Multi-pronged strategies to provide efficient, sustainable, and durable control to Sclerotinia stem rot
Sustainable Production
Crop protectionDiseaseField management
Lead Principal Investigator:
Damon Smith, University of Wisconsin
Co-Principal Investigators:
Daren Mueller, Iowa State University
Martin Chilvers, Michigan State University
Mehdi Kabbage, University of Wisconsin
+2 More
Project Code:
Contributing Organization (Checkoff):
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Brief Project Summary:

The main goal of this project is to develop a modern and highly integrated management plan for white mold in soybeans. Objectives include: evaluating current, standard soybean management practices including irrigation, row spacing, population density, and fungicide treatment applied using an advisory tool; identifying new germplasm lines resistant to Sclerotinia sclerotiorum that can be incorporated into management programs or soybean breeding programs; refining the soybean SSR advisory tool to incorporate output for different resistance forms; and exploitation of transgenic soybean silenced in NADPH oxidases to achieve abiotic and biotic stress tolerance.

Key Benefactors:
farmers, agronomists, plant pathologists, breeders

Information And Results
Final Project Results

Updated October 30, 2020:
These updates are the most significant during the duration of this funding period.

Objective 1) To evaluate current, standard soybean management practices, including irrigation, row spacing, population density, and fungicide treatment applied using an advisory tool, for use in integrated Sclerotinia stem rot management.

Data from the last several years have been consolidated into a large analysis over the winter of 2020. This study examined the effects of integrating row spacing, planting population, and foliar fungicide applications using a smartphone app on SSR disease severity index (DIX) and soybean yield potential using multi-state, multi-year field trials from 2017-2019. The interaction of row spacing and planting population had a significant effect on both DIX (P = 0.04) and yield (P < 0.01). DIX was lowest with a planting population of less than 140,000 seeds/a in a 30-in row spacing. Conversely, DIX trended higher in the 15-in row spacing and was highest when a planting population of 200,000 seeds/a was used with a 15-in row spacing. However, yields were highest in 15-in rows and decreased as planting populations were reduced at both row spacings. Fungicide application had a significant effect on DIX (P < 0.01) and yield (P < 0.01). The greatest reduction of DIX and the highest yields were observed when fungicide was applied at both R1 and R3 growth stages. While our analysis suggests wide row spacing and lower planting populations can reduce disease, it can also decrease yield potential. Therefore, additional factors such as field history and environmental factors need to be considered for field specific SSR management, but the combination of wide row spacing and low populations is recommended for high-pressure SSR fields. A research publication has been drafted and will be submitted to a peer-reviewed journal in Fall 2020. An extension fact sheet will also be developed after the research publication has been peer-reviewed (sometime in 2021).

Objective 2a) To identify new germplasm lines resistant to Sclerotinia sclerotiorum that can be incorporated into integrated management programs or into soybean breeding programs.

In Spring of 2019, 501 soybean germplasm lines (F6 seed; see previous results to track previous generations of these breeding lines) were planted at the Arlington Agricultural Experiment Station for increase. These lines were evaluated for phenotypic traits such as maturity group (2.0 – 3.0 MG) branching, hilum color, pubescence, plant height, etc. Based on these traits, 25 lines were chosen to carry forward in yield and disease evaluation in replicated field trials in 2020 (F7 seed). In addition, all 25 lines were screened in the greenhouse during the spring of 2020 against Sclerotinia sclerotiorum (the white mold pathogen). We have developed a set of 4 soybean lines that are used as “check lines” to evaluate the range of white mold resistance in new breeding materials. The 25 lines were screened in two batches against our check line panel. Using this assay technique we have identified at least 5 lines of the 25 agronomically desirable lines with resistance to the white mold pathogen that was similar to that of our most resistant check line. Thus, we expect to identify 3-5 lines from the 2020 field trials (harvest happening at the time this was written) that we will advance for further field evaluations and development into named cultivars, based on both disease resistance and favorable agronomic traits.

Objective 2b) To refine the existing soybean SSR advisory tool to incorporate model output for different forms of resistance.

In 2018, Sporecaster was made available to the public as a free download on the Google Play Store and iPhone app store. As of this report, Sporecaster was downloaded over 3,500 times from the Apple and Android stores. Daily use rates during the major “white mold season” (July and August) ranged between 600 and 800 users per day. Sporebuster is used to determine if a crop is at risk for white mold and advises if a fungicide application should be made. This app is meant to be run in-season and uses site-specific weather information to provide the risk prediction.

Sporecaster was previously validated (2016 and 2017) in commercial fields and research trials. In those validations, Sporecaster was over 80% accurate in predicting yield-limiting epidemics of white mold. Additional field validations were performed in 2018. While white mold severity was much less compared to 2016 and 2017, epidemics were present in some fields. In the 2018 validations of 16 commercial fields, Sporecaster was accurate ~80% of the time in predicting yield-limiting epidemics. In 2019 a smaller number of commercial validations were performed. Generally the app worked well, except in Northwest Iowa. In this region, the app made widespread misses. We have spent the winter of 2020 back-validating and making adjustments to the app. The major adjustments have been made to weather inputs to improve accuracy. We have also added the ability for the user to adjust a spray action threshold to what they feel comfortable with. The new version (version 1.35) is now available on both platforms for update or download for the 2020 field season.

We are also continuing to work on understanding how cultivar resistance can be included in the Sporecaster prediction to improve accuracy. This could be done by modifying the action thresholds based on resistance type. Work is underway to understand how this could be implemented, using greenhouse and field trials on varieties with known resistance levels. We spent the winters of 2019 and 2020 conducting controlled inoculations to develop a panel of check varieties that can then be used to compare commercial germplasm for resistance level. We can also use this check panel for field testing to develop new spray thresholds for Sporecaster based on resistance. Two trials were deployed in 2020 to validate this approach. In addition, we recently submitted a research publication for peer-review describing the check panel of varieties and promoting it as a tool for breeders to screen for white mold resistance.

Objective 3) Exploitation of transgenic soybean silenced in NADPH oxidases to achieve abiotic and biotic stress tolerance.

We performed qPCR using primers of the silencing construct in transformed plants in an attempt to identify transgenic lines that most highly expressed the construct. The assumption is that this would translate to identifying lower RBOH expression. From there, we took the top 6 lines with the highest construct expression, the empty-vector control, and wild-type Williams 82 plants and challenged them with two isolates of Sclerotinia sclerotiorum (1980 and #20) using our published petiole inoculation assay. No significant differences were found in disease levels. We are currently conducting a follow-up experiment of the same 8 lines, to be inoculated soon, so that we can measure the RBOH expression levels at 96 hpi compared to 0 hpi. We hope the results of this experiment will help us further refine which line(s) are stable transformants to pursue in future disease assays.

Objective 4a) Develop outreach publications and tools based on results generated here and disseminate through the national Crop Protection Network portal.

We recently updated the white mold fungicide efficacy publication (https://crop-protection-network.s3.amazonaws.com/publications/pesticide-impact-on-white-mold-sclerotinia-stem-rot-and-soybean-yield-filename-2020-02-18-181018.pdf) on the Crop Protection Network (CPN) Website. Information from this publication was used to further update efficacy ratings for white mold fungicides on the fungicide efficacy table (https://crop-protection-network.s3.amazonaws.com/publications/fungicide-efficacy-for-control-of-soybean-foliar-diseases-filename-2020-03-18-150123.pdf) also housed on the CPN website. We are actively updating the general white mold information fact sheet (https://crop-protection network.s3.amazonaws.com/publications/cpn-1005-white-mold.pdf). Many of the updates to this fact sheet are based on new research results from this work. The updates are now available on the website.

Objective 4b) Develop an electronic book compiling information about Sclerotinia stem rot and management of the disease for a diverse audience.

The framework for the electronic book is now in place and content is starting to be added. We will be working on completing this book by the end of 2021.

The results of the work reported here has the following significance:
1. The research guides management recommendations for white mold which include reducing planting populations down to around 120,000 seed per acre and moving to 30-in row spacings without dramatic yield losses where white mold is a significant problem.
2. Using white mold resistant soybean varieties is also critical in a complete white mold management plan. We are working to improve varieties that have good resistance and yield well. These can be used in conventional production systems or as breeding material in other programs.
3. The Sporecaster tool continues to be improved. Eventual improvements will encompass the ability to change spray thresholds based on known resistance levels in soybean varieties.
4. We continue to explore alternative types of engineered resistance against white mold. While progress was initially slow, we are making excellent headway and hope to identify some tools to dramatically improve resistance levels in soybeans in the future.

The United Soybean Research Retention policy will display final reports with the project once completed but working files will be purged after three years. And financial information after seven years. All pertinent information is in the final report or if you want more information, please contact the project lead at your state soybean organization or principal investigator listed on the project.