Sclerotinia stem rot (SSR), caused by Sclerotinia sclerotiorum, is one of the most important diseases of soybean. Disease management is complicated by the long-term survival of sclerotia in the soil and the absence of resistance in elite, commercial cultivars. Furthermore, the lifecycle of S. sclerotiorum in soybean fields is highly dependent on weather conditions, leading to a highly sporadic occurrence of the disease over seasons and an aggregated distribution within fields. Management relies on a multi-pronged approach of combining partially resistant cultivars with cultural practices, such as altering row spacing and planting population, along with chemical control. These control measures are constrained by economic trade-offs, incomplete efficacy of chemicals, and a lack of understanding of application timing for fungicides. Newer tools have been developed to improve management, such as disease prediction models that can assist farmers in making decisions about fungicide application. This review aims to introduce the Sclerotinia pathosystem in soybean, while covering the complicated biology of S. sclerotiorum that leads to the need for integrated management by soybean farmers.

Sclerotinia sclerotiorum, the causal agent of Sclerotinia stem rot, is a devastating fungal pathogen of soybean that can cause significant yield losses to growers when environmental conditions are favorable for the disease. The development of resistant varieties has proven difficult. However, poor resistance in commercial cultivars can be improved through additional breeding efforts and understanding the genetic basis of resistance. The objective of this project was to develop soybean germplasm lines that have a high level of Sclerotinia stem rot resistance to be used directly as cultivars or in breeding programs as a source of improved Sclerotinia stem rot resistance. Sclerotinia stem rot-resistant soybean germplasm was developed by crossing two sources of resistance, W04-1002 and AxN-1-55, with lines exhibiting resistance to Heterodera glycines and Cadophora gregata in addition to favorable agronomic traits. Following greenhouse evaluations of 1,076 inbred lines derived from these crosses, 31 lines were evaluated for resistance in field tests during the 2014 field season. Subsequently, 11 Sclerotinia stem rot resistant breeding lines were moved forward for field evaluation in 2015, and seven elite breeding lines were selected and evaluated in the 2016 field season. To better understand resistance mechanisms, a marker analysis was conducted to identify quantitative trait loci linked to resistance. Thirteen markers associated with Sclerotinia stem rot resistance were identified on chromosomes 15, 16, 17, 18, and 19. Our markers confirm previously reported chromosomal regions associated with Sclerotinia stem rot resistance as well as a novel region of chromosome 16. The seven elite germplasm lines were also re-evaluated within a greenhouse setting using a cut petiole technique with multiple S. sclerotiorum isolates to test the durability of physiological resistance of the lines in a controlled environment. This work presents a novel and comprehensive classical breeding method for selecting lines with physiological resistance to Sclerotinia stem rot and a range of agronomic traits. In these studies, we identify four germplasm lines; 91–38, 51–23, SSR51–70, and 52–82B exhibiting a high level of Sclerotinia stem rot resistance combined with desirable agronomic traits, including high protein and oil contents. The germplasm identified in this study will serve as a valuable source of physiological resistance to Sclerotinia stem rot that could be improved through further breeding to generate high-yielding commercial soybean cultivars.

Sclerotinia stem rot (SSR) epidemics in soybean, caused by Sclerotinia sclerotiorum, are currently responsible for annual yield reductions in the United States of up to 1 million metric tons. In-season disease management is largely dependent on chemical control but its efficiency and cost-effectiveness depends on both the chemistry used and the risk of apothecia formation, germination, and further dispersal of ascospores during susceptible soybean growth stages. Hence, accurate prediction of the S. sclerotiorum apothecial risk during the soybean flowering period could enable farmers to improve in-season SSR management. From 2014 to 2016, apothecial presence or absence was monitored in three irrigated (n = 1,505 plot-level observations) and six nonirrigated (n = 2,361 plot-level observations) field trials located in Iowa (n = 156), Michigan (n = 1,400), and Wisconsin (n = 2,310), for a total of 3,866 plot-level observations. Hourly air temperature, relative humidity, dew point, wind speed, leaf wetness, and rainfall were also monitored continuously, throughout the season, at each location using high-resolution gridded weather data. Logistic regression models were developed for irrigated and nonirrigated conditions using apothecial presence as a binary response variable. Agronomic variables (row width) and weather-related variables (defined as 30-day moving averages, prior to apothecial presence) were tested for their predictive ability. In irrigated soybean fields, apothecial presence was best explained by row width (r = −0.41, P < 0.0001), 30-day moving averages of daily maximum air temperature (r = 0.27, P < 0.0001), and daily maximum relative humidity (r = 0.16, P < 0.05). In nonirrigated fields, apothecial presence was best explained by using moving averages of daily maximum air temperature (r = –0.30, P < 0.0001) and wind speed (r = –0.27, P < 0.0001). These models correctly predicted (overall accuracy of 67 to 70%) apothecial presence during the soybean flowering period for four independent datasets (n = 1,102 plot-level observations or 30 daily mean observations).

Sclerotinia stem rot (SSR), caused by Sclerotinia sclerotiorum, is a globally important, yield limiting disease of soybean. Progress has been made in our understanding of this pathosystem at the plant level, such as the key role of oxalic acid in disease development and the importance of cell wall-degrading enzymes and other secreted proteins. Unfortunately, advances have largely focused on the fungal side of this interaction and only provide glimpses into the plant mechanisms governing resistance to this pathogen. With the absence of commercially available resistant soybeans, chemical and cultural solutions are being used by farmers to manage SSR with limited success. Additional research is needed to identify S. sclerotiorum resistance mechanisms that can be exploited to improve genetic resistance in soybean and decrease reliance on spray regimes. Technologies such as transgenics and RNAi could be exploited to improve the level of resistance to S. sclerotiorum in soybean. This review offers insight into the hurdles of managing SSR at the plant level and potential solutions that might be adopted in the future.

Sclerotinia sclerotiorum population variability directly affects Sclerotinia stem rot (SSR) resistance breeding programs. In the north-central United States, however, soybean germplasm selection has often involved only a single isolate. Forty-four S. sclerotiorum isolates from Illinois, Michigan, Minnesota, Nebraska, Wisconsin, Poland, and across 11 different host species were evaluated for variation in isolate in vitro growth, in vitro oxalate production, and in planta aggressiveness on the susceptible soybean ‘Williams 82’. Significant differences (P < 0.0001) were detected in isolate in planta aggressiveness, in vitro growth, and in vitro oxalate production. Furthermore, diverse isolate characteristics were observed within all hosts and locations of collection. Aggressiveness was not correlated to colony growth and was only weakly correlated (r = 0.26, P < 0.0001) to isolate oxalate production. In addition, the host or location of collection did not explain isolate aggressiveness. Isolate oxalic acid production, however, may be partially explained by the host (P < 0.05) and location (P < 0.01) of collection. Using a representative subset of nine S. sclerotiorum isolates and soybean genotypes exhibiting susceptible or resistant responses (determined using a single isolate), a significant interaction (P = 0.04) was detected between isolates and genotypes when SSR severity was evaluated. Our findings suggest that screening of S. sclerotiorum-resistant soybean germplasm should be performed with multiple isolates to account for the overall diversity of S. sclerotiorum isolates found throughout the soybean-growing regions of the United States.

In soybean, Sclerotinia sclerotiorum apothecia are the sources of primary inoculum (ascospores) critical for Sclerotinia stem rot (SSR) development. We recently developed logistic regression models to predict the presence of apothecia in irrigated and nonirrigated soybean fields. In 2017, small-plot trials were established to validate two weather-based models (one for irrigated fields and one for nonirrigated fields) to predict SSR development. Additionally, apothecial scouting and disease monitoring were conducted in 60 commercial fields in three states between 2016 and 2017 to evaluate model accuracy across the growing region. Site-specific air temperature, relative humidity, and wind speed data were obtained through the Integrated Pest Information Platform for Extension and Education (iPiPE) and Dark Sky weather networks. Across all locations, iPiPE-driven model predictions during the soybean flowering period (R1 to R4 growth stages) explained end-of-season disease observations with an accuracy of 81.8% using a probability action threshold of 35%. Dark Sky data, incorporating bias corrections for weather variables, explained end-of-season disease observations with 87.9% accuracy (in 2017 commercial locations in Wisconsin) using a 40% probability threshold. Overall, these validations indicate that these two weather-based apothecial models, using either weather data source, provide disease risk predictions that both reduce unnecessary chemical application and accurately advise applications at critical times.

Identifying the optimal timing for fungicide application is crucial in order to maximize the control of Sclerotinia stem rot (SSR), which is caused by Sclerotinia sclerotiorum. In this study, the impact of canopy closure and soil temperature on apothecia production was investigated to optimize fungicide application timing. Replicated soybean plots with a row spacing of 0.36 and 0.38 or 0.76 m were established in 2015 and 2016 in an irrigated soybean field at Michigan State University's Montcalm Research Center. The number of apothecia and ascospores and the incidence of SSR were monitored two times per week for 10 to 12 weeks. In both row-spacing trials, apothecia were observed earlier in 2016 (before the R1 growth stage) than in 2015 (between R1 and R2). The maximum number of apothecia was 50 times higher with the 0.36-m row spacing than with the 0.76-m row spacing in 2015 but was 2.5 times higher with the 0.76-m row spacing than with the 0.38-m row spacing in 2016, though the overall numbers were much lower in 2016. The apothecia distribution pattern was synchronized with the canopy closure pattern and the soil temperature profile. The peak number of apothecia was observed when canopy closure reached at least 50% and when average soil temperature in the row was between 21.5 and 23.5°C. In 91% of the cases, the presence of apothecia was observed when the percentage of light blocked was 70%, and no apothecia germinated in the absence of light or under full light exposure. During the first 50 days after plant emergence, the rate of canopy closure was higher in 2016 than in 2015, and the first diseased plant was observed earlier in 2016 (R2) than in 2015 (R5). Canopy closure and the distance of the sampling point from the soybean row explained much of the variability in the number of apothecia. These results can partially explain the inconsistent efficacy of fungicide applications based on the soybean growth stage and will be helpful for informing disease models and fine-tuning fungicide application strategies.

The development and implementation of research-inspired, discovery-based experiences into science laboratory curricula is a proven strategy for increasing student engagement and ownership of experiments. In the novel laboratory module described herein, students learn to express, purify, and characterize a carbohydrate-active enzyme using modern techniques and instrumentation commonly found in a research laboratory. Unlike in a traditional cookbook-style experiment, students generate their own hypotheses regarding expression conditions and quantify the amount of protein isolated using their selected variables. Over the course of three 3-hour laboratory periods, students learn to use sterile technique to express a protein using recombinant DNA in E. coli, purify the resulting enzyme via affinity chromatography and dialysis, analyze the success of their purification scheme via SDS-PAGE, assess the activity of the enzyme via an HPLC-based assay, and quantify the amount of protein isolated via a Bradford assay. Following the completion of this experiment, students were asked to evaluate their experience via an optional survey. All students strongly agreed that this laboratory module was more interesting to them than traditional experiments because of its lack of a pre-determined outcome and desired additional opportunities to participate in the experimental design process. This experiment serves as an example of how research-inspired, discovery-based experiences can benefit both the students and instructor; students learned important skills necessary for real-world biochemistry research and a more concrete understanding of the research process, while generating new knowledge to enhance the scholarly endeavors of the instructor.