1- Horticulture Crop Research Department, Khorasan Razavi Agricultural and Natural Resources Resaerch and Education Center, AREEO, Mashhad, Iran.
Abstract: (6 Views)
Introduction: Barley (Hordeum vulgare L.) with a cultivated area of nearly one and a half million hectares and with a production of about three million tons per year after wheat is the main crop in the country. Khorasan Razavi province has the first rank of barley production in Iran with the production of 415,736 tons per hectare. Due to the low expectation of the barley crop in relation to water and soil conditions, this crop can have a better position in most of the poor, low rain, salty and low water lands of the country. Increase in yield is one of the primary aims pursued in plant breeding programs (Reynolds et al., 2009). Similar to other crops, insufficient yield stability in barley is recognized as a one of the factors responsible for the gap between actual yield and potential yield (Cattivelli et al., 2008). In breeding programs, the identification of superior genotypes is difficult due to environmental variability of target locations and the interaction of these variabilities with the investigated genotypes. Therefore, it is important to evaluate the advanced agronomic lines across various environments and over multiple years to ensure their yield stability and production (Yan and Rajcan, 2002). Many statistical models have been suggested to analyze GxE interaction. GGE (genotype plus genotype-by-environment) biplot method proposed by Yan et al. (2000) is a multivariate model, which is based on principal component analysis, that simultaneously represents G, E and GxE interaction on a graph known as biplot. GGE biplot is widely used in agricultural research as it provides a simple graphical interpretation of GxE interaction. The main objective of this study was to select the superior barley genotypes based on grain yield and its stability in temperate regions of Khorasan Razavi province.
Materials and Methods: 19 promising barley lines along with check cultivar Behrokh, were studied during 2018-2020 in Neishabour and Mashhad regions located at Khorasan Razavi province. The experimental design was a randomized complete block with three replications. Univariate (environmental coefficient of variation and Eberhart and Russell parameters) and multivariate (GGE biplot) methods were used to yield stability assessment of genotypes. Combined analysis of variance for grain yield was analyzed using ADEL-R software. The GGE biplot and univariate stability indices biplots methodologies were employed to analyze GxE interaction and characterization of barley genotypes using GEA-R software (Yan, 2001).
Results: The combined analysis of variance showed that the main effect of environment and genotype × environment interaction were significant at 1% probability level, while the main effects of genotype was significant at 5% probability level. The results also showed that about 51% of total variation was related to environment effect, 5.24% to genotype effect and 19.41% to genotype × environment interaction. Overall the average grain yield of the evaluated lines ranged from 5.838 to 6.651 ton /ha and the G15, G16 and G12 lines had the lowest and G8, G9, G11, G19 and G20 had the highest grain yield, respectively. Based on the environmental coefficient of variation, G3 and G2 were the most stable genotypes, respectively, but their grain yield was lower than the overall average. So based on this method G11, G9 and G19 were selected as stable genotypes with higher than average yield. The graph of regression coefficient and deviation coefficient from regression introduced G2 genotype, which had a below-average yield, as a stable genotype and G8, which was one of the most yielding lines, as genotype with high compatibility. Simultaneous evaluation of grain yield and stability through average environment coordinate (AEC) biplot showed that genotype G8 with the high grain yield was the most stable genotypes. There were many similarities between 2 years of Mashhad (The first environmental group) as well as 2 years of Neishbour (The second environmental group). The angles between these two environmental groups was about 90 degrees, indicating that they were indipendent in ranking of genotypes. Among the investigated environments, the environment of Mashhad in 2017 was close to the ideal environment. An ideal environment should clearly discriminates among genotypes and Simultaneously be a good representative of the target environment.Also according to resulting from biplot of barley promising lines in comparison with ideal genotype, G8 was identified as the ideal genotype. Moreover the closest genotype to it were G20 and G19. On the whole, the mentioned promising lines compared to other genotypes had high grain yield, stability and good general compatibility in the investigated environments. GGE biplot method is based on agronomic compatibility and stability, and therefore, the genotypes that are selected in this way, in addition to stability and compatibility, also have high performance.
Conclusion: In general, based on the results of this study, among the G8, G20 and G19 lines, the promising line/lines that retain their high yield and favorable characteristics compared to check cultivars after being examined in extension research experiments at farmers condition of temperate regions, can be selected as candidates for naming and introduction.
Materials and Methods: 19 promising barley lines along with check cultivar Behrokh, were studied during 2018-2020 in Neishabour and Mashhad regions located at Khorasan Razavi province. The experimental design was a randomized complete block with three replications. Univariate (environmental coefficient of variation and Eberhart and Russell parameters) and multivariate (GGE biplot) methods were used to yield stability assessment of genotypes. Combined analysis of variance for grain yield was analyzed using ADEL-R software. The GGE biplot and univariate stability indices biplots methodologies were employed to analyze GxE interaction and characterization of barley genotypes using GEA-R software (Yan, 2001).
Results: The combined analysis of variance showed that the main effect of environment and genotype × environment interaction were significant at 1% probability level, while the main effects of genotype was significant at 5% probability level. The results also showed that about 51% of total variation was related to environment effect, 5.24% to genotype effect and 19.41% to genotype × environment interaction. Overall the average grain yield of the evaluated lines ranged from 5.838 to 6.651 ton /ha and the G15, G16 and G12 lines had the lowest and G8, G9, G11, G19 and G20 had the highest grain yield, respectively. Based on the environmental coefficient of variation, G3 and G2 were the most stable genotypes, respectively, but their grain yield was lower than the overall average. So based on this method G11, G9 and G19 were selected as stable genotypes with higher than average yield. The graph of regression coefficient and deviation coefficient from regression introduced G2 genotype, which had a below-average yield, as a stable genotype and G8, which was one of the most yielding lines, as genotype with high compatibility. Simultaneous evaluation of grain yield and stability through average environment coordinate (AEC) biplot showed that genotype G8 with the high grain yield was the most stable genotypes. There were many similarities between 2 years of Mashhad (The first environmental group) as well as 2 years of Neishbour (The second environmental group). The angles between these two environmental groups was about 90 degrees, indicating that they were indipendent in ranking of genotypes. Among the investigated environments, the environment of Mashhad in 2017 was close to the ideal environment. An ideal environment should clearly discriminates among genotypes and Simultaneously be a good representative of the target environment.Also according to resulting from biplot of barley promising lines in comparison with ideal genotype, G8 was identified as the ideal genotype. Moreover the closest genotype to it were G20 and G19. On the whole, the mentioned promising lines compared to other genotypes had high grain yield, stability and good general compatibility in the investigated environments. GGE biplot method is based on agronomic compatibility and stability, and therefore, the genotypes that are selected in this way, in addition to stability and compatibility, also have high performance.
Conclusion: In general, based on the results of this study, among the G8, G20 and G19 lines, the promising line/lines that retain their high yield and favorable characteristics compared to check cultivars after being examined in extension research experiments at farmers condition of temperate regions, can be selected as candidates for naming and introduction.
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