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United States Department of Agriculture

Agricultural Research Service

Title: A Method of Developing a Core Collection from Very Large Germplasm Data Sets

item Skinner, Daniel
item Bauchan, Gary

Submitted to: Journal of Heredity
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: September 28, 1998
Publication Date: N/A

Interpretive Summary: A method is described to systematically evaluate a very large data set of plant accession evaluations, and select a representative sample. The sample is designed to represent at least 70% of the variation present in the entire colletion, and be comprised of not more than 10% of the accessions. The method is a significant advance over existing methods because it greatly reduces the computing resources needed, and allows analysis of very large data sets heretofore unmanageable.

Technical Abstract: The assemblage of a core collection from very large germplasm collections is problematic. The computing resources needed to carry out genetic distance calculations and comparisons with commonly-available programs is prohibitively large. We have developed a method which assembles a core collection by maximizing the selected diversity (measured as mean Euclidian distance) from within groups of accessions defined by species, subspecies, and geographic origin. The effectiveness of the method was tested on a collection of 17,798 annual Medicago accessions that had been evaluated for 24 characters. The method resulted in a core collection of 1705 accessions that represented 90% of the extremes of the 24 characters, indicating that the entire range of the characters was represented in most cases. Accessions representing the extremes missed easily could be added to the core collection. The method used requires relatively small computing resources and should be useful to curators of large germplasm collections.

Last Modified: 4/19/2015