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ARS Home » Midwest Area » Madison, Wisconsin » U.S. Dairy Forage Research Center » Dairy Forage Research » Research » Publications at this Location » Publication #426510

Research Project: Developing Sustainable Forage and Cover Crop Systems for Dairy Farms

Location: Dairy Forage Research

Title: Data from: hairy vetch (Vicia villosa Roth) germplasm contains a cryptic second species (Vicia varia Host)

Author
item Tilhou, Neal
item Raasch, John
item Kucek, Lisa
item Riday, Heathcliffe

Submitted to: Ag Data Commons
Publication Type: Database / Dataset
Publication Acceptance Date: 5/19/2025
Publication Date: 5/19/2025
Citation: Tilhou, N.W., Raasch, J.A., Kucek, L.K., Riday, H. 2025. Data from: hairy vetch (Vicia villosa Roth) germplasm contains a cryptic second species (Vicia varia Host). Ag Data Commons. https://doi.org/10.15482/USDA.ADC/29042735.v1.
DOI: https://doi.org/10.15482/USDA.ADC/29042735.v1

Interpretive Summary: This dataset is data on DNA markers from hairy vetch individuals in a breeding program which is attempting to produce improved strains for use on farms. During our work, we found that hairy vetch populations are a mix of two different species which look similar. These DNA markers were used to characterize the genetic backgrounds of individuals in the breeding program and in commercial seed which farmers use.

Technical Abstract: In an effort to improve cover crop performance, we have been breeding improved strains of the cover crop hairy vetch. Based on field data and molecular data, we realized that hairy vetch germplasm contains a genetically isolated subpopulation which can be reasonably considered a distinct species called smooth vetch (Vicia varia Host). These two species are visually quite similar, but have differences in agronomic performance (flowering time and winter survival). To provide a rapid, low cost method to screen individuals and determine their species, we collected single sequence repeat (SSR) marker data on a large number of individuals in the breeding program. Using individuals with known species identities from next-gen sequencing, we built a model to discriminate between the two species of vetch using a linear discriminant model. Properly identifying strains of cover crop vetch can improve agronomic outcomes and breeding progress.