Progress 09/01/14 to 08/31/16
Outputs
Target Audience:Soybean growers, agricultural industry professionals, and agricultural scientists in the State of Wisconsin and the North Central Region of the U.S. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?Several groups in Wisconsin and the North Central region were presented with results of data from efforts conducted on this research project. Results were presented to seven separate groups in Wisconsin totaling 353 attendees. These groups were comprised mostly of growers and consultants. Approximately 200 attendees were also presented with these data at the Wisconsin Crop Management Conference. This group was comprised of agriculture industry professionals and growers from Wisconsin and the north central region. Data presented included progress in the development of Sclerotinia stem rot-resistant soybean germplasm and the prediction model development and validation. In addition, a doctoral level graduate student and undergraduate students were trained in plant pathology under this project. An online webinar was also devleoped describing forecasting systems in soybean and specifically the model developed here. That webinar can be viewed here:http://www.plantmanagementnetwork.org/edcenter/seminars/soybean/SoybeanDiseaseForecasting/. How have the results been disseminated to communities of interest?Approximately 700 individuals have been presented with data from this project at local and regional extension meetings in 2016. The data have been used to demonstrate new approaches to controlling Sclerotinia stem rot and highlight new technology coming down the pipeline. What do you plan to do during the next reporting period to accomplish the goals?
Nothing Reported
Impacts
What was accomplished under these goals?
Objective 1: After multiple field and greenhouse evaluations, 31 breeding lines with multi-disease resistance were selected and evaluated for resistance to Scerlotinia stem rot (SSR) in field tests during 2014-2016 field seasons. Germplasm lines 51-23, SSR51-70, and 52-82B exhibited a high level of SSR resistance and desirable agronomic traits. In 2015, 51-23 yielded 3,156.2 kg/ha, and SSR51-70 yielded 2,801.8 kg/ha. The highest yield achieved was 3,742.8 kg/ha for germplasm line 52-82B. All lines exhibited protein content above the 35 percent average for the Great Lakes Region and oil content above 18 percent. Based on disease resistance and positive agronomic traits, crosses for these three lines were initiated in the summer of 2016. Crosses were conducted with the assistance of Dr. Asheesh Singh's lab at Iowa State University and consisted of a cross between 51-23 and 52-82B and SSR 51-70 and 51-23. The cross between 51-23 and 52-82B was the first cross made between lines containing both sources of SSR resistance (AxN-1-55 and W04-1002). AxN-1-55 (PI 640911) was released as public germplasm (Diers et al.) with partial SSR resistance in 2006. AxN-1-55 was derived from a single F4 plant that expressed 75% plant survival after challenge with S. sclerotiorum in controlled inoculation trials. W04-1002 is an inbred line derived as a pure line selection from PI 567157A (Impullitti et al., 2009). W04-1002 has expressed 90 to 100% survival after repeated challenges with multiple isolates of S. sclerotiorum and is considered highly resistant to the pathogen (Peltier and Grau, 2008). The mechanisms responsible for resistance in these two lines is believed to be very different. Four planting dates of each parental line were made at the research farm of Iowa State University, to account for differential maturity dates and to ensure flowering dates corresponded for crossing. Crosses between lines were conducted by graduate student Megan McCaghey and Dr. Asheesh Singh's Lab Manager, Jennifer Hicks on July 11th, 2016 and July 28th, 2016. The crosses yielded as follows: A16201-UW (51-23/52-82B)-41 seeds; A16202 (SSR51-70/51-23)-76 seeds. Seed was shipped to the Dr. Damon Smith's Lab, and 30 seeds from each cross were planted in the UW West Madison Greenhouses for seed increase on September 23rd, 2016. F1 germination rates were 29 of 30 seeds for 116201 and 28 of 30 for 116202. The soybeans have been trellised incrementally to conserve pod development on lateral branches. Plants are currently at the R2-R3 and beginning pod set. F1 plant phenotypes will be recorded, monitored for trellising, and seeds will be harvested in January of 2017 in preparation for field evaluations in the summer of 2017. Gerplasm line 91-38, partially developed under support from this project is in the process of being increased and released as a variety by the name 'Dane', for the 2018 field season. The non-GMO, food-grade soybean market is small. However, we have polled several soybean farmers on the board of the Wisconsin Soybean Association and they are very interested in this market and soybean variety. They believe that this soybean can provide them with a high-value product for a niche-market that takes some of the management challenges out of growing soybeans in the upper Midwest. While yield of 'Dane' (91-38) might be a bit below commercial standards, the protein levels (>38%), yellow hilum, and the fact that white mold management will not need to be used on this variety, allow for farmers to make a nice premium from 'Dane'. 'Dane' (91-38) soybean variety has been developed and field tested for 3 growing seasons in various environments. We believe it has been reasonably vetted and is ready for release. Thus, we need two cycles of increase to release to farmers by the 2018 growing season. To release in this timeframe, we plan to increase the variety with collaborators in Chile during the winter of 2017. We then plan to increase again in Wisconsin in conjunction with UW Foundation seeds in the summer of 2017. This should result in enough seed to begin to release to farmers in 2018. Moving forward, UW Foundation Seeds would grow and license 'Dane'. To our knowledge, 'Dane' soybean will be the first soybean variety released from the University of Wisconsin since 1970. 'Dane' soybean will provide a solution for growers who want to grow non-GMO, food-grade soybeans in the upper Midwest and who do not want to invest in expensive white mold management strategies such as fungicide application. 'Dane' soybean will be just the first of a long line of soybean varieties that will be developed at the Unviersity of Wisconsin. REFERENCES Diers, B.W., Kopich-Obuch, F.J., Hoffman, D.D., Hartman, G.L., Pedersen, W.L., Grau, C.R., and Wang, D. 2006. Registration of AxN-1-55 soybean germplasm with partial resistance to Sclerotinia stem rot. Crop Sci. 46:1403-1404. Impullitti, A.E., Malvick, D.K. and Grau, C.R., 2009. Characterizing reaction of soybean to Phialophora gregata using pathogen population density and DNA quantity in stems. Plant Dis. 93:734-740. Peltier, A.J. and Grau, C.R., 2008. The influence of light on relationships between Sclerotinia stem rot of soybean in field and controlled environments. Plant Dis.92:1510-1514. Objective 2 In 2014 and 2015, we monitored the growth and development of S. sclerotiorum and collected detailed data of the progression and severity of white mold disease in Wisconsin soybean fields. Publically available weather data were used in a series of statistical models to predict disease development to generate a single model for spray advisory purposes. The experimental model used in 2016 utilized maximum air temperature, maximum relative humidity, and maximum wind speed to predict the risk of infection by the white mold fungus. It also has the capability of compensating for previous fungicide applications in programs that require more than one application of fungicide per season. It also uses long-term weather information as input variables. Specifically, 30-day moving averages of air temperature and leaf wetness are used to calculate the daily white mold estimates. This is novel as the biology of the white mold fungus suggests that 30- or 40-day weather periods are required for the formation of mushroom-like fungal structures called apothecia. The model is also novel in that it was developed using logistic regression techniques. This allows the researchers to calculate the daily risk, or probability, that apothecia are likely to be present in soybean fields. This is analogous to a daily weather report. Current model thresholds are set so that when the model predicts a 40% chance of apothecia being present in a soybean field a fungicide application is recommended. Below 40% chance, no fungicide application would be recommended. In 2016, model validations were conducted in Iowa, Michigan, and Wisconsin. The model predicting apothecial presence was available through the integrated pest information platform for extension and education (iPiPE). In Wisconsin, both research trials and grower fields were scouted for apothecia and subsequent white mold development throughout the season. In 14 of the 19 scouted fields, the model successfully predicted the risk of inoculum presence during the susceptible growth stages; these results were verified by the resulting presence or absence of disease. Currently, the model is exhibiting a promising 74% success rate across a variety of soybean growing systems throughout the state. The model will be further refined using the high resolution results from these tri-state validations.
Publications
- Type:
Journal Articles
Status:
Published
Year Published:
2016
Citation:
Willbur, J. F., Ding, S., Marks, M. E., Lucas, H., Grau, C. R., Groves, C. L., Kabbage, M., and Smith, D. L. 2017. Comprehensive Sclerotinia stem rot screening of soybean germplasm requires multiple isolates of Sclerotinia sclerotiorum. Plant Dis. In-Press.
- Type:
Journal Articles
Status:
Published
Year Published:
2016
Citation:
McCaghey, M., Willbur, J., Grau, C., Chapman, S. Diers, B., Groves, C., Ranjan, A., Kabbage, M., Smith, D. 2016. Development and evaluation of germplasm lines resistant to Sclerotinia stem rot.
- Type:
Journal Articles
Status:
Published
Year Published:
2016
Citation:
Willbur, J., Lucas, H., Mueller, B., Chapman, S., Kabbage, M., and Smith, D. 2016. Validation and refinement of a predictive model for Sclerotinia sclerotiorum apothecial development in soybean fields. Phytopathology 106: S4.5.
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Progress 10/01/14 to 09/30/15
Outputs
Target Audience: Soybean growers, agricultural industry professionals, and agricultural scientists in the State of Wisconsin and the North Central Region of the U.S. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided? Several groups in Wisconsin and the North Central region were presented with results of data from efforts conducted on this research project. Results were presented to seven separate groups in Wisconsin totaling 409 attendees. These groups were comprised mostly of growers and consultants. Approximately 200 attendees were also presented with thes data at the Iowa Integrated Crop Management conference. This group was comprised of agriculture industry professionals and growers from the north central region. Data presented included progress in the development of Sclerotinia stem rot-resistant soybean germplasm and the prediction model development and validation. In addition, a doctoral level graduate student and undergraduate students are being trained in plant pathology under this project. How have the results been disseminated to communities of interest? Approximately 609 individuals have been presented with data from this project at local and regional extension meetings in 2015. The data have been used to demonstrate new approaches to controlling Sclerotinia stem rot and highlight new technology coming down the pipeline. What do you plan to do during the next reporting period to accomplish the goals? The 2016 growing season will be used to collect further field data for making resistant soybean germplasm selections. Additional data will be collected in 2016 to refine the apothecial prediction model. Seperate validation experiments will also be conducted using the newest iteration of the prediciton model. Additionally, we are studying light quality effects on apothecial development for integration into an optimized forecasting model.
Impacts
What was accomplished under these goals?
Objective 1: Previously, resistant soybean germplasm was generated by crossing a highly resistant experimental line (W04-1002) with lines exhibiting good resistance to other diseases such as brown stem rot, soybean sudden death syndrome, and soybean cyst nematode. In addition, another set of crosses was performed using the experimental breeding line (AxN-1-55). This work was supported by the WSMB. After multiple screenings, 31 lines were selected for advanced white mold field screening in 2014. Lines were planted in a nursery with four check varieties. Disease ranged from almost 60 disease severity index (DSI) units in the susceptible breeding line 91-44 to zero DSI units for SSR81-23. All lines identified as physiologically resistant in greenhouse evaluations had less than 20 DSI units in the field trials. Yield loss is generally not expected until rating reaches 25 or more DSI units (Smith, personal communication). Yield ranged from 55.9 bu/a for AxN-1-55 to 26.6 bu/a for SSR81-123. Lodging was an important yield component in this trial. Lodging was significantly (α=0.05) correlated with yield. Breeding lines that lodged severely, yielded less than lines that had lower lodging scores (correlation coefficient = -0.47). Lines with the best physiological resistance to white mold (mostly the 9 x 1 population) tended to yield low-to-moderately in the 2014 trial due to lodging and perhaps yield drag due to the high level of physiological resistance present in many of these lines. Further evaluation and selection took place in 2015. Sixteen lines with four check varieties were planted in a nursery. DSI units ranged from 51 to 2.5 units (Table 1). Yield was consistent with results from 2014. Highly resistant plants tended to yield less than some susceptible lines. However, plants heavily damaged by white mold (DSI units >25) had significant yield reduction compared to those that had a low DSI score. Germplasm lines 91-38, 91-224B, and SSR51-70 tended to have a good balance of white mold resistance and yield with minimal lodging in 2015. 91-38 yielded 43 bu/a, 91-224B yielded 47 bu/a, while SSR51-70 also yielded 47 bu/a. Highest yield achieved was 62 bu/a for 52-82B. However, the 5 x 2 population tends to be less consistent in resistance response under controlled inoculations, and in field evaluations, compared to the 9 x 1 population or the 5 x 1 population. White mold-resistant soybean germplasm has been registered with the Wisconsin Alumni Research Foundation (WARF). WARF promotes innovative research by facilitating the commercialization of scientific technologies; therefore, soybean germplasm can be accessed by public and private breeders to develop locally and globally available commercial varieties. Interest in white mold resistance from several commercial seed companies has been high. Objective 2: In 2014, we monitored the growth and development of S. sclerotiorum and collected detailed data of the progression and severity of white mold disease in Wisconsin soybean fields. Publically available weather data were used in a series of statistical models to predict disease development to generate a single model for spray advisory purposes. The experimental model uses air temperature and leaf wetness to predict the risk of infection by the white mold fungus. It also has the capability of compensating for previous fungicide applications in programs that require more than one application of fungicide per season. It also uses long-term weather information as input variables. Specifically, 30-day moving averages of air temperature and leaf wetness are used to calculate the daily white mold estimates. This is novel as the biology of the white mold fungus suggests that 30- or 40-day weather periods are required for the formation of mushroom-like fungal structures called apothecia. The model has the following formula: Probability of apothecial development = 172.0 - 2.011(Fungicide) - 10.72 (30-day Mean Air Temperature) + 5.76 (30-day Maximum Leaf Wetness) The model is also novel in that it was developed using logistic regression techniques. This allows the researchers to calculate the daily risk, or probability, that apothecia are likely to be present in soybean fields. This is analogous to a daily weather report. Current model thresholds are set so that when the model predicts a 40% chance of apothecia being present in a soybean field, a fungicide application is recommended. Below 40% chance, no fungicide application would be recommended. In 2015, the first iteration of the model was validated in the field (West Madison Agricultural Research Station, Madison, WI) against a two-spray, calendar program (Endura® at 8 oz was the fungicide used). These treatments were compared to not treating. The advisory called for two applications of fungicide in 2015 due to the extremely favorable weather for disease. Therefore, disease levels were high and no savings of fungicide was achieved over the calendar program. However, white mold was low and yields were significantly higher in plots that received fungicide vs. plots that were not treated. The model also was very accurate in our validation experiments. The first fungicide spray was recommended by the advisory at the time when apothecial numbers were increasing and just prior to heavy spore catches. This allowed researchers adequate time to apply fungicide to protect plants prior to the conducive infection periods. The second application was also recommended with similar accuracy,during a second increase in apothecial numbers. In addition to the development of a potential advisory, this modeling exercise is helping to improve our understanding of the complex interaction of temperature and moisture required to make accurate white mold predictions. This understanding may also help us look a long-term forecasting in order to make disease predictions well in advance of an epidemic. Additional support from soybean growers in Michigan was also garnered by research colleagues at Michigan State University and the North Central Soybean Research Program has also pledged support for this research. Additional support has allowed us to collect additional apothecia and spore trapping data in Michigan which will be used in conjunction with additional Wisconsin data from 2015, in developing a new iteration of the model. Continued development and testing will occur in the 2016 field season in Wisconsin and Michigan.
Publications
- Type:
Conference Papers and Presentations
Status:
Accepted
Year Published:
2015
Citation:
Willbur, J.F., Lucas, H., Kabbage, M., and D.L. Smith. 2015. Development of a predictive model for Sclerotinia Sclerotiorum apothecial development to control white mold in soybean fields. Phytopathology 105:S4.148.
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Progress 09/01/14 to 09/30/14
Outputs
Target Audience: Soybean growers, agricultural industry professionals, and agricultural scientists in the State of Wisconsin and the North Central Region of the U.S. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided? Several groups in Wisconsin and the North Central region were presented with results of data from efforts conducted on this research project. Results were presented to eight separate groups in Wisconsin totaling 398 attendees. These groups were comprised mostly of growers and consultants. Approximately 100 attendees were also presented with thes data at the Illinois Ag Masters conference. This group was comprised of agriculture industry professionals and growers from the north central region. Data presented included progress in the development of Sclerotinia stem rot-resistant soybean germplasm. In addition, a doctoral level graduate student and an undergraduate student are being trained in plant pathology under this project. How have the results been disseminated to communities of interest? Approximately 498 individuals have been presented with data from this project at local and regional extension meetings in 2014. The data have been used to demonstrate new approaches to controlling Sclerotinia stem rot and highlight new technology coming down the pipeline. What do you plan to do during the next reporting period to accomplish the goals? The 2015 growing season will be used to collect further field data for making resistant soybean germplasm selection. Publically available weather data is being accessed and a series of statistical models to predict disease development will be generated for testing in the 2015 field season. Additionally, we are studying light quality effects on apothecial development for integration into an optimized forecasting model.
Impacts
What was accomplished under these goals?
Previously, resistant soybean germplasm was generated by crossing a highly resistant experimental line (W04-1002) with lines exhibiting good agronomic traits. After multiple screenings, 31 lines were selected for advanced white mold field screening in 2014. Lines were planted in a nursery with four check varieties. Disease ranged from almost 60 disease severity index (DSI) units in the susceptible breeding line 91-44 to zero DSI units for SSR81-23. All lines identified as physiologically resistant in greenhouse evaluations had less than 20 DSI units in the field trials. Yield loss is generally not expected until rating reaches 25 or more DSI units (Smith, personal communication). Yield ranged from 55.9 bu/a for AxN-1-55 to 26.6 bu/a for SSR81-123. Lodging was an important yield component in this trial. Lodging was significantly (α=0.05) correlated with yield. Breeding lines that lodged severely, yielded less than lines that had lower lodging scores (correlation coefficient = -0.47). Lines with the best physiological resistance to white mold (mostly the 9 x 1 population) tended to yield low-to-moderately in the 2014 trial. Further evaluation and selection will take place in 2015 using 17 advanced lines. These will include: 41-39, 51-23, 51-27, 52-11, 52-14, 52-82B, 81-207, 91-103, 91-145, 91-224B, 91-38, SSR42-136, SSR42-143, SSR51-70, SSR81-107, and SSR81-62. Also, in 2014, we monitored the growth and development ofS. sclerotiorumand collected detailed data of the progression and severity of white mold disease in Wisconsin soybean fields.
Publications
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