Stability analysis of seed yield in safflower genotypes in Iran

Abstract

To assess the stability and yield performance of safflower genotypes and to identify subregions within Iran, a set of experiments was conducted at six locations during [2003][2004][2005]. AMMI model analysis and some stability parameters derived from the grain yield were used. AMMI analysis showed differences between genotypes and environments and the GE interaction was highly significant, indicating that the agro-climatic environmental conditions were different, and that there was a differential response of the genotypes to the environments. The first two IPCA components of the GE interaction explained 51.5% of the GE interaction. According to the AMMI model, G16 was the most superior genotype in 15 out of 18 environments. The biplot of IPCA1 and IPCA2 showed that the six locations represent different environments, and mega-environments in Iran were identified for safflower breeding programmes. Due to the great fluctuation observed when selecting genotypes through stability parameters, it was not possible to distinguish stable genotypes clearly. In addition, when calculating these parameters high yield performance is not considered. So the Yield and Stability Index (YSI) can be recommended as a new approach to facilitate genotype selection, where genotypes with low values of YSI are the best. According to YSI the genotypes G16, G2, G9 and G1 can be selected. These genotypes were also selected using the AMMI model.

Improvement of yield and yield stability in safflower using multivariate, parametric and non-parametric methods under different irrigation treatments and planting date

“…a large proportion of the square sums for environment in our GE analysis indicated diversity among the environments studied. This finding is in agreement with those previously reported on safflower (abdulahi et al, 2009;moghaddam & Pourdad, 2009;Ebrahimi et al, 2016). The biplot constructed with seed yield and IPCa 1 for genotype and environment on the X and y axes, respectively, can be interpreted by comparing the i scores of IPCa 1 for each genotype and environment (Gauch & Zobel, 1996).…”