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Crop Science Abstract - CROP BREEDING & GENETICS

Nonparametric Methods for Interpreting Genotype × Environment Interaction of Lentil Genotypes


This article in CS

  1. Vol. 46 No. 3, p. 1100-1106
    Received: June 13, 2005

    * Corresponding author(s): dehghanr@modares.ac.ir
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  1. Naser Sabaghniaa,
  2. Hamid Dehghani *a and
  3. Syyed Hossain Sabaghpourb
  1. a Dep. of Plant Breeding, Tarbiat Modares Univ. Tehran, P.O. Box 14115-336, Tehran, Iran
    b Dryland Agricultural Research Institute, Kermanshah, Iran


Analysis of multienvironment trials (METs) of crops for cultivar evaluation and recommendation is an important issue in plant breeding research. Evaluating both stability of performance and high yield is essential in MET analyses. The objective of this investigation was to compare 10 nonparametric stability methods and apply nonparametric tests (which do not require distributional assumptions) for genotype-by-environment (G × E) interaction to 11 lentil (Lens culinaris Medik) genotypes. Nine improved lentil genotypes and two local cultivars were grown in 20 semiarid environments in Iran from 2002 to 2004. Results of nonparametric tests of G × E interaction and a combined ANOVA across environments showed there were both crossover and noncrossover G × E interactions and genotypes varied significantly for yield. In this study, high values of TOP (proportion of environments in which a genotype ranked in the top third) and low values of rank-sum (sum of ranks of mean yield and Shukla's stability variance) were associated with high mean yield, but the other nonparametric methods were not positively correlated with mean yield and instead characterized a static concept of stability. The results of principal component (PC) analysis and correlation analysis of nonparametric stability statistics and yield indicated that only rank-sum and TOP methods would be useful for simultaneously selecting for high yield and stability. These methods recommended FLIP 92–12L as stable and FLIP96–6L as unstable genotypes. A biplot of the first two PCs also revealed that the nonparametric methods grouped as three distinct classes that corresponded to different agronomic and biological concepts of stability.

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