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a Dep. of Plant Breeding, Tarbiat Modares Univ. P.O. Box 14115-336 Tehran, Iran
b Dryland Agricultural Research Institute, Kermanshah, Iran
* Corresponding author (dehghanr{at}modares.ac.ir).
Selection of lentil (Lens culinaris Medik) cultivars with wide adaptability across diverse farming environments is important, before recommending them to achieve a high rate of cultivar adoption. Seed yield of 11 lentil genotypes, tested in a randomized complete-block design with four replicates across 20 environments in Iran, was analyzed using site regression (SREG) stability model. The biplot technique facilitates a visual evaluation of superior genotypes, which is useful for cultivar recommendation and megaenvironment identification. A substantial amount of genotype x environment (GE) interaction for lentil grain yield was detected. Location (L) and genotype x location (GL) variabilities were the predominant components of total yield variation. The first two principal components (PC1 and PC2) of the SREG model accounted for 76% of the total GE interaction. There were four winning genotypes and three megaenvironments according to the SREG model. The best genotype in one location was not always so in other test locations. According to the ideal-genotype biplot, genotype G5 was better than all other genotypes; G5 exhibited both high mean yield and high stability of performance across environments. According to G + GE sources of variations, the genotypes (G4, G7, G9, and G10) were the most suitable varieties for the lentil-producing regions in Iran.
Abbreviations: ICARDA, International Center for Agricultural Research in Dry Areas E, environment main effect G, genotypic main effect GE, genotype x environment interaction GGE, G plus GE MET, multiple-environment trials SREG, site regression SVD, singular value decomposition
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Received for publication October 11, 2006.
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