mar
Phomopsis stem canker is a yield-limiting disease affecting sunflower (Helianthus annuus) in the United States. In 2018, a logistic regression based model was developed to predict Phomopsis stem canker. Upon validation using data sets not used for model development, the model predicted Phomopsis stem canker in 100% of the cases (sensitivity) and no disease in 92% of the cases (specificity). The model was converted to a risk map and hosted at iPIPE. To validate the risk map, field trials were set up at a total of five locations in Nebraska (1 field), North Dakota (2 fields) and South Dakota (2 fields). The study design was a randomized complete block on a susceptible hybrid with 10 treatments containing Headline and a non-treated check. Of the 10 treatments, seven included growth stage based applications [V8 (late vegetative), R1 (bud initiation), R5 (flowering), V8+R1, V8+R5, R1+R5, and V8+R1+R5] and three included forecasting model based applications. Disease severity was evaluated at growth stages between when flowering was complete (R6) through to physiological maturity (R9) stage using a 0-4 scale. While no disease was observed in North Dakota, disease was observed in Nebraska and South Dakota. Results from the Nebraska and South Dakota trials indicate that although significant differences in yield were not observed among treatments, greater yield was observed when the fungicide was sprayed at R1 or using the model compared to non-treated check.