Soybean cyst nematode (SCN) is the most significant disease threat to soybean production in the United States, and it continues to spread in North Dakota. Management tools for SCN are available, but a 15-30% yield loss is common before above ground symptoms appear. Making proactive identification and monitoring are critical for two reasons. First, soil sampling is the best way to initially detect SCN, this is increasingly important in the western, central, and northeastern parts of the state. Second, monitoring egg levels allows growers to evaluate how well their management tools are working and is increasingly important in the southeast and east central parts of the state. In 20 I 3, the NDSC and NDSU developed a free-sampling-bag program for growers, in order to encourage growers to sample for SCN. Since 2013, approximately 4,300 samples have been submitted by North Dakota producers using this program. Maps generated from the project have served as a highly leveraged tool to increase awareness of the expanding SCN problem in North Dakota. We propose to continue this sampling program in 2022.

1. Provide incentive for growers to sample for SCN by covering the cost of up to three SCN samples (pre-labeled bags) per grower on a first come first-serve basis (up to 2,000).
2. Creation of a SCN distribution map (limited resolution -no farms or growers can be
identified) that can be used to determine how widespread SCN is. This map will be
widely distributed in an effort to encourage growers to sample and/or manage SCN.

1. Sample bags distributed to soybean growers.
2. Maps of SCN distribution in the state. These will be distributed throughout winter and summer events, websites, the NDSU Crop and Pest Report, ag media and others.

Update:
2022 Mid-Term Progress Report
Prepared by: Sam Markell
Date: 11/29/22

SCN sampling bags, instructions and sample submission forms were delivered to every NDSU County Extension office in August, 2021. Electronic versions of instructions and sample submission forms were also distributed through NDSU listservs. Interviews were conducted to advertise and emphasize the importance of sampling and the opportunity provided by the North Dakota Soybean Council and program. Upon request, sampling bags (and materials) were provided to multiple crop consultants, elevators and other grower-advisors directly by Dr. Markell.

To date, 321 samples have been received. Draft maps for 2021 have been created. Of greatest interest are three new ‘hot spots’ in the state. Specifically, a location in SE Walsh County (egg count in range of 10,001-20,000 eggs/100cc), a location in NE Stutsman County (egg count in range of 2,001 – 10,000 eggs/100cc) and a location in NE Kidder County (egg count in range of 201 – 2000 eggs/100cc). These new finds are the highest known levels within approximately 20 to 50 miles. Of additional interest, significant numbers of samples were taken in Benson County, all of which are reported as ‘0’. This type of intense sampling is critical for the detection of new areas of concern, or, an indication that SCN is either rare or not reported in counties on the edge of SCN distribution.

Maps will be distributed at winter meetings (real and/or virtual), through NDSU Extension, the SCN Coalition (www.thescncoalition.com), willing media partners and likely by partnerships (magazine, media, etc..) with the North Dakota Soybean Council and North Dakota Growers Association. We thank the North Dakota Soybean Council for their support.

Update:

View uploaded report

Research Project Description:
Soybean cyst nematode (SCN) is the most economically important biological threat to soybean production in the United States, and the nematode continues to expand in North Dakota. Soil sampling is the most reliable way to detect the presence of SCN and the most effective way to determine how well management tools are working in soybean fields. This project supports a sampling program for soybean growers which increases our understanding of SCN prevalence in North Dakota.

Research Conducted:
Pre-labeled soil-sampling bags are distributed to soybean growers and their advisors through NDSU Extension in late summer and early fall. The NDSC covers the laboratory fees of samples submitted to Agvise (partner laboratory), growers receive their data directly through the mail, and NDSU Extension receives egg level and geographic data to construct maps (no additional information about submitters or field is obtained).

Results of the Research:
In 2022, 397 total SCN samples were received, of which 201 were found to have at least 50 eggs+ J2/100cc soil. Three new findings had the highest reported egg levels within an approximate 20 to 50 miles radius, including locations in SE Walsh, NE Stutsman, and NE Kidder Counties. In contrast, robust sampling throughout Benson County was conducted and all samples were reported as negative (0), suggesting that even if SCN is suspected (or known), it may not be an immediate threat in any given area. Since 2013, 4,806 samples have been mapped, which has increased our understanding of the SCN-threat in to soybean growers in ND.

Benefits/Recommendations to the North Dakota Soybean Farmers and Industry:
For growers who have not detected SCN before, we recommend that they concentrate on areas in the field where SCN is most likely to first be introduced, such as field entrances. For growers who know they have SCN, we recommend they soil sample to determine how well current management strategies are working.

Acknowledgements:
We thank growers, Extension agents and others who participated in this program, Michaela Halvorson for map construction, Agvise for sample processing, and the North Dakota Soybean Council for support.

For growers who do not know if they SCN or are in areas where distribution of SCN is expanding (the western, central and northern pa1ts of the state). This program benefits them by providing them a mechanism and incentive (lab fees paid by NDSC) to sample for SCN. For growers who know they have SCN, this program benefits provides them by providing a
mechanism and incentive to determine their SCN egg count, which can help them evaluate how well their management tools are working.