Stability of performance in lentil (Lens culinaris Medik) genotypes in Iran |
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| Authors: | Mehdi Mohebodini Hamid Dehghani Sayyed Hossain Sabaghpour |
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| Institution: | (1) Dryland Agricultural Research Institute (DARI), P.O. Box 67145-1164, Kermanshah, Iran;(2) International Centre for Agricultural Research in the Dry Areas (ICARDA), P.O. Box 5466, Aleppo, Syria |
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| Abstract: | The development of genotypes, which can be adapted to a wide range of diversified environment, is the ultimate goal of plant breeders in a crop improvement program. In this study, several stability methods were used to evaluate the genotype by environment interaction (GE) in 11 lentil (Lens culinaris Medik) genotypes. The genotypes were evaluated for grain yield at 4 different locations for 3 years in semi arid areas of Iran. The testing locations have different climatic and edaphic conditions providing the conditions necessary for the assessment of stability. A combined analysis of variance, stability statistics, rank correlations among stability statistics and yield stability statistic were determined. Significant differences were detected between genotypes and their GE interactions. Different univariate stability parameters were used to determine stability of the studied genotypes. The level of association among the parameters was assessed using Spearman's rank correlation. The different stability statistics which measured the different aspects of stability was substantiated by rank correlation coefficient. Rank-correlation coefficients between yield and some stability parameters were highly significant. Genotypes mean yield (Mean) was significantly correlated to the Lin and Binns stability parameter PI (r = 0.93*
*í) and desirability index Di (r = 0.89*
*í). A principal component analysis based on rank correlation matrix was performed for grouping the different stability parameters studied. In conclusion, based on most stability parameters, the genotypes G2, G5 and G9 were found to be the most stable. Results from rank correlation and principal component analysis showed that the stability variance (σi
2) was strongly correlated with Wricke's ecovalance, stability parameters of Plaisted and Peterson, and Plaisted. |
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