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This article in CS

  1. Vol. 23 No. 5, p. 811-815
     
    Received: Aug 16, 1982
    Published: Sept, 1983


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doi:10.2135/cropsci1983.0011183X002300050002x

Genotype ✕ Environment Interaction Analysis for Yield in Alfalfa1

  1. R. R. Hill and
  2. J. E. Baylor2

Abstract

Abstract

A trial with 49 entries of alfalfa, Medicago sativa L., was evaluated for total season yield under two harvest managements for 3 years at two sites. Data from the trial series formed a base for which methods of analysis of genotype ✕ environment interaction for perennial forage crops were compared. The methods of analysis included: a) routine multifactor analysis of variance with sites, managements, years, and entries as the main effects; b) linear regression of individual entry means on the mean of all entries in each environment as well as linear regression with the ith entry eliminated from the environmental mean; and c) an orthogonal contrast analysis that partitioned the variation over environmentfso r each entry into sources duet o years, sites, and managements and all possible interactions between these factors. Entries, all the two-factor interactions, and the site ✕ management ✕ entry interaction were significant sources of variation in the analysis of variance. There was significant variation in correlations among pairs of entries, and regression analysis did not provide a simple interpretation of the observed responses of genotypes to different environments. The orthogonal contrast analysis revealed that entries varied in their response to years (age of stand), sites, and managements. Entries that increased in yield relative to the average of all entries in the trial as the stand aged all had moderate or higher levels of resistance to Colletotrichum trifolii Bain (anthracnose) and Fusarium oxysporum Schlect. f. medicaginis (Welmer) Snyd. & Hans. (Fusarium wilt). We concluded that the orthogonal contrast analysis was easier to interpret than regression on environmental means for analysis of genotype ✕ environment interactions in perennial crops such as alfalfa, especially when a pattern such as the response to age of stand was present and could not be detected by the regression analysis.

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