Study of grain yield stability of barley ( Hurdem vulgare L.) genotypes by AMMI model

Introduction Barley (Hordeum vulgare L.) After wheat, maize and rice is the fourth grain, which is cultivated for grain use and has a perennial diploid and polyploid, and has been dispersed throughout the world. The adaptation of cultivars in different environmental conditions in plant breeding programs is of particular importance. Reactions between genotypes and environmental effects are referred to as genotype and environment interaction.The interaction between the genotype and the environment creates complexity in yield prediction and is a challenge for plant production and breeding programs. Methods for reducing the interaction between genotype and environment and increasing performance can be used to select and introduce high-performance and sustainable lines in different regions. Therefore, the aim of this study was to investigate the genotype × environment interaction and adaptability and performance stability of 21 barley genotypes using the analysis of the main and multiplicative effects (AMMI) model. Data related to location and years in the form of integrated environment and data analysis were carried out based on six environments. Then AMMI analysis and calculation of the main components of the interaction effect for all genotypes and drawing of the plot and calculation of ASV stability index was performed using IRRISTAT software. Materials and methods The present experiment was carried out in randomized complete block designs with two replications during 2014-2015, 2015-2016, 2016-2017 under rain-fed and irrigation conditions (a total of six environments) at the research farm of Faculty of Agriculture, Razi University, Kermanshah, Iran. Findings The combined analysis of variance for grain yield showed significant differences for year, genotype, genotype × year, year × location and year × location × genotype effects. The results of the analysis of AMMI model showed a significant difference between genotype and environment and four components of the interaction for grain yield were significant. The first and second components in AMMI model accounted for 52.78% and 26.00% of the interaction sum of squares, respectively. Genotypes with high values of the first major components (positive or negative) have a high interaction with the environment, while the genotypes with the first major component near zero have lower interaction. Genotypes 2, 5, 8, 10, 13 and 20 with fewer values of the first component of interaction were more stable than the other genotypes. The value of ASV was obtained from the ratio of sum of squares of IPCA1 (the first component of interaction) to IPCA2 (the second component of the interaction) for each genotype. According to the stability Index, the genotypes 9, 12, 15 were selected with the lowest values of AMMI stability as most stable genotypes. In order to determine sustainable genotypes with general and specific adaptation, AMMI Biplot was used for different locations. The results showed that genotype 2, 5, 8, 10, 13, which are at the center of biplot, have general stability and the genotypes that are closer to any environment the environment have specific adaptability to the environment. Among stable genotypes, genotypes 10 (Roho / 4 / Zanbaka / 3 / ER / Apm / Lignee131 / 5 / Otis), 8 (Baladieldawaia / 5 / AwBlack / Aths // Arar / 3 / 9Cr279-07 / Roho / 4 / DD-14 / Rhn-03) and 2 (Zarjau/80-5151//Skorohod/3/Robur/WA2196-68//DZ40-66) had higher mean grain yield. Therefore, these genotypes can be proposed for using in future breeding programs to introduce new cultivars. Conclusion Combined analysis of variance showed significant effect of year, genotype and genotype × year interaction for grain yield. The significant effect of genotype indicates the diversity of studied genotypes in terms of grain yield. Among the stable genotypes, genotypes 2, 8 and 10 had also higher grain yield, therefore, it can be suggested that the genotypes can be introduced as new cultivars or for use in future breeding programs. However, it is not appropriate to use a stablity method to identify high-performance and stable genotypes, so, it is recommended to use different methods to assess the stability.