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Crop Science Abstract -

Custer Analysis for Genotype × Environment Interaction with Unbalanced Data


This article in CS

  1. Vol. 35 No. 5, p. 1300-1305
    Received: May 6, 1993

    * Corresponding author(s): zhao@ins.infonet.net
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  1. Z. Ouyang ,
  2. R. P. Mowers,
  3. A. Jensen,
  4. S. Wang and
  5. S. Zheng
  1. ICI Seeds, Research Dep., 2369 330th Street, Slater, IA 50244



From the viewpoint of a seeds business, classification of locations into homogeneous groups based on genotype × environment interaction (GE) facilitates selection of testing sites and proper placement hybrids or cultivars. Our principal objective was to develop methods to cluster ICI Seeds' strip-test locations into homogeneous groups with respect to GE. Difficulties encountered in these cluster analyses included missing values in the distance matrix used for cluster analysis (caused by unbalanced data), selection of a proper distance measure, and graphical presentation of clusters. We propose use of a modified distance measure to resolve the first two difficulties. Dendograms are used to present clusters, and bar charts are used to show relative effects of individual hybrids or cultivars within clusters. Classification of counties in Iowa is into four groups: northern, central, southeastern, and southwestern regions. The results of the GE analyses compare favorably with breeder and agronomist observations on hybrid adaptation and show some similar groupings with divisions of the state specified in the Iowa State University yield test report.

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Copyright © 1995. Crop Science Society of America, Inc.Copyright © 1995 by the Crop Science Society of America, Inc.