| چکیده انگلیسی مقاله |
Extended Abstract Introduction and Objectives
The increased demand for cereals that are consumed by humans and livestock can be met through the development of planting of drought-tolerant genotypes. Due to the interaction of genotypes × environment, the best genotype in one environment may not be the best in other environments, and therefore, this interaction provides valuable information about the yield of each genotype in different environments and plays an important role in evaluating the yield stability. Genetic modification of drought tolerance in crops is one of the most stable and cost-effective approches to increase production and yield stability. Examining the compatibility and stability of grain yield based on various parametric and non-parametric stability statistics and evaluating tolerance to drought stress based on stress indices in the barley promising genotypes of the country's temperate climate are among the goals of this research.
Materials and Methods
To assess the adaptation and stability of grain yield and to select high-yielding barley genotypes suitable for terminal drought stress in the temperate climate of the country, the number of 16 barley genotypes were cultivated during the two crop years of 2021-2023 in the randomized complete blocks design with three replications in three research stations including Varamin, Birjand and Yazd under two conditions of none stress and drought stress at the end of the season (12 environments). After determining the grain yield, stress indices including MP, GMP, TOL, HARM, STI, YI, YSI, RSI and SSI and the correlation of each of them with grain yield were calculated. Stability statistics in this study include Nassar and Huehn’s stability statistics (S(1-6)), Thennarasu’s stability statistics (NP(1-4)), deviation from regression (S²dᵢ), regression coefficient (b), Shukla’s stability variance (σ²ᵢ), environmental variation coefficient (CV), variance component (θᵢ), coefficient of variance (θ(i)), Wricke’s ecovalence (Wᵢ²) and Kang’s sum of ranks (KR) and their relationship were calculated based on Pearson correlation. Analysis of variance, mean comparison and simple correlation were calculated using SAS-9.0 program, stability statistics were calculated using STABILITYSOFT, and principal component analysis, stress indices and correlation of each of these indices with grain yield were calculated using iPASTIC. The three-dimensional distribution diagram of genotypes in the ranges A, B, C and D was also drawn using Grapher software.
Results
The results of the combined analysis of variance indicated the significance of genotype×environment interaction. According to S(1-2) statistics, G7, G10, G11 and G3 genotypes and according to S(3-6) statistics, G7, G3 and G9 genotypes were the most stable genotypes. Among the non-parametric Thennarasu’s stability statistics according to NP(1) criterion of G9, G3 and G5 genotypes, according to NP(2) G5, G3 and G8 genotypes and according to NP(3) and NP(4) criteria, G7, G3 and G9 genotypes were recognized as the most stable genotypes. Based on Wricke (W²) and Shukla (σ²) equivalency stability statistics, genotypes G3, G9 and G13 were the most stable genotypes. Based on Eberhart and Russell's regression method, G9, G7 and G3 genotypes, which also had high yield, had general compatibility and good yield stability. Based on Francis and Kannenberg (CVi), genotypes G1, G2 and G15 had the lowest coefficient of environmental variation. On the other hand, based on the average rank of each genotype in all stress indices (AR), G2, G7 and G3 genotypes were the most tolerant and G14, G11 and G10 were the most sensitive genotypes to drought stress at the end of seasons, respectively. In the conditions of drought stress at the end of the season, grain yield had a positive and significant correlation with YI, HM, GMP, STI, MP, YSI and RSI indices and a negative and significant correlation with SSI index. In non-stress conditions, grain yield had a positive and significant correlation with MP, GMP, STI, HM and YI indices, but no significant correlation was observed between grain yield and SSI, TOL, YSI and RSI indices. The analysis of principal components also showed that the first principal component explained 69.71% and the second principal component explained 30.27% of the variance of the main variables. The first main component has a positive and high correlation with yield in both stressed and non-stressed environments, as well as MP, STI, GMP and HM indices, and the second component also has a positive and high correlation with grain yield in non-stressed environment and TOL and SSI indices and it also had a negative and high correlation with RSI and YSI indices. Based on the biplot diagram, G3, G7, G8, G9, G12 and G13 have higher grain yield potential and are more tolerant to drought stress.
Conclusion
Grain yield in this study had a negative and significant correlation with NP(3), KR, NP(2), NP(4), S(6) and S(1) statistics, respectively, and therefore these statistics can be used for identifying stable genotypes. G3, G7 and G9 with averages of 6732.9, 6730.6 and 6608.1 kg/ha, respectively, not only had the highest grain yield but also had the highest grain yield stability and tolerance to terminal drought stress among the studied genotypes based on the total ranking of all studied stability statistics and stress indices, and they can be used as a new cultivar in drought-affected regions in the temperate climate or as desirable genetic materials in barley breeding programs for drought tolerance. |