Extended Abstract

1. Introduction: Barley is one of the most important cereal crops that have been crucial to the development of human’s comunities. Barley grain yield is strongly influenced by environments and breeders often determine the stability of high yield genotypes across environments before recommending a stable cultivar for release. Understanding genotype-environment (GE) interactions is crucial for assessing yield stability and genotype adaptability to different environmental conditions. Various non-parametric methods have been introduced to study and interpret genotype responses to environmental changes. These methods provide alternatives to parametric stability measures, especially when dealing with outliers in data, ensuring reliable evaluations. Non-parametric measures based on ranks can offer robust evaluation of genotype stability in different environments without relying on specific statistical assumptions. The current research aimed to compare the performance and assess the GE interactions in 18 barley genotypes across 4 locations over 3 years to identify stable genotypes with high yields.

2. Materials and methods: Each year, 16 lines and two selected check cultivars of Mahoor and Khorram were tested at 4 different research stations in Iran in a randomized complete block design with 3 replications. All research stations are located in warm weather in Iran including Gachsaran, Moghan, Khorramabad and Gonbad. The experimental plot consisted of six rows with 6 m long and 0.2 m spacing between rows, which resulted in a plot area of 7.2 m2 and the seed rate was 350 seeds per m2 for each genotype. Grain yield was determined for each genotype at each plot after removing margin effect at test environments. Various non-parametric methods were used to estimate the stability of the studied genotypes.

3. Results and Discussion:

The results of the combined analysis of variance indicated that the main effect of genotype, the two-way and three-way interaction between genotype, year, and location were significant at the 1% probability level. Therefore, various non-parametric methods were used to identify stable lines. The environments used in this study are unique and have many differences in terms of climate, soil conditions and agronomic management, so the dynamic stability of the cultivars was of great importance to us. So, methods that have a high correlation with the performance of lines were used. In order to select stable and high-yielding lines, the stability statistics of Fox et al. (1990) and the average stability rank were selected. Based on these statistics, lines 1, 2, 13 and 18 are selected and introduced as the most suitable hybrids in the tested environments. To understand the nature of relationships among the nonparametric methods and grouping of barley lines, a hierarchical cluster analysis was performed. The 13 nonparametric statistics and 18 barley lines were grouped in three and five distanced groups, respectively.

4. Conclusion: In conclusion, several of stability statistics that have been employed in this study quantified stability of lines with respect to yield, stability and both of them. Considering the high importance of dynamic stability for us, the stability statistics of Fox et al. (1990) and the average stability rank were selected, based on which lines 1, 2, 13 and 18 are selected and introduced as the most suitable lines in the studied environments. Given the dynamic nature of the stability of these genotypes, their performance will increase with the improvement of environmental conditions and the use of useful agricultural inputs will further improve their performance.