Statistical Approaches to Analyse Gene Bank Data Using a Lentil Germplasm Collection as a Case Study


Normally in a plant gene bank a large number of accessions per each crop and/ or taxon is stored. During their characterization and preliminary evaluation, several quantitative and qualitative data are recorded and, usually, a wide intra accession variation is observed. Th e management of all this information becomes very difficult without effective statistical methods combining these different types of data. At the Institute of Plant Genetics, CNR, in Bari (Italy) this problem has been tackled by testing many statistical approaches. The present contribution describes one of these approaches, which to date has proven to be highly adequate; a case study describing a lentil germplasm collection has been used for demonstration. A valuable application of this method is the determination of core subsets important to increase the utilization and accessibility of plant genetic resources. In the presented case study a subset of the lentil germplasm collection was chosen to perform molecular analysis based on ISSR markers. The samples were selected on the basis of both morpho-agronomic evaluation and geographical origin. These markers proved to be useful for distinguishing among closely related genotypes and for possibly substantiating the genetic peculiarity of some interesting material

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