A Method for the Efficient Management and Utilization of Large Germplasm Collections

Abstract

To make efficient use of large germplasm collections, it is advisable to assemble a representative core collection and to evaluate the relationships among the traits studied. However, 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. The objects of this study were (i) to develop a method which assembles a core collection by maximizing the diversity (measured as mean Euclidean distance) from within groups of accessions defined by species, subspecies, and geographic origin and (ii) to test the effectiveness of the method on a collection of 20 997 annual Medicago accessions from the Australian Medicago Resource Center in Adelaide, South Australia, that had been evaluated for 27 agronomic characteristics. The method resulted in a core collection of 1705 accessions that represented 74% of the extremes of the 27 characters, indicating that the entire range of the characters was represented in most cases. Accessions representing the extremes easily could be added to the core collection. The method used requires relatively minor computing resources and should be useful to curators of large germplasm collections. To assess the relationships among the 27 measured traits, correlation coefficients of all possible combinations of traits were calculated. The most strongly associated traits were, as expected, such traits as grams of seed per plant and grams of pods per plant and indicated that some traits could be omitted from future evaluations with little loss of information, thereby increasing the efficiency with which germplasm evaluations can be carried out.