2016
Molecular Detection of Soybean Cyst Nematode in North Dakota
Contributor/Checkoff:
Category:
Sustainable Production
Keywords:
NematodePest
Parent Project:
This is the first year of this project.
Lead Principal Investigator:
Guiping Yan, North Dakota State University
Co-Principal Investigators:
Samuel Markell, North Dakota State University
Berlin Nelson, North Dakota State University
+1 More
Project Code:
Contributing Organization (Checkoff):
Institution Funded:
Brief Project Summary:

The soybean cyst nematode is a major pest for soybean production. Other cyst nematodes such as sugar beet cyst nematode, clover cyst nematode and cereal cyst nematode are known to or may be present in fields in North Dakota. These nematodes are very similar to SCN in morphology. Distinction between SCN and these nematodes is difficult and time consuming based on morphology using traditional microscopic methods. Molecular techniques offer new possibilities for distinguishing cyst nematode species. The goals of this research are 1) to differentiate SCN from sugar beet cyst nematode that is known to occur in ND and other closely related cyst nematodes that may be present in ND; and 2)...

Unique Keywords:
#nematodes
Information And Results
Project Deliverables

The soybean cyst nematode is a major pest for soybean production. Other cyst nematodes such as sugar beet cyst nematode, clover cyst nematode and cereal cyst nematode are known to or may be present in fields in North Dakota. These nematodes are very similar to SCN in morphology. Distinction between SCN and these nematodes is difficult and time consuming based on morphology using traditional microscopic methods. Molecular techniques offer new possibilities for distinguishing cyst nematode species. The goals of this research are;
1) To differentiate SCN from sugar beet cyst nematode that is known to occur in ND and other closely related cyst nematodes that may be present in ND.
2) To detect SCN sensitively and directly from DNA extracts of field soils with low SCN densities.
The project we propose here will lead to an effective detection system that is capable of identifying SCN from fields co-infested with sugar beet cyst nematode and improving SCN detection efficiency in soybean fields infested with low level of SCN. This detection system will speed SCN test results to growers and prevent false positive detection from the traditional SCN counting method. Sensitive and accurate detection of SCN is essential for recommending effective measures to control SCN.

Final Project Results

The United Soybean Research Retention policy will display final reports with the project once completed but working files will be purged after three years. And financial information after seven years. All pertinent information is in the final report or if you want more information, please contact the project lead at your state soybean organization or principal investigator listed on the project.