Soybean growers across the US face several common yield limiting diseases that can result in annual losses from $2.2 to $4.6 million. Decision making tools provide a method to target fungicide applications, simultaneously improving fungicide efficacy and proactively delaying the development of fungicide resistance. With funding from soybean checkoff funds, the development of the Sporecaster app has been successful in helping farmers in northern states make fungicide application decisions for management of white mold. The Sporecaster platform has since been used to develop a framework for frogeye leaf spot for northern soybean growing regions. Given the importance of frogeye leaf spot to Southern, Mid-southern, and Atlantic regions, the present proposal aims to expand the frogeye leaf spot prediction framework to these regions. In addition, the proposal aims to consolidate research activities across these regions for two other common disease problems, Cercospora leaf blight and target spot, laying the groundwork for comparable prediction tools for these diseases. The project will use historical datasets of fungicide trials, new uniform fungicide trials, spore trapping networks, and improved detection tools for predominant foliar pathogens of soybean to develop the data necessary for developing prediction tools. Each of these will independently provide information relevant to soybean farmers and other stakeholders involved in soybean production, and will also be combined into higher impact decision making tools relevant across the U.S.

Objective 1: Expand the development and validation of frogeye leaf spot prediction tool to new regions, using the Sporecaster framework
Objective 2: Develop and conduct experiments to adapt the Sporecaster framework for Cercospora leaf blight prediction
Objective 3: Develop and conduct experiments to adapt the Sporecaster framework for target spot prediction
Objective 4: Communicate results of the research to farmers and other stakeholders involved with soybean production

1. Peer-reviewed publications that detail the development of prediction models and tools for Cercospora leaf blight, frogeye leaf spot, and target spot.
2. Peer-reviewed publication that reports on the most efficacious and economically viable fungicides for management of Cercospora leaf blight.
3. Peer-reviewed publication that reports on the most efficacious and economically viable fungicides for management of target spot.
4. Peer-reviewed publication that detail the geographical and temporal distribution of spores of important foliar fungal pathogens of soybean that will improve our epidemiological and biological understanding of these pathogens.
5. Updated foliar disease information on SRIN.
6. Updated Extension publications on frogeye leaf spot and new Extension publications on Cercospora leaf blight and target spot.

Updated June 16, 2024:
Uniform foliar fungicide trials have been planted at 15 locations across 11 states (AL, AR, DE, KY, LA, MS, NC, PA, TN, VA, WI). Growth stages at these locations vary from just recently planted to approaching R2 development stage. At least one location for each participating state has already or will be soon deploying spore traps at two different heights within a "no fungicide" area of the field. The spores will be collected throughout the season and will be analyzed via molecular quantification assays at the University of Wisconsin (Damon Smith Lab) and at Louisiana State University (Sara Thomas-Sharma Lab). Pathogens that will be quantified are Cercospora sojina (frogeye leaf spot pathogen), Corynespora cassiicola (target spot pathogen), and the different Cercospora species complex that cause Cercospora leaf blight. The Smith Lab recently hired Dr. Shalina Yerukala as a post-doc partially funded on this project. Dr. Yerukala is currently working to extract DNA from all spore trap samples. She is also working on developing a species-specific primer set for Cercospora sojina. The Smith Lab has a promising protocol they are working on and are hopeful that they will get the PCR protocol validated very soon. Once validated, they will begin processing spore trap DNA from all 2023 and 2024 samples. The Thomas-Sharma Lab is currently testing published qPCR assays to detect the target spot pathogen, Corynespora cassiicola, on soybean. The primers amplify an 85 bp product in the elongation factor 1 alpha (TEF1) gene of the pathogen. DNA extracted from 6 isolates of the pathogen from Kentucky was shared with their lab and were tested with the assay. An average DNA concentration of 20 ng/ul resulted in average cycle threshold values of 24.39. They are currently testing DNA of 6 more isolates collected in Arkansas. They are also going to collect isolates of the pathogen from Louisiana this growing season. Louisiana isolates together with isolates from Kentucky and Arkansas obtained from collaborators (once APHIS permits are obtained) will be used to develop standard curves of spore counts. The latter will allow them to determine spore counts of the pathogen collected on the spore trap samples.

Updated January 31, 2025:
Uniform soybean foliar fungicide field trials were conducted in nineteen different states (data from two projects were combined, where 11 states participating as collaborators in this project, and 8 states participating through a different regional project), in which eleven treatments and a nontreated check were evaluated. Primary disease pressure came from frogeye leaf spot (FLS; caused by Cercospora sojina) and Septoria brown spot (SBS; caused by Septoria glycines). Averaged across all locations, all fungicide treatments significantly reduced frogeye leaf spot severity compared to the nontreated control, where Revytek fungicide provided the greatest FLS reduction, but was not different than all other fungicide treatments except Trivapro and Quadris. For SBS management, only Miravis Neo and the three-way mixture of Echo + Folicur + Topsin were significantly different than the nontreated control. Averaged across all locations, only plots treated with Veltyma fungicide resulted in a significantly greater yield than the nontreated control. The data from the uniform fungicide trial were used to help revise the 2025 edition of the Crop Protection Network Soybean Foliar Fungicide Efficacy Guide. In addition, the data from these trials are being used to test, adjust, and optimize disease prediction models

Spore traps were deployed in soybean fields across eleven different states. Spore samples were collected at two different heights weekly. The samples were sent in bulk to the Smith Laboratory (University of Wisconsin), where DNA currently is being extracted from the 2024 spore samples. For the spore samples collected in 2023, all DNA have been extracted and the Smith Lab and Thomas-Sharma Lab (LSU) are enumerating spores of Cercospora sojina (FLS pathogen) and the species of Cercospora that cause Cercospora leaf blight. The Thomas-Sharma Lab also is developing a molecular assay to enumerate spores of the target spot pathogen (Corynespora cassiicola).

The Smith Lab continues to optimize and validate the “Frogpsotter” app that is used to forecast the risk of frogeye leaf spot A beta version of the app was made available for the 2024 growing season, and a protocol was developed to validate the risk model and evaluate spray thresholds on disease and yield. At several locations, fungicide treatments were applied at different timings based on either growth stage (R3, beginning pod) or a FLS risk threshold of 40%, 50%, and 60% if that risk occurred between R3 to R5. Weekly disease data and yield data were collected across all locations, and currently are being analyzed. The model currently uses a 21-day average of maximum air temperature and 10-day average of total daily hours with max relative humidity > 75% (wetting variable), and daily risk indices are calculated in the tool. The disease data collected from field trials are currently being used to retrain the model, and further field validation will occur during the 2025 growing season.

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Uniform soybean foliar fungicide field trials were conducted in nineteen different states (data from two projects were combined, where 11 states participating as collaborators in this project, and 8 states participating through a different regional project), in which eleven treatments and a nontreated check were evaluated. Primary disease pressure came from frogeye leaf spot (FLS; caused by Cercospora sojina) and Septoria brown spot (SBS; caused by Septoria glycines). Averaged across all locations, all fungicide treatments significantly reduced frogeye leaf spot severity compared to the nontreated control, where Revytek fungicide provided the greatest FLS reduction, but was not different than all other fungicide treatments except Trivapro and Quadris. For SBS management, only Miravis Neo and the three-way mixture of Echo + Folicur + Topsin were significantly different than the nontreated control. Averaged across all locations, only plots treated with Veltyma fungicide resulted in a significantly greater yield than the nontreated control. The data from the uniform fungicide trial were used to help revise the 2025 edition of the Crop Protection Network Soybean Foliar Fungicide Efficacy Guide. In addition, the data from these trials are being used to test, adjust, and optimize disease prediction models

Spore traps were deployed in soybean fields across eleven different states. Spore samples were collected at two different heights weekly. The samples were sent in bulk to the Smith Laboratory (University of Wisconsin), where DNA currently is being extracted from the 2024 spore samples. For the spore samples collected in 2023, all DNA have been extracted and the Smith Lab and Thomas-Sharma Lab (LSU) are enumerating spores of Cercospora sojina (FLS pathogen) and the species of Cercospora that cause Cercospora leaf blight. The Thomas-Sharma Lab also is developing a molecular assay to enumerate spores of the target spot pathogen (Corynespora cassiicola).

The Smith Lab continues to optimize and validate the “Frogpsotter” app that is used to forecast the risk of frogeye leaf spot A beta version of the app was made available for the 2024 growing season, and a protocol was developed to validate the risk model and evaluate spray thresholds on disease and yield. At several locations, fungicide treatments were applied at different timings based on either growth stage (R3, beginning pod) or a FLS risk threshold of 40%, 50%, and 60% if that risk occurred between R3 to R5. Weekly disease data and yield data were collected across all locations, and currently are being analyzed. The model currently uses a 21-day average of maximum air temperature and 10-day average of total daily hours with max relative humidity > 75% (wetting variable), and daily risk indices are calculated in the tool. The disease data collected from field trials are currently being used to retrain the model, and further field validation will occur during the 2025 growing season.

This project will provide validated tools that soybean farmers across the U.S. can utilize to make important disease management decisions.