Methods of constructing core collections by stepwise clustering with threesampling strategies based on the genotypic values of crops

A genetic model with genotypexenvironment (GE) interactions for controlling systematical errors in the field can be used for predicting genotypic valu es by an adjusted unbiased prediction (AUP) method. Mahalanobis distance, c alculated based on the genotypic values, is then applied to measure the gen etic distance among accessions. The unweighted pair-group average, Ward's a nd the complete linkage methods of hierarchical clustering combined with th ree sampling strategies are proposed to construct core collections in a pro cedure of stepwise clustering. A homogeneous test and t-tests are suggested for use in testing variances and means, respectively. The coincidence rate (CR%) for range and the variable rate (VR%) for the coefficient of variati on are designed to evaluate the property of core collections. A worked exam ple of constructing core collections in cotton with 21 traits was conducted . Random sampling can represent the genetic diversity structure of the init ial collection. preferred sampling can keep the accessions with special or valuable characteristics in the initial collection. Deviation sampling can retain the larger genetic variability of the initial collection. For better representation of the core collection, cluster methods should be combined with different sampling strategies. The core collections based on genotypic values retained larger genetic variability and had superior representative s than these based on phenotypic values.