Project Details:

Title:
Developing an Integrated Management and Communication Plan for Soybean Sudden Death Syndrome

Parent Project: Developing an integrated management and communication plan for soybean SDS
Checkoff Organization:North Central Soybean Research Program
Categories:Soybean diseases, Research coordination, Communication
Organization Project Code:
Project Year:2021
Lead Principal Investigator:Daren Mueller (Iowa State University)
Co-Principal Investigators:
Keywords:

Contributing Organizations

Funding Institutions

Information and Results

Click a section heading to display its contents.

Project Summary

Sudden death syndrome (SDS) is an annual threat in most of the North Central region. Since 2014, this disease alone caused an estimated annual loss of nearly 40 million bushels in the U.S., valued at approximately $1.8 billion (Allen et al. 2017). The foundational management strategy for SDS (caused by Fusarium virguliforme) in soybean is using resistant cultivars. We have been evaluating industry standard susceptible and resistant cultivars in the North Central region for the last seven years, and resistant cultivars have shown less disease and more yield than the susceptible cultivars in most evaluations. However, in years when environmental conditions are favorable for disease development resistance alone does not provide adequate disease control or reduce farmer risk sufficiently. As the disease continues to spread into new areas, we have an opportunity for early education and improved awareness of the importance of using an integrated management program for SDS. Thus, the main goal of this project is to investigate management options that will help ensure resistant cultivars will be as effective as possible in years when SDS risk is high. Major achievements from the previous projects are listed below.

We determined that foliar symptoms and root rot both cause yield loss to SDS. Also, resistant varieties and effective seed treatments can reduce both SDS foliar symptoms and root rot. In 2018 and 2019, several hundred individual plants with different visual ratings of SDS were tagged in fields located in the Boone, Hamilton, Story, and Webster counties in Iowa. Disease was rated multiple times at weekly interval. Two hundred soybean plants with a range of SDS foliar symptoms were arbitrarily sampled (fifty plants from each field) at R6 growth stage for the Fv population density (in soybean root tissues and soil). At the end of the season, the remaining labeled plants were harvested individually and yield component data including a total number of pods per plant, the total number of seeds per plant, total seed weight per plant and 100-seed weight per plant were collected from individual plants to correlate yield with the SDS severity. Result showed that the disease onset time is highly correlated with the final disease severity and yield. Plots with earlier disease onset had greater disease severity at the end of the season and greater yield loss. We are expanding this project (Obj. 3c) to validate the relationship between the disease onset and final disease severity with multiple varieties.

We finished a study looking at the effect of soybean cyst nematode (Heterodera glycines; SCN) management on SDS severity. In summary, fall season SCN population density and SDS were positively correlated and SCN resistance played a critical role on SDS development. Cultivars with no resistance to SCN had the highest disease. Even though the PI 88788 type resistance did not keep nematode populations in check, any type of SCN resistance led to greater yields, lower SDS, and lower SCN reproduction than the cultivars with no resistance.

Meta-analysis has been recognized as a powerful method of combining results from several independent studies and is becoming more common in many disciplines nowadays. Recently, we completed a study and published a paper combining over 200 field trials studying the effect of ILEVO on disease and yield response. We used SDS, and yield data from field trials established for objective 1a. In addition, we collected field data from multiple field locations with disease severity from very high to none. In summary, we found a 35% reduction in foliar disease and 4.4 bushels/acre (7.6%) increase in yield for fluopyram-amended seed treatment relative to commercial base seed treatments without fluopyram. However, the disease severity, planting date, geographical locations, and weather conditions influence the efficacy and yield benefits of ILEVO.

We determined the relationship between SDS and soybean yield using meta-analytic model approach. A total of 52 uniform field experiments conducted in Illinois, Indiana, Iowa, Michigan, Wisconsin, and Ontario Canada from 2013 to 2017 comparing crop protection products against SDS were analyzed in this study. For each study, correlation and regression analyses were performed separately to determine correlation coefficients (r), intercept (ß0) and slope (ß1) and then summarized using meta-analysis. The overall mean correlation coefficient was -0.41 indicating yield was negatively correlated with FDX. That means yield will be decreased with increasing SDS foliar symptoms. The correlation was affected by disease level and cultivar with a greater magnitude in higher disease levels and with susceptible cultivars. The mean ¯ß1 was -0.33 bu/ac/%. In relative percent term, for every unit of FDX increase yield will be decreased by 0.5%.

We completed field experiments for a study coordinated by Dr. Shawn Conley to investigate the economic risk and profitability of seed treatments on soybeans planted at different populations. Briefly, planting population does not seem to have an effect on SDS but analysis of economic risk and profitability of seed treatments with different seeding rates suggested that the lowest economic risk and highest average profit with ILeVO seed treatment was obtained when seeding rates are reduced to 103,000 and 112,000 seeds/a from 140,000 seeds/a, respectively.

We have collected one year of data on nematicide seed treatments to compare their effect on management of SDS and SCN. We recently completed a study aimed to develop models to predict SDS severity and soybean yield loss using at-planting risk factors to integrate with current SDS management strategies in Decatur MI. For this study, we intensively monitored for F. virguliforme and nematode quantities at-planting, plant health throughout the growing season, end-of-season SDS severity, and yield using an unbiased grid sampling scheme from field studies. The result showed that the distribution of F. virguliforme and SCN distributions at-planting had a significant correlation with end-of-season SDS severity and yield. We identified the most effective quantitative PCR technique for identifying F. virguliforme in soybean plants and in soil. This will allow us to evaluate the effects of management practices on inoculum levels in the field and F. virguliforme levels in soybean plants.

Project Objectives

Objective 1. Determine how fungicides and nematicide seed treatment, in-furrow, and foliar fungicides will affect SDS and SCN
Objective 2. Field evaluation of integrated management of sudden death syndrome and understanding their “side effects” on F. virguliforme population and soil health
Objective 3. Develop models to quantify the negative yield impacts of SDS foliar symptoms and root rot
Objective 4. Study genetic and virulent variability of F. virguliforme using differential soybean varieties and resistance mapping for foliar chlorosis and necrosis of sudden death syndrome
Objective 5. Communicate research results with farmers, agribusinesses and other soybean stakeholders

Project Deliverables

Objective 1:
• Data on the effect of new seed treatments, in-furrow and foliar fungicides on SDS.
• Identification of products that work best for SDS management and when these products will be most needed.
• A plan for stewardship of seed treatment products.

Objective 2:
• Information on how management options may affect the risk of SDS.
• Identification of the ideal plant population with ILeVO seed protectant to maximize yield and ROI.
• Determining the influence of integrated SDS management on SDS, yield, and soil health.
• Publish manuscript demonstrating use of a pre-plant soil qPCR assay as a tool for SDS prediction
• Identify routinely measured and emerging soil health indicators for potential to serve as rapid indicators of SDS risk
• Information on how soil phosphorous and potassium levels in soil influence SDS severity
• Determining the role of flooding on reducing risk of SDS

Objective 3:
• A correlation of SDS symptoms in the field and yield.
• Models to summarize the SDS foliar symptoms - yield and root rot -yield relationships.
• A full understanding of the impact of SDS on yield at the plant and field level, which will guide recommendations for management.
• Preliminary data to help us identify the effect of SDS on yield using aerial imagery – future studies.

Objective 4:
• Phenotype and linkage map SDS chlorosis and necrosis susceptibility
• Characterize the annotation, expression, and sequence polymorphism for candidate genes located within QTL
• Silence SDS foliar susceptibility genes to confirm findings
• Screen isolates of our >500 F. virguliforme isolate collection for differential toxin production to identify potential races
• Publish findings so that results can be incorporated into breeding programs to improve foliar SDS resistance

Objective 5:
• A portfolio of products to help farmers and agribusiness professionals to understand SDS and make informed decisions on best management practices.
• Return on investment estimates for different SDS management strategies.

Progress of Work

Final Project Results

Benefit to Soybean Farmers

Our project will continue to evaluate which practices can be used to best manage SDS.

Performance Metrics

Objective 1: Things done and will continue doing.
• Data has been collected on the effect of new seed treatments for SDS management.
• We have identified when (plant population, variety resistance, etc.) effective seed treatments would work best as part of an SDS IPM plan.
• We have outlined when seed treatments should be used for SDS as part of a plan for stewardship of seed treatment products.

Objective 2: We have made progress in this objective, but much more to come.
• We have identified how some management options (e.g., corn residue) may affect the risk of SDS.
• We have identified the ideal plant population with ILeVO seed protectant to maximize yield and ROI.
• We have collected one year of data on determining the influence of integrated SDS management on SDS, yield, and soil health.
• We have published manuscript demonstrating use of a pre-plant soil qPCR assay as a tool for SDS prediction. This is setting up our next steps in identifying high risk fields.
• We are collecting data on how soil phosphorous and potassium levels in soil influence SDS severity. We did not get very much SDS in these fields in 2019 so we may do some greenhouse screens to supplement this work.
• We started collecting information on the role of flooding and drainage on reducing risk of SDS

Objective 3: This objective is nearly complete.
• We have determined the correlation of SDS symptoms in the field and yield on a plant and small plot basis.
• We have also determined the levels of yield loss expected when using our FDX ratings.
• We have collected data to determine the role of root rot and how that affects FDX and yield.
• We are collecting preliminary data to help us identify the effect of SDS on yield using aerial imagery – future studies.

Objective 4: Progress is continuing for this objective to improve breeding efforts.
• Phenotype and linkage map SDS chlorosis and necrosis susceptibility
• Characterize the annotation, expression, and sequence polymorphism for candidate genes located within QTL
• Silence SDS foliar susceptibility genes to confirm findings
• Screen isolates of our >500 F. virguliforme isolate collection for differential toxin production to identify potential races

Objective 5: Communications is an ongoing part of this project.
• We continue to add to our portfolio of products to help farmers and agribusiness professionals to understand SDS and make informed decisions on best management practices.

Project Years