Comparison of statistical methods to development of a core collection for a spring wheat collection
Marcin Studnicki
marcin_studnicki@sggw.edu.plKatedra Doświadczalnictwa i Bioinformatyki, SGGW Warszawa (Poland)
Wiesław Mądry
Katedra Doświadczalnictwa i Bioinformatyki, SGGW Warszawa (Poland)
Tadeusz Śmiałowski
Instytut Hodowli i Aklimatyzacji Roślin, Zakład Roślin Zbożowych w Krakowie (Poland)
Abstract
A core collection consists of a limited number of the accessions gathered in an existing collection, chosen to represent the genetic variability within the whole collection of plant genetic resources. The purpose of creating core collections is to improve the utilization of genetic resources in crop improvement programs. The aim of this work was both to present and evaluate different procedures of sampling and clustering and to assess the size of core collections. This paper describes the development of a core subset of the spring wheat germplasm collection maintained at the Department of Cereal Breeding and Quality Evaluation of the Plant Breeding and Acclimatization Institute in Kraków. 196 accessions of spring wheat were evaluated for 10 phenotypic traits in the seasons 1996–2001. The spring wheat core collection was established in tree steps. In the first step a total of 196 accessions were stratified into homogenous groups. Two methods of cluster analysis: Ward’s method and UPGMA (Unweighted Pair Group Method with Arithmetic mean) were comparatively used. In the second step, a number of entries per group was determined. Two strategies: proportional and logarithmic were used. In the final step of establishing core collections the actual entries were chosen. Five core collections contained 10%, 15%, 20%, 25% and 30% of objects from the whole collection. The mean percentage difference (MD%) and the variance difference percentage (VD%) were applied for screening optimal sampling strategy, cluster methods and size of core collections.
Keywords:
cluster analysis, core collections, plant genetic resources, spring wheatReferences
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Authors
Marcin Studnickimarcin_studnicki@sggw.edu.pl
Katedra Doświadczalnictwa i Bioinformatyki, SGGW Warszawa Poland
Authors
Wiesław MądryKatedra Doświadczalnictwa i Bioinformatyki, SGGW Warszawa Poland
Authors
Tadeusz ŚmiałowskiInstytut Hodowli i Aklimatyzacji Roślin, Zakład Roślin Zbożowych w Krakowie Poland
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