|Johnston, W. - WASHINGTON STATE UNIV.|
|Nelson, M. - US GOLF COURSE ASSOC.|
|Golob, C. - WASHINGTON STATE UNIV.|
Submitted to: Book Chapter
Publication Type: Book / Chapter
Publication Acceptance Date: January 1, 1999
Publication Date: December 1, 1999
Citation: Johnson, R.C., Johnston, W.J., Nelson, M.C., Simon, C.J., Golob, C.T. 1999. Core utilization and development: an example with poa pratensis l. In: Johnson, R.C. and Hodgkin, T. editors. Core Collections for Today and Tomorrow. Rome, Italy: ICGRI. p. 49-60. Interpretive Summary: A core collection is a subset of a larger germplasm collection usually made up of seeds collected from diverse sites and countries. It offers a way to improve access to germplasm collections by providing a highly diverse, representative subsample of the total collection. The future of the Poa pratensis L. (Kentucky bluegrass) seed production industry in the U.S. depends on the development of new germplasm with both high turf quality and seed production potential. Evaluation of the entire USDA-ARS collection for these attributes would, however, be prohibitively expensive and impractical. In this study we used a core collection to identify genetic types with high turf and seed production. We also compared several methods of developing core collections using agronomic and molecular data (RAPDs). The results showed that both agronomic and molecular marker data could be used to produce high quality core collections in Kentucky bluegrass. However, it appeared that the agronomic data when used with the proper statistical approach produced a core that maximized both agronomic and molecular diversity and gave the highest overall quality. This work showed how core collections have increased access and utilization of the Kentucky bluegrass germplasm collection.
Technical Abstract: Core collections offer a way to improve access to germplasm collections by providing a highly diverse, representative subsample of the total collection. Our objectives were to compare methods of developing core collections using agronomic and molecular data, and identify a core best suited for future utilization and testing. From 228 total accessions, cores representing 10% of the collection were developed using random sampling, UPGMA hierarchal cluster analysis, and stratification by broad geographic regions. Cores developed from cluster analysis of agronomic attributes provided cores with increased variances and ranges compared to cores developed without cluster analysis. This resulted from more uniform sampling of accessions from the total collection. Stratification over broad geographic areas without clustering produced cores that were similar to a core selected at random. The RAPD based core selected with cluster analysis, and without geographic stratification, had a lower Sorenson matrix mean (less mean similarity) than any other molecular core (P<0.05), indicating high genetic diversity. In addition, the UPGMA agronomic core (without stratification) had increased molecular diversity (lower Sorenson matrix mean) when analyzed with RAPD marker data. Thus, it provided a core with both high agronomic and molecular diversity, and among the cores developed, appeared to have the highest overall quality.