Project Details:

Title:
Multi-pronged strategies to provide efficient, sustainable, and durable control of Sclerontinia stem rot - Year 3

Parent Project: Multi-Pronged Strategies to Provide Efficient Sustainable and Durable Control to Sclerotinia Stem Rot
Checkoff Organization:North Central Soybean Research Program
Categories:Soybean diseases
Organization Project Code:MSN241179
Project Year:2021
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)
Keywords: Disease Management, Disease prediction, Diseases resistance, Epidemiology, Sclerotinia sclerotiorum, Sclerotinia stem rot, White Mold

Contributing Organizations

Funding Institutions

Information and Results

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Project Summary

Impact of Sclerotinia sclerotiorum on soybean
Sclerotinia stem rot (SSR; white mold) is caused by Sclerotinia sclerotiorum and consistently ranks in the top ten diseases plaguing global soybean crops. Between 2010 and 2014, SSR resulted in total soybean yield losses valued at an estimated $1.2 billion in the U.S. and Canada (Allen et al., 2017). Furthermore, according to a United Soybean Board report from 2011, SSR epidemics in the Great Lakes region alone were responsible for 94% of nationwide losses to the disease and cost regional farmers ~$138 million (USDA-NASS, 2015). Sclerotinia stem rot is infamously characterized by its challenging fungal promiscuity and longevity, and by the subsequently devastating crop losses; farmers in the north central region of the United States justifiably rank white mold management second behind soybean cyst nematode (Heterodera glycines) in significance and concern. Michigan farmers ranked Sclerotinia stem rot as the number one (tied with planting rates) soybean production issue to be researched over multiple meetings conducted over the 2017/2018 winter meeting season (Staton, 2018). Successful control requires farmers to use multiple tools in an integrated disease management plan. The most accessible tools are often simply manipulating standard soybean management practices to reduce pathogen inoculum and subsequent disease.

Management of Sclerotinia stem rot in soybean
The integrated management of SSR utilizes a combination of cultural, chemical, and biological control practices (Peltier et al., 2012). Some practices may include, crop rotation using non-host crops (Garcia-Garza et al., 2002; Mueller et al., 2002; Rousseau et al., 2007), practicing reduced tillage (Garcia-Garza et al., 2002; Kurle et al., 2001; Mueller et al., 2002), using resistant cultivars (Grau et al., 1982; Hoffman et al., 2002; Kurle et al., 2001), modifying the soybean canopy through seeding rate and row spacing (Jaccoud-Filho et al., 2016; Kurle et al., 2001; Lee et al., 2005), and applying in-season chemical control (Mueller et al., 2004; Peltier et al., 2012; Sumida et al., 2015; Saharan and Mehta, 2008). Many of these practices manipulate the host environment to be unfavorable for diseases development, such as increasing air flow through the canopy or reducing inoculum development in the field.

In Wisconsin, agronomic studies have determined that soybeans planted on either a 7.5- or 15- inch row spacing will consistently yield 7-10% more than soybeans planted at a wider 30-inch row spacing (Bertram and Pedersen, 2004). Additionally, this study reports that, at a narrow 15- inch row spacing, optimal yields may be achieved at population densities of 173,000- 272,000 seeds/acre. Optimal population densities for 30-inch rows, however, range from 124,000-222,000 seeds/acre. The development of the SSR fungus, and subsequent soybean infection, is known to be dependent on canopy closure and favored by cool, moist conditions (Boland and Hall, 1988a). High-yielding soybean row spacing and seeding rates, therefore, inherently increase the risk of SSR development by reducing the time to full canopy closure and by reducing canopy ventilation.

Studies in Brazil have shown that narrow row spacing and high population density increases white mold disease severity and incidence (Jaccoud-Filho et al., 2016). The seeding rates used in this research, however, are not representative of the optimal populations recommended for soybeans grown in the North Central region. In Michigan, population was also found to be positively correlated with disease severity and negatively correlated with yield (Lee et al., 2005); this research, however, only considered a narrow range of high density seeding rates in 7.5- or 30- inch row spacings. As a result, it is difficult to give regionally appropriate SSR management recommendations in environments prone to SSR. Effective integrated management systems require integrated evaluation of regional standards in irrigation, row spacing, seeding rate, and fungicide treatment and their effects on white mold incidence and severity. Moreover, it is important to investigate how manipulation of these practices directly affects the biology surrounding fungal development, and as discussed below, the element of plant resistance

Resistance to S. sclerotiorum in soybean
In the absence of elicitors of strong host resistance to S. sclerotiorum, polygenic alleles with minor effects are widely believed to contribute to resistance to S. sclerotiorum. Partially resistant soybean genotypes have been selected and identified (Bastein et al, 2014; Boland and Hall, 1987; Grau et al., 1982; Han et al., 2008; Huynh et al., 2010; Iquira et al., 2015; Kim and Diers, 2000; Li et al., 2010; McCaghey and Willbur et al., 2017; Sebastian et al., 2010; Zhao X et al., 2015). Overall, 103 quantitative trait loci (QTL) that contributed to resistance have been recorded in Soybase on 18 out of 20 chromosomes (Soybase, 2010). Identification of these loci provide an opportunity to use marker assisted selection (MAS) as a potential tool for the screening of lines resistant to SSR. However, such an approach presents practical challenges that must be overcome to deploy SSR resistance.

While polygenic resistance (quantitative resistance) is thought be more durable than qualitative resistance; breeding using quantitative resistance is complicated. This includes the “drag” of deleterious and undesirable traits within and near QTL regions, existence of numerous QTL with minimal sole contribution to SSR resistance, and epistatic interactions that pose a challenge to heritability (Moellers et al., 2017). Furthermore, the genetics of physiological resistance to S. sclerotiorum are not well understood. Current ‘field tolerant’ soybean cultivars may be tolerant due to avoidance phenotypes such as flowering time and plant height or entangled environmental and genetic interactions. For example, Kim and Diers (2000) used Novartis S19-90 as a source of resistance in breeding lines and mapped three QTL that accounted for 8-10% of disease severity (DSI) variability. However, two were associated with disease escape mechanisms of greater height, increased lodging, and later flowering date. These escape mechanisms make screening for physiological disease resistance in a field setting difficult. Furthermore, flowering time or canopy closure may differentially align with apothecial development in varied environments, thus impacting disease resistance across environments. Additionally, screening for resistance is complicated by aggregated distributions of inoculum in field trials, if canopy closure and favorable microenvironments for infection differ in a field, resulting in differential disease pressure. To circumvent resistance conferred by escape mechanisms, breeders have mapped QTL and screened lines using inoculation methods that avoid this issue (Arahana et al., 2001; Guo et al., 2008; Vuong et al., 2008). However, other technologies such as genetic modification or gene editing could help advance the industry toward improved resistance to Sclerotinia stem rot.

Chemical Control
Spray regimes for white mold are most effective when targeting the flowering window, particularly at the R1 (beginning bloom) growth stage (Mueller et al., 2004). In greenhouse studies, certain fungicides have all demonstrated suppression of S. sclerotiorum signs and symptoms on leaves (Mueller et al., 2002). Chemical sprays may be ineffective and inconsistent when the incidence of SSR is high. The effectiveness of fungicides differs based on the chemical used and application timing in north-central regional studies (Byrne and Chilvers, 2016; Huzar and Novakowiski et al., 2017; Mueller et al., 2016; Smith et al., 2015). Furthermore, field trials demonstrate effective control against S. sclerotiorum by several pesticides and herbicides, but they do not provide complete control, and incidence after chemical sprays can range from 0-60% in plot trials (Mueller et al., 2002 and 2004). Application coverage is also important, with flat-fan spray nozzles with high-fine to mid-medium droplets (200-400 µm) being the most effective. Poor coverage, fungicide rate, mixing, sprayer calibration, and environmental conditions can all affect fungicide efficacy. Coverage is influenced by the density of the canopy, droplet size, and spray volume (Derksen et al., 2008). Additionally, the lactofen formulation used in Dann et al. (1999) had phytotoxic effects that resulted in a 10% yield decrease in the absence of SSR. Lactofen can also cause phenotypic effects such as stunting and discolored, malformed leaves (Huzar-Novakowiski et al., 2017).

Epidemiological modeling to improve management strategies
Historically, S. sclerotiorum apothecia and SSR incidence were both spatially aggregated and correlated within sectors of soybean fields (Boland and Hall, 1988b). More recently, the distribution of SSR has been correlated with apothecia in both canola (Qandah and del Rio Mendoza 2012) and soybean (Wegulo et al., 2000). In both studies, disease incidence decreased as distance from apothecial inoculum sources increased. Furthermore, ascospores were deposited near the apothecia within soybean fields (Wegulo et al., 2000), which supports the relationship between apothecia and disease. Sclerotial load, determined by intensive soil sampling, was not found to describe white mold incidence in bean fields (McDonald and Boland, 2004). Apothecial presence, therefore, is a promising candidate to use for SSR risk assessment in soybean fields. In the Great Lakes region, Willbur et al. (2018a) combined much of this prior knowledge of SSR in other crops, with new data to develop SSR risk models using environmental parameters including maximum temperature, mean relative humidity, and maximum wind speed to predict apothecial presence. Models were used in a set of subsequent field validation experiments to test accuracy of prediction of end-of-season disease levels. In those validation efforts in Wisconsin, Iowa, and Michigan models predicted SSR over 80% of the time (Willbur et al., 2018b). Furthermore, sources of weather data were tested, including data from an open-source weather provider, darksky.net. Weather from this source were nearly as accurate as weather from on-site weather stations (Willbur et al., 2018b). Plant phenology information and canopy and row-spacing parameters have subsequently been combined with these prediction models into a smartphone application that can be used anywhere to predict the risk of apothecial presence during the soybean bloom period. Thus, timely fungicide applications can be made if weather is conducive or fungicide sprays can be saved if favorable conditions do not exist before and during bloom. The smartphone application is available on the Android and iPhone platforms and is called Sporecaster.

Project Objectives

Research Goal
To develop a modern and highly integrated management plan for white mold of soybean.

Objectives

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.

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

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

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

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

Project Deliverables

The results of this research will be used to not only increase our understanding of the biology and epidemiology of SSR on soybean, but will be used to formulate improved, modern integrated management decisions for SSR control in soybean. Several important outcomes and deliverables will result from this research. These include:

-Peer-reviewed publications detailing the findings pertaining to integrated management of SSR
-A second peer-reviewed publication detailing adjustment to fungicide regime based on soybean SSR resistance level
-Further validation of Sporecaster on soybean
-Demonstration plots will be available for field day and other educational opportunities in the participating states (Iowa, Michigan, and Wisconsin) where integrated strategies for managing SSR will be showcased
-Fact sheets and publications will be generated using the most current information as a result of this coordinated effort (three personnel on this proposal have extension appointments in addition to their research appointments).
-Results of research will be presented at stakeholder meetings
-Blog articles will be written on extension personnel websites

Progress of Work

Final Project Results

Benefit to Soybean Farmers

Soybean farmers and agriculture scientists will benefit from this research by:
-Gaining an improved understanding of key, modern management strategies for SSR on soybean
-Improved management of SSR in soybean resulting in improved yield and profitability
-Improved timing of necessary fungicide applications through use of the advisory tool will improve fungicide efficacy and disease control
-Reduced unnecessary fungicide inputs i.e. where weather conditions are non-conducive to apothecia production during flowering a fungicide application can be avoided
-New and improved outreach materials will be developed, including updated web pages and handouts

Performance Metrics

1. Peer-reviewed publication detailing the findings pertaining to integrated management of SSR will be written in winter of 2020. Data for this publication were generated based on this work.
2. A second peer-reviewed publication detailing adjustment to fungicide regime based on soybean SSR resistance level is planned based on data from this project.
3. Further validation of Sporecaster on soybean. These data will be used to improve accuracy.
4. Demonstration plots were available for field days and other educational opportunities in the participating states (Iowa, Michigan, and Wisconsin) where integrated strategies for managing SSR will be showcased.
5. Fact sheets and publications will be generated using the most current information as a result of this coordinated effort.
6. Results of research will be presented at stakeholder meetings in all states involved.
7. Blog articles will be written on extension personnel websites.

Project Years