نوع مقاله : مقاله پژوهشی
عنوان مقاله English
نویسندگان English
Introduction: Identifying a congenially targeted production environment and understanding the effects of genotype by environmental interactions on the adaptation of chickpea genotypes is essential for achieving an optimal yield stability. Different models like additive main effect and multiplicative interactions (AMMI 1, AMM2), weighted average absolute scores of BLUPs (WAASB), and genotype plus genotype–environment (GGE) interactions were used to understand their suitability in the precise estimation of variance and their interaction.
Chickpea (Cicer arietinum L.) is a cool-season grain legume traditionally important in the human diet of Mediterranean and Asian countries that has been increasingly adopted as food globally. GEI can be studied by a number of methods, such as AMMI (additive main effect and multiplicative interaction) analysis or GGE biplot (genotype plus genotype-by environment). However, as long as these methods assume genotypes as random variables, they are not appropriate for analyzing the structure of the linear mixed-effect model (LMM). WAASB (weighted average of absolute scores) has been proposed to better characterize ideal genotypes and a superiority index, WAASBY, to select genotypes based on both yield performance and the WAASB stability score. One of the multivariate methods is AMMI analysis. The BLUP provides reliable estimates, but new insights to deal graphically with a random GEI structure are needed. using LMM, and proposes a new quantitative genotypic stability measure called WAASB, which is the Weighted Average of Absolute Scores from the singular value decomposition of the matrix of BLUPs for the GEI effects generated by an LMM.measure called WAASB, which is the eighted Average of Absolute Scores from the singular value decomposition of the matrix of BLUPs for the GEI effects generated by an LMM. The aim of this study was to evaluate the efficiency of yield stability analysis models and to assess genotype × environment interaction effect on seed yield of 18 chickpea genotypes for identifying high-yielding and adapted genotypes by BLUP and AMMI models.
Materials and Methods: Seventeen selective advanced genotypes of chickpea from ICARDA with one check variety (Azad) were evaluated across four locations (Gachsaran, Ilam, Gonbad, and Khoramabad) at two growing seasons (2014-2016), in a completely randomized block design with three replications. The data, the analysis of data was performed on 8 environments. Eighteen chickpea genotypes for identifying high-yielding and adapted genotypes by BLUP and AMMI models. Statistical analyses, including simple analysis of variance, combined analysis of variance, and stability analysis carried out by the metan (Multi-environment trial analysis) R package. Five AMMI stability indices, including ASV (AMMI stability value), SIPC (Sum of IPCs scores), EV (Eigenvalue stability parameter of AMMI), Za (Absolute value of the relative contribution of IPCs to the interaction), WASS (Weighted average of absolute scores), and simultaneous selection index (ssi) of these parameters, were used for stability evaluation of genotypes.
Results and Discussion: The results of Likelihood ratio test (LRT) showed that the effect of genotype and genotype × environment interaction on seed yield was significant. Therefore, the best linear unbiased predictors (BLUPs) analysis was considered appropriate for these data. According to AMMI stability value (ASV) index, genotypes 13, 16, 11, 4 and 6 had more yield stability. Simultaneous selection index (SSIASV) based on ASV identified genotypes 6, 16, 2,5 and 11 in terms of seed yield and yield stability as superior genotypes. Given that by using these simultaneous selection indices, genotypes with different patterns for multivariate trials can be considered similar, the results can be misleading. Based on the first two main components, AMMI2 biplot diagram identified genotypes 18, 12, 6 and 15 as genotypes with yield stability. The results of the mosaic diagram showed that the contribution of genotype and genotype × environment interaction were 15.45% and 84.55% of the total variation, respectively. Based on weighted average of absolute scores (WAASBY) index using BLUP analysis, genotypes 5, 12, 14, 15 and 18 were identified as high yielding with yield stability.
Conclusion: In general, us in mixed models as well as all the components in calculating the WAASBY index, it can be concluded that this index is superior to other indices. Genotypes 5, 12, 14, and 15 had high yield in most environments, and in most methods had good stability and could be candidates for the introduction of new cultivars.
کلیدواژهها English
